Leading Learning

Many learning businesses know they need to innovate, but moving faster and experimenting can run headlong into culture and the fear of being wrong. This episode of the Leading Learning Podcast looks at why that happens and what to do about it.

Elizabeth Engel and Jamie Notter, co-authors of the white paper “Lean at Ten: Culture Eats Methodology for Lunch,” join co-host Celisa Steele to discuss the core elements of lean startup, the cultural patterns that can undermine using the methodology, and how pairing lean startup with design thinking can help organizations build empathy, surface assumptions, and learn more effectively.

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Download a PDF transcript of this episode’s audio.

Celisa Steele: [00:00:03] If you want to grow the reach, revenue, and impact of your learning business, you’re in the right place. I’m Celisa Steele.

Jeff Cobb: [00:00:10] I’m Jeff Cobb, and this is the Leading Learning Podcast.

Jeff Cobb: [00:00:17] Many learning businesses know they need to innovate, but moving faster and experimenting can run headlong into culture and the fear of being wrong. This episode looks at why that happens and what to do about it.

Celisa Steele: [00:00:29] The episode features my conversation with Elizabeth Engel and Jamie Notter, co-authors of the white paper “Lean at Ten: Culture Eats Methodology for Lunch.” Elizabeth is chief strategist at Spark Consulting, where she provides membership consulting and also helps associations with new product development using lean startup methodology. Jamie is a consultant, speaker, author, and self-proclaimed culture scientist.

Jeff Cobb: [00:00:55] Elizabeth explains the core elements of lean startup and why this approach is especially well suited to resource-constrained organizations like associations.

Celisa Steele: [00:01:04] And Jamie speaks to the cultural patterns that can get in the way of effectively adopting the methodology.

Jeff Cobb: [00:01:10] Elizabeth and Jamie also talk about pairing lean startup with design thinking, building empathy with learners, and taking practical steps to make organizations more agile and more willing to learn.

Celisa Steele: [00:01:22] If you’re trying to move faster or innovate without burning out your team, the conversation with Jamie and Elizabeth offers not just food but a feast for thought.

Celisa Steele: [00:01:38] I want to talk to you guys about “Lean at Ten: Culture Eats Methodology for Lunch,” the white paper that the two of you put out. That title refers to the lean startup methodology. I’m thinking that it would be great to have you explain briefly what that methodology is and why you think it can be helpful to associations. Elizabeth, I’m going to ask that of you.

Elizabeth Engel: [00:02:01] The methodology was developed by a guy named Eric Ries, and he had a background in Lean Six Sigma and also in startups. He had an epiphany that there was no point in working efficiently if you’re going the wrong way. Lean Six Sigma is all about process improvement, being efficient, and all that good stuff. But, if you’re going the wrong way, you just end up at the wrong destination faster. He wanted to stop this from happening as early in the process as possible. In any product development situation, he realized that you are making assumptions about certain things when you are thinking about developing something innovative, something new, for your audiences. You’re making an assumption about the audience, you’re making assumptions about whatever the problem is that you think that they have, and you’re making assumptions about what your solution might be for them, and any of those things could be off. What he did is he constructed a methodology to help you figure out if one of those things is off and course correct as quickly as you possibly can.

Elizabeth Engel: [00:03:05] There are a couple of key elements to the methodology, and they are called Lean Canvas. Basically, it’s a series of questions that helps you develop a one-page business plan that helps you surface your assumptions about audience problem and solution so that you can actually test them. How do you test them? That’s the core of the methodology. It’s the build-measure-learn cycle. The idea is you build something, then you measure what’s happening, and you learn from it. And the additional elements that help you do that—the thing that you’re building is an MVP. It’s a minimum viable product, which is a fancy way of saying a prototype. You’re basically trying to build something that approximates what your solution is with the absolute minimal investment of resources, broadly defined, that you can possibly do. Truly, it’s a beta. You are making a prototype. Then you are getting it in the hands of your audiences as quickly as possible—that’s the measure piece. And so, when you’re measuring what’s happening with your prototype, you’re not just asking people what they think; you’re giving them a call to action and asking them to do something and then seeing what happens. That requires you identify appropriate, useful, good metrics. That could be a whole podcast in and of itself—what are those things?

Elizabeth Engel: [00:04:39] There are tons of resources out there that can help you figure out what are metrics that actually matter to determine whether you’re going in the right direction on your audience problem and solution. And so the idea is you’ve got all this data, and you’re supposed to learn from it—that’s the third part of the cycle. And then what you’re doing with that data that you have, that learning that you gain from going through this cycle, is you’re making a decision to persevere (“We’re headed in the right direction; let’s keep going.”), to pivot (“We were not quite going the right way with regards to audience problem or solution, so we need to make some changes here.”), or kill it (“This whole idea is not going to work, and so let’s stop this, again, with a small investment of resources and move on.”). That whole small investment of resources thing that I keep mentioning is why I have felt, for the past 10 years or more, that lean startup methodology is so helpful for associations because people look at it, association execs might look at it and say, “Startup? I’m not a startup. Why are you pushing this on us?” And the answer is we have some things in common with startups, one of the most important being we have highly limited resources.

Elizabeth Engel: [00:05:54] Now, with startups, it’s all about your VC money and your runway, and that’s not our world. But associations tend to be resource-limited, and that’s not just money. It’s staff time and attention. It’s volunteer time and attention. It’s member time and attention. Because of that, we want to make sure that we are using those limited resources responsibly and in an efficient and effective way to try to help our members solve their biggest problems and achieve their most important goals. And that’s what lean startup methodology can do.

Celisa Steele: [00:06:30] Thank you for that explanation of the methodology and then for why you think it can help associations. Jamie, I have a question for you because it’s about culture, which I know is your area in particular. Part of what you argue in the white paper is that it’s culture that’s holding back many associations from being able to make use of lean startup methodology. First, will you define culture for us and how you think about that? Second, what are the cultural patterns in associations that tend to derail or undermine lean startup efforts?

Jamie Notter: [00:07:07] My definition of culture is pretty short. Culture is the collection of words, actions, thoughts, and stuff (sorry for the technical term) that clarify and reinforce what is truly valued in an organization. The culture in your organization is all about what’s valued because what’s valued drives behaviors. Whether you’ve paid attention to culture or had an all-on project to develop it or anywhere in between, you’ve got one. People know what’s valued, whether you told them or not. And sometimes you tell them what’s valued and then they say, “Yes, I know that’s what you’re saying, but that’s not really what’s valued.” People know what’s valued, and they know that through the words you use, how you describe your culture, what you talk about, through the behaviors, the actions, and, if the actions are different than the words, the actions win on that one. The behaviors are more important. Thoughts are about underlying assumptions, mental models, beliefs. Sometimes that stuff ends up driving behaviors in ways that are different than what you thought you would in your culture. And then stuff is just tangible aspects of work—the equipment you use, the way your office is designed, dress code, anything that’s not human. Those things also tell people what’s valued. That collection is a little complex, but it’s out there. That makes it clear what’s valued, and what’s valued drives behavior.

Jamie Notter: [00:08:25] For the second question, what we say is valued is not always what is valued, and what I have found around culture patterns is there are a lot of things inside organizations that everyone consistently says they want, like collaboration and transparency, and two that are relevant to lean startup, agility and innovation. We all want that, we say we want that, and we do value those things. Turns out there’s a competing commitment inside your culture that negates that value, or at least part of it. Innovation is the biggest one for lean startup. Elizabeth’s description of the lean startup methodology…this is not our first rodeo, by the way. We’ve done a bunch of podcasts. And that was the best, most succinct description so far, Elizabeth. I’ll give you an A+ on that one. It’s really clear—build, measure, learn. And prototyping requires engaging in what I call the practices of innovation, which is experimenting and sometimes being wrong and being okay to fail. Because, if all your experiments are right and they all succeed, you’re doing them wrong. You’re doing stuff you already know how to do. You’re not going to get innovation by doing stuff you already know. You need to be able to fail.

Jamie Notter: [00:09:39] There’s a commitment we have inside organizations, most cultures that says, “Look, I value innovation. I want to unlock new value. This is cool. Let’s do it—as long as nobody is ever wrong, as long as I don’t have to say I failed at something.” We value being right. We value being the smartest people in the room. We value providing right answers to our colleagues and helping move the ball forward. That’s a good thing to value, but, if you push too hard on that, it generates behaviors where people say, “Well, we can run an experiment, but I’m not going to tell anybody.” Or “We can run an experiment, but I’m only going to test a little tiny thing because I don’t want to have to go to the board and say ‘I did something, and it didn’t work.’” We’ve got this pattern where we value the concept but not the practice of innovation, which means we say we will be behind lean startup, and we will try it, and then no one does any experiments that are worth it, where you get the real learning. You do some experiments, but I probably could have told you that outcome without running that experiment. We make it small, and it doesn’t work.

Jamie Notter: [00:10:43] There are several patterns that impact that. Agility is one of them. We don’t fix things. We don’t stop things. That’s a challenge, I think, for doing this work. My original background is in the field of conflict resolution, so this is a bias of mine, but our inability to have difficult conversations makes doing lean startup really hard. And a lot of organizations have that. The number one correlation between the 64 things I measure in culture is managing change and managing conflict. If you can’t do your conflict, you’re going to have a tough time doing this change. It’s going to come out in the learning process, I think. You build, measure, and learn. What we learned was my original idea was right, but the customers were stupid, and we need to keep going forward. No one’s going to say, “No, we were wrong. This product is going to fail.” If you can’t have those real conversations, you dumb down the learning, and you end up doing the process but making not as good decisions and not getting as good results.

Celisa Steele: [00:11:47] I heard you mention innovation practices. You mentioned difficult conversations. In the white paper, you mentioned four culture areas. Those are two of them. You also mentioned effective action and organizational clarity. Maybe I already know the answer based on what you’ve shared, but do you see that one of those tends to be the hardest for associations? Again, you already mentioned specifically innovation practices right at the outset. Maybe that’s the answer. Maybe you have another answer.

Jamie Notter: [00:12:11] Which is the hardest? All of them. These are ones where most organizations, not just associations, struggle. And the organizational clarity one contains the silo issue. Everybody is bad at silos. And silos are fine. You can have silos. What I don’t want are silos where I can’t see what’s going on across those lines, where I can’t step over the line and engage with someone. It’s like you should have fences between your silos, but they should be a foot and a half high. I know where the lanes are, but I can get across if I need it, and I can see what you’re working on. That piece, again, is across the board, but, from working on culture in associations, that is almost always something that they actively work on when they start a culture design initiative—the silo question. So that piece is big. The innovation piece is big. But I will say they are not unique to associations. They cut across. I work mostly in associations, but I have also worked in government and corporate, and we’ve got a lot of data from those other industries, and the data looks the same.

Celisa Steele: [00:13:18] Elizabeth, that one other thing that you all mentioned in the white paper is design thinking and how you feel like it can pair well with the lean startup methodology. Tell me a little bit about how those two approaches reinforce each other and why you’re seeing a place for both in associations.

Elizabeth Engel: [00:13:38] Design thinking is creative problem-solving that relies on human-centered approaches to innovation, and the concepts of design thinking parallel lean startup concepts really well. The two methodologies really complement each other. If you read the white paper that we’ll give you the information about a little bit later on and that Celisa mentioned at the top of the podcast, you’ll see that it was our National Council of Architectural Registration Board’s case study, they were the ones who really built design thinking heavily into their particular—and this will be important to think about later—iteration of how lean startup works. What they realized, in putting together their lean startup practice, is that empathy with your audiences, your members, your learners, your customers, etc., is the key. That’s the secret sauce to making this thing go. You want to develop a member-centric, customer-centric perspective so you can learn what their real and significant problems are, what their most important goals are. That allows you to focus on providing solutions for those things. To Jamie’s point that he raised earlier, this whole idea of “Oh, the customers were just dumb. My idea is great.” No, the customer is not wrong. You might be wrong, but that’s okay as long as you learn something from being wrong. And that development of empathy and an empathetic practice of learning about your audiences is what’s going to make this thing go.

Celisa Steele: [00:15:16] That emphasis on empathy and the member perspective, the learner perspective, the user perspective, whoever that is, is really important. And I feel like it can be hard to get the time and attention of members, learners, those users whose perspective is ultimately so important and that you really want. I would love any practical suggestions you have for how an organization can get the input it needs. Jamie, I’m going to throw this softball to you.

Jamie Notter: [00:15:48] We say we don’t have the time to get the information from the users, the learners, whatever it is. In fact, we have all the time in the world to do that. We just choose to spend our time doing other stuff that’s not as valuable. One of my mantras in this conversation—and I’ve said this outside of lean startup stuff—is organizations run too lean. I don’t mean lean startup. I mean, we are doing more with less times 100 years, and we’ve created a system where we have no slack. We have no ability to do what we need to do. And it doesn’t have to be that way. One of the case studies that Maddie [Grant] and I wrote about in When Millennials Take Over is a software company in Ann Arbor, Michigan. I’m going to get this wrong, but they had a position in the organization—I think it rotated, so it wasn’t a permanent job description—but, on every project, someone was the customer anthropologist, and they went out and lived with them. It was like participant observation. If they were designing a wedding-planning Web site, someone went out there and planned a wedding with people who were planning weddings, talked to them about it, hung out with them, and went to the dress shops and did the stuff, and—this is the empathy stuff—learned their perspective deeply. And they managed to do that and be profitable.

Jamie Notter: [00:17:11] This is part of the agility piece because we’re not stopping things. We don’t stop things, and we don’t fix things, so we don’t have the bandwidth to do it. We need to get much more disciplined about what activities are generating value in our organization and stop doing the things that are not generating value. That’s a bigger-picture answer. I don’t know if it’s what you were looking for because you said “practical.” There’s nothing more practical than freeing up time by not doing things that are not providing value anymore. It is hard to do, though—I get it—because part of it’s cultural. Part of it’s just “We’ve always done it that way.” And part of it is, by doing certain things, you then generate the demand for those things, even though they’re not driving value. So it’s a tough conversation, but that’s where people should be focusing.

Celisa Steele: [00:18:00] You answered one side of the question—meaning if, in my association, we want to prioritize empathy with the people we serve, we need to put in the time and, like you’re saying, maybe stop doing something else so that we do have the time to do it. There’s the added layer too of, if you really want that member’s or prospective member’s input, that takes some time on their side, potentially depending on your instrument. How do you manage to make the case to the people that you want to build this product for? “We want to do it the best possible way, but we need your input.” And knowing that most people feel a lot of constraints and requests for their time and attention, how do you get them to engage and allow you, even once you do that work internally, to say, “Okay, this is important”? How do you get that external buy-in to say, “Okay, I’m going to participate and give you feedback,” whether that’s through a focus group, a survey, or whatever type of instrument you’re using?

Jamie Notter: [00:19:01] Elizabeth can probably say this better than me, but, for me, you’re not giving them a survey and a focus group and asking them what they want. You are delivering something that meets their need. You’re saying, “Hey, I’ve got something that is going to make your life better. It’s just an MVP.” (You wouldn’t say it like this.) “But it’s just an MVP. It’s just a prototype. But I want you to use it and have it make your life better.” That’s the incentive, I think, for someone to be involved. It’s like, “Hey, I actually get to get my job done faster because of this. I get to be happier at work because of this.” Whatever problem you’re solving, you deliver that in a small way, and they’re like, “You mean I get to use this, and it’s going to make my life better?” “Yes, I just need to have a conversation with you at some point about how it worked and what was great about it or bad about it.”

Elizabeth Engel: [00:19:54] And, yes, to add, the other piece of this is, “And, if it doesn’t make your life better, I need to know that. Tell me ’This did not make my life better.’ If it is making your life better, but it’s missing some stuff, I need to know that too.” One of the other things that people get freaked out about with this whole idea of giving somebody a prototype is, “My members are going to hate that. They’re not going to want to use something that’s not completely beautiful and perfect and fully functional and blah, blah, blah,” and sort of, yes, with a caveat. Some of your members do not want to be faced with a half-baked idea, a product that’s still in the process of being fleshed out, etc. Some of them can’t deal with that. But not all of them. And part of figuring out what your lean startup work is going to look like in your organization is figuring out who are my audience members that I go to them and say, “I’ve got a prototype. I want you to help me with this. Tell me what you think. What’s working? What’s not working? What’s missing? What did we put in that doesn’t need to be here?” They’re going to go, “That’s great. That’s exactly what I want to do.” You have to know who those people are.

Jamie Notter: [00:21:08] If you’ve got something that you’ve designed that you think is going to make their life better, and you’re testing that out, and nobody—including these people that you’ve identified that are the types that would dig this—has time to do it, then you’ve just learned you don’t got something here. You got to go back or pivot or whatever you’re going to do. So the “They don’t have time” thing is not an excuse because you can find people who like it, and, if they really don’t have time, it’s because they don’t like what you’re offering.

Elizabeth Engel: [00:21:39] And, in that particular instance, it’s very likely that although you may have identified a problem that they face, it is either not a real problem or not a significant problem. It’s not high enough up on their priority list. So, therefore, move on to solving something that’s a bigger deal for them.

Celisa Steele: [00:22:02] Elizabeth, I know in this white paper—and you’ve made the argument before that associations, many of them through their education and training and other offerings, while they serve lifelong learners, need to act themselves organizationally as a lifelong learner. Talk a little bit about what that looks like. How does an organization start behaving more like a lifelong learner?

Elizabeth Engel: [00:22:23] The key underlying attitude change that you need is to, from top to bottom of your organization, develop a constant curiosity about your members and other audiences and their worlds and operating environments. Just task everyone with becoming a sponge for gathering information. You want to develop that deep interest in learning about what drives my members? Once you’ve got that piece going, everybody’s curious; everybody wants to know what’s driving your members. They’re all collecting information as often and frequently and in as many formats as they can. This gets back to Jamie’s thing about fences between your silos—they need to be really low fences. You want to be transparently and openly sharing that information internally, which means you can’t sit there and hoard data, like, “This is mine, and I’m not sharing it with anybody else because [reasons].” You’ve got to be willing to share data across those low fences and also across your hierarchies. Your frontline staff, customer service people, those who are interacting with your members, your learners, and your other audiences on a day-to-day basis get all kinds of insight that often doesn’t make its way up the chain. You need to create mechanisms for that to happen.

Elizabeth Engel: [00:23:47] The other thing that is useful—both to becoming a learning organization and your larger lean startup practice—is suspending your need for immediate certainty. You basically want to be extending your process, your time period in which you are asking questions, in which you are developing hypotheses, in which you are testing hypotheses. We don’t have to know the answer immediately. We just have to keep asking good questions. Here’s a short example of developing a learning practice. When I worked for the Children’s Hospital Association—which at the time was called NACRI—one of my areas of responsibility was running our corporate partnerships. We were doing all right with corporate partnerships when I came in, certainly making some money, but there was definitely potential there to make them happier and to bring in more money as a result.

Elizabeth Engel: [00:24:39] And so back to Jamie’s example of that person at that startup in Ann Arbor who was tasked with going out into the field—that’s exactly what I did. We had corporate partners all across the country, and, yes, I had to get approval to do this, and there was some investment of money, but the first year or so I was there I visited every single one of our corporate partners in their offices—wherever they were—to talk to them about “What are your goals with our audiences? What are you trying to achieve here? Where are the barriers that you’re finding? What opportunities do you see?” Etc. So curiosity—get out there, talk to them, pick up as much information as you possibly can, and then bring it back and share it, not just with our little team running corporate partnerships but with all of our program areas across the association. “Here’s what these people are looking for and what they are trying to achieve and what they want to do. How does this potentially fit with your program area?” Some program areas didn’t fit at all, but some program areas were like, “Oh, my god, we have a thing over here that we never thought about pitching to a corporate partner that could help them. It would help us.” Everybody benefits.

Celisa Steele: [00:25:56] If there’s an organization that doesn’t feel culturally ready to try out lean startup methodology, or maybe they’ve even toyed with it some and haven’t had a lot of success, what’s a small but meaningful step that that organization can take to try to get more culturally ready for something like lean startup?

Jamie Notter: [00:26:17] The first step is conversations with your people about what your culture is—what it really is, not what you want it to be, not what the ideal culture is, not, for the love of all things holy, your core values. You can do all that stuff, but that’s later. Because that has to come from where you are. So have a conversation. You could take a culture assessment and get real data and talk about it. That’s fine too, but that’s not a simple step. The simple step is getting around the table and saying on the key things (innovation, agility, transparency, collaboration), big topics, big concepts that everyone likes, “How do we do on those? How do we do that?” And ask yourself, “Where are we doing it well, and where are we not doing it well?” Nobody wants to have that conversation about where are we not doing it well in our culture. You just need to have it because it is what it is.

Jamie Notter: [00:27:10] And, if you start to have the conversation that says, “You know what? We love to share information, but we also like to control it,” to Elizabeth’s point a minute ago. “I’d feel so much better if I just have control of this information.” Why do we do that? You can talk about why you do it. It’s like, “Well, where could we let go of a little control?” Then conversation about what your culture is. And then try some stuff that would fix those parts that you think are holding you back. I use this example all the time: “Hey, how about, after our senior team meetings, we share the notes with everybody?” “Oh, no, I don’t know how people would use that. And there’s confidential things that happen.” “Don’t share the confidential stuff then. Just bullet points. Let everyone know.” “Okay, we’ll try it.” And then, when they do, they realize nobody cared. Because you talk about boring stuff in your leadership team meetings. “Okay, that actually makes me a little more relaxed.” These little behaviors start to loosen things up. And it’s an experiment.

Jamie Notter: [00:28:14] And I just Trojan-horsed a little bit of experimentation into your culture by having you experiment with your culture. But it loosens things up a little, and suddenly you’ve got people that are willing to say, “You know what, I don’t know that I can do a full lean startup on this, but I’m going to start changing the way we ask questions about our new product development in our meetings.” And so you can see some changes around the edges right away. Again, the more progress you get with that, then the more bold you’re going to get and say, “You know what? We really need to overhaul this piece of our culture around experimentation. Let’s get a team together and design a new way of doing things.” That’s the big culture-change stuff. You can get your way there through smaller changes that, as long as they keep working, will give you momentum.

Celisa Steele: [00:29:10] You guys include some case studies in the white paper, and I really appreciate that because that helps bring these concepts alive. Elizabeth, when you think about those case studies, what’s something that one of those associations that you highlighted did that listeners might consider doing or trying out in their own organization?

Elizabeth Engel: [00:29:30] I have a quick one from each of them. The National Registry of Emergency Medical Technicians started by creating a shared definition of innovation, which is really important because we tend to talk about it a lot without always making sure that we all mean the same thing. And they started there. The National Council of Architectural Registration Boards, which I already mentioned, figured out how to adapt the methodology to their own culture and way of working. They were the ones who said, “We’ve got to bring in this whole design thinking/empathy piece.” You don’t just go to the store and buy the box of lean startup methodology and open it up and out pops this fully formed practice that you could run with. You have to make it your own. And the American Association of Veterinary State Boards invested time in training their team, including their board of directors, so that everybody understood what was happening. You probably noticed when we first kicked this off, and Celisa asked about what are the key components of the methodology, it’s a little jargon-y. If some of your folks develop facility with that, and some don’t, it’s like you’re not part of the secret society. Well, they made sure that it wasn’t a secret society. Everybody understood and knew what was going on. If you ever see me in person and want to talk about this, for your listeners, ask me about the minimum viable lemonade stand because it’s a fun story.

Celisa Steele: [00:30:53] I love a little Easter egg in a podcast, so people can follow up with that. I really appreciate the fact that you guys put out the white paper, that you’ve made the time to come on the podcast and talk about it. There’s a lot more in the white paper. We will make sure to link to that in the show notes and encourage listeners to go and download that. But, as we’re beginning to wrap up, I would love to know from each of you if there’s one thing that you hope listeners take away from the conversation today. What is that? What would you have be that highlight for them? Jamie, do you want to go first?

Jamie Notter: [00:31:27] I’m just going to repeat the “understanding what your culture is” piece. Start that conversation. Stop being afraid of culture and thinking it’s too big and too hard. Just start having the conversation that says, “We’ve got a culture, and it’s driving behaviors here. What is it, and which behaviors are the ones that are getting in the way?” The sooner you start that conversation, the sooner you get to the other side, where you’ve got a place where everyone loves working there and where you can do lean startup. So I would start with changing your conversation about what your culture is.

Celisa Steele: [00:31:54] Elizabeth, how about you—what takeaway?

Elizabeth Engel: [00:31:56] I would say pick a project that’s completely under your control, experiment with the methodology, and then share the results widely, whether it is persevere, pivot, or kill. When people can see how the methodology works and see it working in their own organizations, they’ll want to try it themselves. If you read the AAVSB case study, that is very much what’s happened there because they’ve made this—back to Jamie’s part of this—part of their culture. It is now the case that anytime anybody comes up with an idea for something, they go to AAVSB’s chief innovation officer, Chrissy Bagby, and they’re like, “Hey, Chrissy, can we run this through the methodology?”

Jamie Notter: [00:32:34] I’m going to add on to that, though, because this is such an important point. We’ve talked about how your existing culture can prevent you from doing lean startup effectively. The converse or inverse—I don’t know what it is, but it’s one of those “verses”—is true. You can change your culture by running this process. This could be a culture play—in my language—where you say, “You know what? We need to be better at experimentation, so I want to run this process, and we’re going to see if it works.” It’s interesting that, if you consciously make it part of culture change…so many people are like, “Oh, well, it’s a culture change thing. Let’s try it out,” whereas you just went to the boss and said, “You need to do lean startup because it’s the best thing ever.” Like, “Oh, no, that’s too hard.” It also can open a window if you frame it as “We’re going to use this as a way to try and change our culture.”

Celisa Steele: [00:33:24] This is the Leading Learning Podcast, so we always like to ask guests who come on about their own learning practices and habits. I would love to hear from each of you about how you continue to grow and improve yourselves. Elizabeth, tell me a little bit about your approaches.

Elizabeth Engel: [00:33:40] That is the point of the whole white paper series. I’ve been doing these annual-ish white papers ever since I launched Spark 13 years ago, and that’s how I pick whatever the topic or focus of that year’s or year-ish’s white paper is going to be. What’s something associations need to be paying more attention to that I want to do a deep dive on and learn more about myself? Pick the topic. Do the research. Find the co-author. Make it so.

Celisa Steele: [00:34:08] Great. Jamie, how do you approach your own learning?

Jamie Notter: [00:34:12] Recently I’ve switched, as part of my deciding within the last year that I wanted to call myself a culture scientist. If I’m a scientist, I need to do research, and so it’s a little bit following Elizabeth’s model. But I now try and identify what my research question is. Once I have a research question, then I need to create a practitioner guide, based on the research, that I put out in the community, and people use it to do things and experiment with things and then report back their learning to me. I’ve done this before in my career, in different formats, but the key is creating a structure, like Elizabeth was talking about. I need a structure where I’m having questions that I want answered, and I need to go out and do it. I also read a book and think that’s interesting. We do this all the time, but, without the structure, it’s too slow, in my opinion. So having a structure of question, investigation, and next steps, I’m finding very, very useful.

Celisa Steele: [00:35:11] I like that both of you prioritize very active hands-on learning in your answers—rolling up your sleeves and doing something with whatever it is you want to learn more about. Do either of you have something else that you are hoping to have a chance to say that you haven’t yet had a chance to say in the conversation?

Jamie Notter: [00:35:29] Both the culture work and the lean startup work are ultimately about speed. And I can’t say enough how much speed is needed in the association world. I’ve used this on some other stuff that Elizabeth and I have done. Quote from Justin Trudeau, former Canadian Prime Minister: “The pace of change has never been as fast as it is today, and it will never again be this slow.” That line is going in one direction. Honestly, with AI and everything else that’s going on, it’s getting steeper. I still hear associations saying, “Well, I’m going to go ahead and develop my five-year strategic plan.” “I’m going to go ahead and wait a while. “The board doesn’t meet until next August, so we’ll make that decision then.” I hear lots of “slow” in associations. It’s really imperative that we move to make these kinds of changes, to do these kinds of processes if we’re going to keep our heads above water. So I just want to add some urgency to it.

Jeff Cobb: [00:36:37] We’re not done quite yet—stick around for our recap.

Celisa Steele: [00:36:40] Download (completely free, no sign-up required) the “Lean at Ten: Culture Eats Methodology for Lunch” white paper, plus visit Jamie Notter’s Web site and newsletter and Elizabeth Engel online at Spark Consulting.

Jeff Cobb: [00:36:57] If you got value from this episode, please share it with a colleague, or leave a rating and a review. Those actions help others find the Leading Learning Podcast and support the work we’re doing.

Celisa Steele: [00:37:08] One thing that stayed with me from the conversation was Elizabeth’s admonition to suspend the need for immediate clarity. Her invitation to linger with the questions and hypotheses rather than rushing to solutions feels both countercultural and exciting to me.

Jeff Cobb: [00:37:25] Speaking of culture, I appreciated Jamie’s comment at the end that there’s an urgency to this work. There are real costs associated with not doing this work.

Celisa Steele: [00:37:35] It’s interesting to think about those two takeaways side by side. There’s a kind of surface-level disagreement—Elizabeth encouraging us to linger, and Jamie urging us to action. But at a deeper level their advice is 100-percent compatible.

Jeff Cobb: [00:37:50] Definitely. Taking action should be predicated on the idea of what’s the right action or, at least, what’s an appropriate action to take, and determining that right or appropriate action usually involves asking good questions and developing and then testing hypotheses.

Celisa Steele: [00:38:08] Thanks again for listening—and see you next time on the Leading Learning Podcast.

To make sure you catch all future episodes, please subscribe on Apple Podcasts, Spotify, or wherever you listen to podcasts. Subscribing also gives us some data on the impact of the podcast.

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Strategy is about making choices—where to focus, what to invest in, and what to stop doing. Data can help bring clarity to those decisions, especially in a complex and competitive environment.

In this episode, Leading Learning Podcast co-hosts Celisa Steele and Jeff Cobb share insights from a survey of learning businesses to help you think about strategy in 2026. They explore top strategic goals and drivers, key trends and challenges shaping learning businesses, and three themes that emerge from the data: the tension between mission and margin, alignment with credibility and areas of authority, and a growing confidence gap around achieving both strategic goals and revenue expectations.

To tune in, listen below. To make sure you catch all future episodes, be sure to subscribe on Apple Podcasts, Spotify, or wherever you listen to podcasts.

Download a PDF transcript of this episode’s audio.

Celisa Steele: [00:00:03] If you want to grow the reach, revenue, and impact of your learning business, you’re in the right place. I’m Celisa Steele.

Jeff Cobb: [00:00:10] I’m Jeff Cobb, and this is the Leading Learning Podcast.

Celisa Steele: [00:00:16] We all know that decision-making is part and parcel of what any organization has to do, and strategy is ultimately about decisions—what to do and what not to do.

Jeff Cobb: [00:00:27] And we believe that data can be helpful when setting strategy and when making decisions. That’s why we’ve annually surveyed learning businesses for the last several years, and it’s why we want to devote this episode of the Leading Learning Podcast, number 469, to sharing data from our most recent survey to help you as you begin 2026.

Celisa Steele: [00:00:49] We think this is a useful set of data to help you have internal discussions and make some decisions about where to focus and invest. So let’s jump in.

Jeff Cobb: [00:00:59] The data we’re sharing is based on responses to an online survey we conducted in September and October of 2025. We received qualifying responses from 156 learning businesses. We also put out a report in December 2025 based on survey responses, so we encourage you to check that out.

Celisa Steele: [00:01:24] The report that you just mentioned, Jeff, draws specifically on the responses we received from association learning businesses. Of the 156 qualifying responses from learning businesses overall, 107 came from associations. Associations were the largest grouping of respondents. Other responses came from commercial training firms, charities, learning businesses embedded in academic institutions, and others.

Jeff Cobb: [00:01:52] Let’s start by looking at the data around strategy. That’s where the survey started, and part of why we started the survey by asking about strategic goals and drivers is because we believe strategy should be driving what you do. We asked two questions about strategic goals. What’s your primary strategic goal for the year ahead? And what’s your secondary strategic goal for the year ahead?

Celisa Steele: [00:02:15] We offered seven predefined choices along with an “I don’t know” and a “something else” answer option, and then folks could fill that in. Respondents could choose one answer.

Jeff Cobb: [00:02:28] For primary strategic goal, what was most selected by a pretty good margin was increasing revenue—29.5 percent.

Celisa Steele: [00:02:38] The second most popular response was strengthening alignment with workforce needs—21.8 percent of respondents selected that as their top strategic goal. That was about eight points lower than increasing revenue.

Jeff Cobb: [00:02:53] The next top responses were enhancing learner engagement. That just barely beat out growing enrollments and registrations, both at around 17 percent. Those were the top primary strategic goals that folks picked.

Celisa Steele: [00:03:09] All of the other options—we had seven predefined options—were selected by under 10 percent of respondents. And the four we just mentioned—increasing revenue, strengthening alignment with workforce needs, enhancing learner engagement, and growing enrollments—sum up the primary strategic goal for the majority of learning businesses responding to the survey.

Jeff Cobb: [00:03:35] We also asked about secondary strategic goal. Same answer options as for the primary goal, and 22.6 percent selected increasing revenue as a secondary goal. When you put together those who chose increasing revenue as a secondary goal with those who chose it as the primary one, you get a majority of respondents saying revenue is a top strategic goal.

Celisa Steele: [00:03:59] Yes, that’s a clear takeaway from the data. Increasing revenue is front and center for learning businesses in 2026. Now, after asking about those primary and secondary strategic goals, we also asked about strategic drivers to get at what’s behind those goals and why learning businesses are focusing on those goals.

Jeff Cobb: [00:04:22] For this question, respondents could pick all that apply from a list of eight named options plus a “something else” option. The top choice was a need to increase financial sustainability or profitability—63.6 percent chose that as a strategic driver. That pairs nicely and appropriately with the top goal of increasing revenue.

Celisa Steele: [00:04:46] The second most selected driver, chosen by 57.1 percent of respondents, was to be seen as setting the pace in the respondent’s field or industry.

Jeff Cobb: [00:04:59] I was a little surprised last year to see this driver rank as highly as it did then, and it’s high again this year. I think this is because of the competitive pressures that organizations feel. It’s hard to stand out in the market for continuing education and professional development. If you’re not seen as somebody who’s setting the pace in your field or industry, it’s going to be hard to attract and convert those learners that are going to contribute to your financial sustainability and profitability.

Celisa Steele: [00:05:32] With your read of that setting-the-pace answer, then we can think about those top two strategic drivers as being existential questions. Can we bring in enough money to keep the lights on and to do what we need to do? And, if we’re not seen as setting the pace in our field or industry, how long can we remain relevant and continue to exist?

Jeff Cobb: [00:05:54] Indeed. This is particularly applicable to our association listeners. As an association, you want to be seen as that leader in your field or industry. It’s a brand thing. It’s not just related to education; it’s related to membership. Are people going to come and even join if you’re not seen as setting the pace?

Celisa Steele: [00:06:16] The third most popular strategic driver was support workforce development—56.5 percent of respondents chose that. Here again we see neat alignment with the strategic goals. The second most popular primary strategic goal choice was strengthening alignment with workforce needs.

Jeff Cobb: [00:06:37] This really was heartening for me. I feel like we’re finally starting to see a lot more visible focus on workforce development and tightly aligning educational offerings and credentialing with employer needs. Even if you’re selling primarily to individual customers or individual members, it’s often the employers who foot the bill for participation in education. So, if they don’t see the value in what you’re doing, it’s unlikely that you’re going to be selling to that individual. And, of course, we’re seeing more focus now on business-to-business (B2B) selling and going directly to the employer and saying, “Hey, use us.”

Celisa Steele: [00:07:14] Jeff, you’ve made the point before that the employer often still has to support the individual learner even if the learner is the one paying and footing that bill, not the employer. The learner may have to take time off work to be able to go to a conference, attend a seminar, or complete that online course. So, if an employer isn’t supportive or makes it hard to do that, then it makes it hard to sell even in that direct-to-consumer (B2C) situation.

Jeff Cobb: [00:07:43] The fourth most cited strategic driver is evolving learner demands—51.9 percent selected that. We were just talking about the importance of speaking to employers and their needs. This driver is about the learners’ needs.

Celisa Steele: [00:08:00] Individual learners now have many more choices than they did a decade ago, even half a decade ago. And they also tend to have a greater need for flexibility in terms of scheduling or in terms of formats. The pandemic got them used to doing things online. This strategic driver of evolving learner demand speaks to all of that.

Jeff Cobb: [00:08:24] “Learner demand” is kind of a catch-all bucket. It’s the kind of thing that we often get called in for because organizations are struggling. They have this sense that demands are evolving, but what does that really mean? What do they need to offer? Do learners want microlearning? Do they want microcredentials? Do they want cohort-based learning? You’ve got to figure that out and be able to evolve as a learning business with those evolving learner demands.

Celisa Steele: [00:08:54] After asking about strategic goals for 2026 and then the drivers behind those goals, we asked about eight trends and issues, how important those are for learning businesses in 2026, and how they’re informing their strategy. We used a five-point scale. For respondents who said that something was “critical,” we assigned that five points; “very important,” four points; down to “not important,” one point. That allowed us to get a weighted average. Here are the eight trends and issues: (1) artificial intelligence; (2) workforce and employer needs; (3) learner preferences for flexibility; (4) personalized learning; (5) increased competition; (6) growth in alternative credentialing, microcredentials, and digital badges; (7) virtual and/or hybrid events (things that are entirely or partially online); and (8) diversity, equity, inclusion, and accessibility (DEIA).

Jeff Cobb: [00:09:59] Out of that list, number one was workforce and employer needs—3.77 weighted average in the responses. Learner preferences for flexibility had a 3.66 weighted average, and then providing more personalized learning experiences had a 3.58 weighted average. To me, those both go a long way towards the whole learner engagement issue. How are you going to be able to create content in a way that engages with learners and meets those evolving demands that we were just talking about?

Celisa Steele: [00:10:37] We asked about the same set of trends and issues in the survey that we did about a year before this one, and these are the same top three as the previous year. So these seem to be at the crux of what learning businesses are focusing on. Now, when I ran through that list of eight, you might remember that at the top was artificial intelligence, but AI is not on that list of top trends and issues that we just touched on.

Jeff Cobb: [00:11:04] No, it did not make the top three, though we are seeing in general that the AI dial has moved in some areas. Still, in my opinion, we’re lagging on how well we’re engaging with and using AI. Around 40 percent of respondents say that they’re having internal discussions about AI, but they don’t have a clear implementation plan. Another roughly 10 percent say they’re not even discussing AI currently. That’s half of the overall responding audience essentially doing nothing with AI at this point—or nothing substantive other than talking about it.

Celisa Steele: [00:11:42] We did see almost 20 percent of respondents say that they are in early stages of AI implementation, things like pilots. That’s significant—a fifth of respondents doing something. And then 16.7 percent say they’re using AI in some offerings, and 6.9 percent say they’re using it in most or all offerings. Both of those are up compared to last year.

Jeff Cobb: [00:12:07] Yes, up a good bit percentagewise. That’s encouraging. Somewhat. But clearly there’s room for a lot more engagement with AI at this point.

Celisa Steele: [00:12:18] We also asked about challenges around maintaining or growing enrollments and registrations. We heard very clearly that revenue is an issue and focus. If you’re a learning business, the way you’re going to grow or maintain revenue is through enrollments and registrations. So what are the things holding learning businesses back or the things that they’re worried about holding them back? Again we provided some predefined choices—eight of them—and then also a “none of these/something else” answer option. In this case, respondents could pick up to three options. We’ll touch on the top four challenges to maintaining or growing enrollments and registrations. All four of these were selected by over a third of the respondents.

Jeff Cobb: [00:13:03] I’ll put these into two buckets. One is a capacity/structural bucket, and the other is a market bucket. Going in that capacity bucket, the top challenge identified was insufficient internal resources (staff or budget)—45.3 percent said that. The other challenge in that capacity bucket, which may be a subset of the first one, is limited marketing resources—39.3 percent said that.

Celisa Steele: [00:13:34] The other two challenges go in your market bucket, Jeff. Pricing challenges were also cited by 39.3 percent—the same number who cited limited marketing resources. This gets to that difficult question of how do you price yourself out there in a very competitive market? That’s clearly a question on respondents’ minds.

Jeff Cobb: [00:13:56] And then the fourth challenge, also going in that market bucket, points to the very competitive market situation. Increased competition was the fourth challenge—35.3 percent of respondents indicated that. Existing in a competitive market, not quite knowing how to price, and with limited marketing resources and insufficient internal resources summarizes the challenges that organizations are seeing.

Celisa Steele: [00:14:23] We also asked a forward-looking question about where learning businesses plan to invest in 2026. Again we gave some predefined choices (ten), and folks could pick up to three. We’ll share the top four areas of planned investment.

Jeff Cobb: [00:14:40] Number one was increasing learner engagement—41.1 percent said this. That dovetails well with the earlier focus on evolving learner demands.

Celisa Steele: [00:14:51] The second most popular area of planned investment is enhancing marketing and outreach efforts—35.2 percent said they’ll be investing there. We were just talking about limited marketing resources as a challenge, so this clearly responds to that. But I do think it’s worth noting that the marketing and outreach efforts option last year was a much more popular choice. This year, about 35 percent, as I just said; last year, almost 59 percent. Maybe we could do a little armchair analysis on what might be behind that drop.

Jeff Cobb: [00:15:25] Yes, but it’s hard to say. It could be a glitch because these are non-statistical surveys. It could be because people spent marketing money last year, didn’t get the results they wanted, and so aren’t putting as much into it this year. Or maybe they’re not being given the budget to invest in it in 2026. But marketing and outreach may be tied in some ways to the next area of investment, which is increasing efforts to partner with other organizations—31.7 percent indicated that. The survey didn’t ask about what underlies that partnering or why they’re looking to partner, but I suspect that many organizations are partnering because they want to expand their reach and get to new customers that may be represented by the partner’s audience. Respondents may be looking to partnering as a way to expand reach rather than direct investment in what would typically be thought of as marketing and outreach efforts.

Celisa Steele: [00:16:27] The same number of respondents who chose partnering chose providing personalized learning experiences as a top area of investment—31.7 percent. This again speaks to the fact that learners have more and more options, and their needs and preferences are evolving. Their expectations for flexibility are changing. And that’s what personalized learning is all about—making sure that the learner is getting the right content in the right format at the right time.

Jeff Cobb: [00:16:57] Let’s turn to the first of three themes and takeaways from the data and our analysis of it. One of the themes has to do with mission and margin. This emerged out of interviews we did with 27 association CEOs about the role of learning and education.

Celisa Steele: [00:17:16] There’s often a tension—and sometimes actual confusion—about the role of education and learning in mission and margin when it comes to the products and services in the portfolio. This is particularly applicable for association learning businesses, but there are other learning businesses that are also mission-driven. If you’re a mission-driven organization of any type, then you’re going to have two dimensions along which you can assess products in your portfolio. One of those dimensions is the contribution to mission. How well does that product support what you’re trying to do and why you exist?

Jeff Cobb: [00:17:55] The other dimension is sustainable net revenue. Is that product profitable? Is it able to bring in a net margin consistently? This mission-margin question is an essential tension that often doesn’t get made as explicit as it needs to be when organizations are thinking about product decisions, how they’re going to invest, and what the challenges are. If you have products that aren’t generating much revenue and also aren’t contributing to your mission in a measurable way, then you really need those out of your portfolio. I know there are people listening that, if they’re honest with themselves, have those in their portfolios and know that they need to be gotten rid of.

Celisa Steele: [00:18:39] We encourage you to access the “Where Mission and Margin Meet” executive briefing that has a visual of this matrix that maps out these two dimensions that we’re talking about here. It’s a very simple tool, but it can help you plot where different products or product lines in your portfolio fit. Jeff, what you were just talking about there is the lower left quadrant, things that need to be retired or redesigned. That’s where the product has weak connection to mission and also weak revenue associated with it.

Jeff Cobb: [00:19:13] But organizations probably also have some things in their portfolio that are solidly about mission but aren’t generating much revenue. Can you look at those and figure out how you might get them to generate a little bit more revenue if you apply some disciplined thinking? Possibly you’re in the position of having some things, on the other hand, that are generating quite a lot of revenue for you but don’t have that much to do with your mission. With those, you might want to ask if can we spin them off and get some cash that you can invest back into the products that are more aligned with mission?

Celisa Steele: [00:19:54] Of course, there are sweet-spot offerings—products that deliver on mission and generate strong net positive revenue.

Jeff Cobb: [00:20:03] Most organizations are lucky if they’ve got, say, 20 percent of their portfolio in the upper right of the matrix, where that sweet spot is. Can you find more of those products? And, to the extent that you’ve got them, can you strengthen your investment in them and get more out of them?

Celisa Steele: [00:20:23] One way to potentially find more products that will fit in that upper right sweet spot—if you’re mapping your offerings out on this matrix—is by making sure that you’re using what we call your Credibility CapitalTM.

Jeff Cobb: [00:20:39] We talked earlier about organizations wanting to be seen as setting the pace or leading their market. A lot of what makes that possible is having a high level of credibility in your market—being seen as the authoritative source, a trusted source. That’s typically tied to specific assets that you have as an organization. I’m thinking particularly of associations, but this can apply to any type of learning business that has intellectual property, which most do, or other types of capital—things like standards and guidelines that you’ve created, credentials you’ve created that have market value to them, accreditations potentially for the businesses and other organizations that are in your sphere, specialized research you produce, market data that you’re known as the source for, even your ability to convene the right people around the issues and challenges and opportunities in your marketplace, being recognized as the advocate for the challenges and issues and opportunities in your marketplace. All of these are potentially parts of your Credibility Capital.

Celisa Steele: [00:21:48] We asked in the survey how closely respondents feel their portfolio of offerings is aligned with their areas of authority, AKA that Credibility Capital that you were just talking about, Jeff. 30.9 percent of respondents said that they feel their portfolio is fully aligned with their areas of authority, and 49.3 percent said they were mostly aligned. That may sound pretty good at first blush. But we think that fully aligned group needs to be bigger.

Jeff Cobb: [00:22:20] Yes, and also there could be a little bit of the curse of knowledge going on here. There’s the potential for respondents to be overrating their alignment from their perspective of inside the organization. The person responding is thinking, “Yes, of course we’re supporting our standards and our credentials and everything else.” But that’s from their perspective. From the market’s perspective, that alignment and the strength of that alignment may be much less clear.

Celisa Steele: [00:22:47] As we talked about in our last episode around “Associations as Architects of Learning,” this is another example of a not-bleeding-at-the-neck issue. A lot of education businesses are running along fine but maybe not great. Same thing here. You’re mostly aligned but not fully aligned. Mostly aligned can be a very dangerous place to be because it can almost feel like justification to keep doing the same things. This is the “If it’s not broken, don’t fix it” mindset. But, if you were more fully aligned, what might that mean in terms of revenue and in terms of contribution to your mission? This is a place where you want to be thinking about coherence and discipline. Once you know what you’re supposed to do, be ruthless about doing it and not doing other things. To go back to the matrix, if you want to be in that upper right quadrant with those sweet-spot offerings, what does that mean? It probably means you need to get rid of some things that should have been sunset long ago, and you just haven’t gotten around to. When you’ve got lean teams, when you’ve got tight resources, when you have a highly competitive market, the way you’re going to be able to do what you need to do to have those sweet-spot offerings is by being disciplined, focused, and fully aligned.

Jeff Cobb: [00:24:12] The final takeaway we’ll share has to do with confidence and, in particular, a confidence gap that we feel we’re seeing. We asked respondents about this in a couple of areas, starting with confidence in achieving their top strategic goals.

Celisa Steele: [00:24:29] Less than a quarter said that they were very confident or extremely confident in achieving their strategic goals. Jeff, you and I are the kind of people who think that strategy is the basis of everything. We believe you need a clear strategy, and you need a clear plan of execution to achieve that strategy. So, if one of those two is missing or weak, you don’t have confidence in achieving your strategic goals.

Jeff Cobb: [00:24:55] Which is not the place you want to be in. It’s definitely a place to apply some discipline, as you said, Celisa, and make sure that you do have strategic clarity, that you’ve considered your tradeoffs, that you’re focused on what really is important, and that you’re confident around your execution on it.

Celisa Steele: [00:25:14] We also asked survey respondents about confidence in meeting revenue expectations in 2026, specifically revenue expectations for education and learning products. Remember, the top primary strategic goal was increasing revenue, so how confident are you in achieving what is for many of these learning businesses their top strategic priority? And again we have under a quarter who are extremely or very confident. In both cases, we have tiny slices who are extremely confident. So our suggestion is to do what it takes to increase your confidence, to close that confidence gap.

Jeff Cobb: [00:25:54] This may not be representative of you and your learning business, but it is a good thought experiment. Think about how confident you are in achieving your strategic goals and in meeting revenue expectations. And, if you and your team aren’t very confident, then why? What can you change? What can you perhaps invest in? What can you stop doing? Find those tradeoffs that you need to make. What is it that you need to do to grow your confidence, to close that confidence gap? These are connected very tightly. You’re not likely to have confidence in meeting your revenue expectations if you don’t have confidence that you actually have a strong strategy in place that you’re capable of executing against well. If you’ve got that in place, then it should follow from that that you’re going to be in a good place to meet your revenue expectations. There are going to be wrinkles, of course. Every strategy, once it hits the market, is subject to change. But, if you’ve had some rigor, if you’ve had some discipline in looking at the data, understanding your market and your situation, making those tradeoffs, and developing the strategy, it should follow that you’ll be confident in meeting the revenue expectations that go with that strategy.

Celisa Steele: [00:27:12] We encourage you to check out the report The Strategic Outlook for Association Learning Businesses 2026, which we did based on the association-focused slice of data from this survey.

Jeff Cobb: [00:27:30] If you access the report, look at this data, find it useful, we’ll ask you to put a little note on your calendar for around next September or so when you see this survey come out again because the reason we’re able to do this is because people generously give their time to participate in the survey. It takes between 10 and 15 minutes, and it yields data that’s really useful to learning businesses—that’s our audience. For those of you, if you’re listening and you did participate in the survey that’s behind this report, we’re truly grateful for that. Thank you. And, if you didn’t get the chance to participate in 2025, again, we hope you’ll make that note to participate in 2026 when it comes back around.

Celisa Steele: [00:28:22] Be sure to check out the two publications we mentioned in this episode: the executive briefing based on interviews with association CEOs and The Strategic Outlook for Association Learning Businesses 2026. You’ll also find show notes, a transcript, and options for subscribing to the podcast.

Jeff Cobb: [00:28:46] If you enjoy the Leading Learning Podcast, please share this episode or another with a colleague or co-worker you feel would appreciate and get value from it. And please spread the word about the executive briefing and report too.

Celisa Steele: [00:28:59] Thanks again—and see you next time on the Leading Learning Podcast.

To make sure you catch all future episodes, please subscribe on Apple Podcasts, Spotify, or wherever you listen to podcasts. Subscribing also gives us some data on the impact of the podcast.

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The post The Strategic Outlook for Learning Businesses 2026 appeared first on Leading Learning.

Mindset shapes how adults approach learning, challenge, and change—and it has important implications for learning businesses. In this episode of the Leading Learning Podcast, number 468, co-hosts Celisa Steele and Jeff Cobb explore Mindset, the influential book by psychologist Carol Dweck, and the broader concept of mindset.

They unpack the distinction between fixed and growth mindsets; examine how mindset affects learners, leaders, and organizations; and discuss practical ways learning businesses can foster conditions that support resilience, effort, and meaningful learning.

To tune in, listen below. To make sure you catch all future episodes, be sure to subscribe on Apple Podcasts, Spotify, or wherever you listen to podcasts.

Download a PDF transcript of this episode’s audio.

Celisa Steele: [00:00:03] If you want to grow the reach, revenue, and impact of your learning business, you’re in the right place. I’m Celisa Steele.

Jeff Cobb: [00:00:10] I’m Jeff Cobb, and this is the Leading Learning Podcast.

Celisa Steele: [00:00:17] Both the concept of mindset and Carol Dweck’s book titled Mindset continue to influence how we think about learning, leadership, and performance. This episode, number 468, is an encore airing of an episode from our archives in which Jeff and I dig into the distinction between fixed and growth mindsets, explore how those mindsets shape the ways adults approach challenge and change, and connect Dweck’s research directly to the work of learning businesses.

Jeff Cobb: [00:00:45] Originally released in May 2019, we think the conversation remains highly relevant as organizations deal with uncertainty, look to cultivate innovation, and work to foster the development of resilient, adaptive learners. We hope you enjoy this revisit to mindset—capital M and lowercase m.

Celisa Steele: [00:01:09] Jeff, here’s a statement for you to consider: You can learn new things, but you can’t really change how intelligent you are. Would you say you mostly agree or disagree with that statement?

Jeff Cobb: [00:01:21] I would have to mostly disagree with that statement. There are probably limits, but I also think that intelligence is much more malleable than we tend to appreciate or acknowledge—or maybe I’m just being hopeful about my own intelligence.

Celisa Steele: [00:01:37] Here’s another statement: No matter what kind of person you are, you can always change substantially. Mostly agree or mostly disagree?

Jeff Cobb: [00:01:46] Now that one I emphatically agree with. You can definitely change the kind of person you are substantially, primarily through learning.

Celisa Steele: [00:01:55] Jeff, as you know, those statements appear in the book Mindset, published by Dr. Carol Dweck in 2007. And we’re going to devote this episode to talking about mindset with a capital M (the book) and mindset little m (the idea).

Jeff Cobb: [00:02:13] That’s right. We thought, why not go with a question-and-answer format for the episode?

Celisa Steele: [00:02:18] Why not indeed?

Jeff Cobb: [00:02:20] The first question is simply what is mindset?

Celisa Steele: [00:02:25] Dweck’s research and work have become well known in the dozen years since Mindset came out, so I’m guessing many listeners are familiar with the term mindset. And, even if it happens to be a new term, it’s pretty self-explanatory. Mindset is the frame of mind, the perspective that we bring to anything we do or experience in life—whether that’s something on the job, at home, something professionally, socially, intellectually.

Jeff Cobb: [00:02:54] Listeners might also know that Dweck says there are two mindsets: the fixed mindset and the growth mindset. If you have a fixed mindset, you believe your qualities are carved in stone. A growth mindset, on the other hand, is founded on the belief that your basic qualities are things you can cultivate through your efforts.

Celisa Steele: [00:03:13] In other words, the growth mindset believes intelligence can be developed, and the fixed mindset believes intelligence is static. To talk a bit about how those mindsets play out, let’s circle back to those statements that I asked about at the very beginning of the episode, Jeff. Dweck uses those statements as a way for individuals to self-assess their own mindset. That first statement, “You can learn new things, but you can’t really change how intelligent you are,” conforms to a fixed mindset.

Jeff Cobb: [00:03:42] And the other statement, “No matter what kind of person you are, you can always change substantially,” reflects a growth mindset. Now that we’ve covered what mindset is, let’s move on to question number two. How does mindset relate to learning?

Celisa Steele: [00:04:00] Growth mindset ties directly to learning. Dweck herself writes, “The belief that cherished qualities can be developed creates a passion for learning.” That is, if you believe you can change and always change substantially—and that your own efforts make that change possible—you’re going to embrace the potential of learning. So it seems that those of us who work in learning businesses should, by default, embrace the growth mindset. And yet…

Jeff Cobb: [00:04:29] And yet that doesn’t always happen. It’s important to recognize that we bring different mindsets to different circumstances. Something I wrote about in 10 Ways to Be a Better Learner and that I continually see in myself and in others is that we may have a growth mindset in many areas of our lives—maybe even most areas—and yet be stymied by a fixed mindset in others.

Celisa Steele: [00:04:51] I see that in myself and in others as well. And Dweck makes the point that, as individuals, we’re usually not entirely of the fixed mindset or entirely of the growth mindset. I might have a growth mindset about my ability in a sport. I might think I can practice tennis, and I can get better. But I might have a fixed mindset about my ability with music. I might tell myself, “There’s no way I can learn to play the violin at this point in my life.”

Jeff Cobb: [00:05:18] I think you can. Because one key to becoming a better learner is to ferret out those fixed mindset areas and, where appropriate, replace them with a growth mindset. It’s common for both learning business professionals and learning businesses to feel, for example, that they have a growth mindset as relates to creating effective education. That’s something they feel confident about—they can always improve there and do a good job at it. But then they feel that they have no abilities and no real capacity for growth when it comes to something like marketing, which is so essential for success as a learning business.

Celisa Steele: [00:05:54] Yes, and there’s another variation of this kind of mixed mindset—we may have a fixed mindset about our own ability in some area but have a growth mindset for others in that area. Again, to use that violin example, I might think it’s too late for me to take up the violin, but I might believe that my kids can learn any musical instrument they want as long as they put in the time and effort.

Jeff Cobb: [00:06:18] Those of us working in learning businesses may judge our own abilities differently than those of the learners and customers that we serve. We might embrace, for example, the almost limitless possibilities of learning—that growth mindset—but then think that our learners are just never going to get it. They’re not going to understand that concept and embrace that growth mindset. Vice versa—the learners can do anything if they’ll engage with those learning experiences we’re creating for them, but then, at the same time, we’re thinking it’s impossible to ramp up our learning business in new areas and to achieve the growth we’d like to with our learning business.

Celisa Steele: [00:06:54] As we’re beginning to tease out here, mindset applies to (A) us as individuals (to ourselves), (B) to the learners that we serve, and (C) to our learning businesses as entities. We want to talk about each of those groups (A, B, and C), and so our next three questions are going to address each.

Jeff Cobb: [00:07:17] How does mindset impact us personally?

Celisa Steele: [00:07:20] We’ve begun to address that mindset has huge ramifications because it’s the backdrop for everything that we do. It’s the backdrop for how we engage with others, for how we learn, for what we choose to learn.

Jeff Cobb: [00:07:35] It’s worth adding that the growth mindset does come with a kind of perseverance. Dweck writes, “The passion for stretching yourself and sticking to it, even, or especially, when it’s not going well, is the hallmark of the growth mindset.”

Celisa Steele: [00:07:51] I think that’s critical. The two mindsets see challenge, risk, and effort very differently. The growth mindset embraces challenge and effort and sees failure as an opportunity to learn and to improve. The fixed mindset, on the other hand, sees challenge and effort as dangerous. If intelligence, social skills, or whatever ability is fixed, then working hard for something is a sign of inferiority. The logic of the fixed mindset is, if you’re good at it, it should come naturally, effortlessly, immediately.

Jeff Cobb: [00:08:26] Yes, the fixed mindset sees failure as forever. If you have a fixed mindset and you fail at something, then you’re bad at that thing. It doesn’t offer a whole lot of opportunities for recovering versus a much more generous viewpoint from the growth mindset that, if you fail, you just did that thing badly that one time. Of course, you’re going to be able to bounce back. This view of setbacks is so important because we know that challenge and effort are important aspects of learning. They’re fundamental to it. Think of the concept of effortful retrieval, for example.

Celisa Steele: [00:09:03] Yes. And effortful retrieval makes me think of the book Make It Stick: The Science of Successful Learning.

Jeff Cobb: [00:09:10] Yes, those authors mentioned Dweck more than once (dozens of times) throughout the book because they recognize how important mindset is to successful learning. In fact, we’ll be sure to link to an episode we did with Peter C. Brown, who was one of the co-authors of Make It Stick. Definitely go check that out. But, in the meantime, let’s move on to the fourth question, which is how does mindset impact the learners you serve?

Celisa Steele: [00:09:37] First and foremost, mindset impacts the learners we serve in the same way that it impacts us. That means mindset determines the attitude that learners bring to a learning experience. And the learner’s mindset plays a huge part in how effective any learning experience can be.

Jeff Cobb: [00:09:57] It’s important to recognize that mindset is not going to be even across groups of learners we serve. Some learners will come with a growth mindset, but others are going to show up with a fixed mindset. This adds a dimension to the concept of prior knowledge that Malcolm Knowles pointed out so many years ago. Not only do learners come to our offerings with different levels of expertise and experience on the subject matter—that differing prior knowledge—but they also bring those different mindsets.

Celisa Steele: [00:10:30] Which adds another layer to teaching and makes it extra tricky. But the good news is that people can be put into a growth mindset, and doing that—putting your learners in the growth mindset—strikes me and probably you too, Jeff, as a potentially powerful tool for learning businesses. So let’s talk a little bit about how we might put learners in a growth mindset.

Jeff Cobb: [00:10:54] Definitely. Here are some pretty simple ideas. One is to tell learners, just say it to them, that whatever they’re about to study can be learned. Emphasize that. And then also emphasize that the learning experience you’re offering is going to give them the chance to learn it.

Celisa Steele: [00:11:12] A related approach, going slightly deeper, is to give the learners an article. Dweck ran tests where she gave research subjects a scientific article that describes people who didn’t have natural ability but developed exceptional skills. Just reading that article was enough to put her research subjects into a growth mindset for at least a period of time. We can do something like that—give them an article to read. We can also put learners in the growth mindset through the messages that we send, like setting rules and norms that often happen at the beginning of an instructor-led or facilitated experience. You might have the instructor or facilitator stress that effort and contribution are what they’re looking for from the learners and that they value effort and contribution above the learner being right or doing something quickly.

Jeff Cobb: [00:12:07] Yes, that kind of upfront work reminds me of Robert Cialdini and what he and I talked about in terms of pre-suasion in the learning context. We had an episode with Bob a while back. We’ll be sure to link to that. But we discussed that just putting a question like “Do you consider yourself a committed learner?” on a slide before the start of a conference session, so it’s up in the room where people can see it as they’re coming into the session, just doing that can pre-suade those people in the room to think of themselves as lifelong learners and better prime them for the learning experience that they’re about to engage in, make them more receptive to it. You could further refine that slide to put those people in the room into a real growth mindset by basically borrowing Dweck’s question and putting something up there like, “Do you believe, no matter what kind of person you are, that you can always change substantially?” You might want to put in parentheses “Yes!” or something like that to further prime them. But, in any case, it’s a simple approach to getting people into that growth mindset in a learning experience.

Celisa Steele: [00:13:20] Those are great ways to prime and pre-suade. And then you have to make sure that you keep that growth mindset front and center as you head into the learning experience. One aspect of that is feedback, which is such a tricky area or can be a tricky area. One thing you need to do is make sure that, in the feedback, you stress and praise learners’ effort and the process that they go through to do something versus judging the learners’ talent or intelligence. You have to be careful about how you give that feedback and what you’re stressing in the feedback. Now, I mentioned facilitators and instructors when I was giving an example earlier, but I want to note that these approaches could apply to asynchronous online courses too. You don’t have to have a human delivering this growth mindset. Jeff, the example you gave of a slide, there’s no human involved there. That’s just up there. It could be easily having text and audio in an e-learning course, as long as what it’s conveying is that growth mindset.

Jeff Cobb: [00:14:28] A word of caution here. Just as we can put people in a growth mindset, we can also put them in a fixed mindset. So we do have to be careful. We need to make sure that those who are designing and delivering learning experiences know about the mindsets and understand what triggers them—something that you want to discuss particularly with your subject matter experts if you’re using volunteer SMEs, for example, to deliver sessions. Make sure they understand this concept, and make sure they understand—they need to know—that labels can trigger the fixed mindset. Even positive labels can do this. Calling someone smart equates that person with their achievement or performance. To prompt a growth mindset, you want to label it a little bit differently. You want to praise effort or way of thinking, saying, “That was a smart way to think about that problem.” That’s very different from simply saying, “You’re smart.”

Celisa Steele: [00:15:25] On the label front, you said even positive labels can do negative work. Sometimes labels that seem innocuous or seem fact-based, Dweck points out that those can have a negative effect. She cites research that shows that just checking a box to indicate race or sex can trigger a stereotype in the learner’s mind and lower test scores. It’s important to think about whenever you’re asking someone to identify themselves, to label themselves, whenever you’re labeling them, that can have an impact on the learner—keep that in mind, and be sensitive to it. A lot of this can feed into bias. Jeff, you got to talk with Howard and Shilpa about bias, so we should link to that episode in the show notes as well.

Jeff Cobb: [00:16:14] Howard Ross may cite the same research in his book Everyday Bias. Howard Ross and Shilpa Alimchandani—we had a great episode. It’s still one of the most popular ranking episodes. It’s been one of the most shared. Very powerful episode and connects into mindset in so many different ways.

Celisa Steele: [00:16:37] With that, we come to our penultimate question. How does mindset impact our learning businesses?

Jeff Cobb: [00:16:43] There is a very important way that mindset connects into learning businesses, connects into our Learning Business Maturity Model, because it directly impacts one of the domains in that model: capacity. How we perceive the capacity of our learning business and how we cultivate that capacity as leaders also connect into the leadership domain of the Learning Business Maturity Model because, as leaders, we have the ability to influence the mindset of those who follow us, so it’s going to influence capacity, and it’s going to influence our ability to cultivate capacity. It’s really, really critical.

Celisa Steele: [00:17:25] That point you made about impacting leadership—Dweck herself dedicates a chapter to “Business: Mindset and Leadership.” And probably no big surprise to listeners, Dweck finds that good leaders have a growth mindset usually and that the fixed mindset tends to be toxic. This is where you have those companies with the big-ego CEOs that tend to shut down feedback, ideas, and innovation from those who serve under them.

Jeff Cobb: [00:17:52] Yes. We’ve done episodes on the Learning Business Maturity Model before and talked about these domains, capacity and leadership. We’ll be sure to link to those. But another danger of a fixed mindset in an organization is that it tends to encourage groupthink—that, of course, deprives the organization of the diversity of opinions and views that often yields insight into the market and also the ability to solve the problems or come up with the innovations that are going to take your learning business forward.

Celisa Steele: [00:18:31] You can self-assess at the organizational level. Just as we opened today’s episode with a couple of questions that help you gauge your own mindset, you can ask questions about your organization to get a feeling for the overall mindset there. You might ask, “How do you act towards others in your workplace? Do you believe that they can change? How do others act towards you? Do they believe that you can change?”

Jeff Cobb: [00:18:57] It’s incredibly important. So many times we come across organizations where there is a pervasive fixed mindset in many ways. There’s not the belief in the organization that they can achieve what they want to achieve as an organization. We may need to do a whole episode on this at some point, but it’s an issue of low organizational self-esteem because they’re stuck in that fixed mindset when they need to be tapping the growth mindset. Incredibly important. But, for now, let’s turn to our final question. What takeaways do we want to emphasize? And that might be a cheat question, but it’s one that allows us to start wrapping up.

Celisa Steele: [00:19:39] I’ll emphasize that the growth mindset doesn’t equal learning, and, by the same token, a fixed mindset doesn’t mean no learning. But a growth mindset does increase the odds that learning will happen, and a growth mindset increases the odds that that learning will stick.

Jeff Cobb: [00:20:00] And I’ll emphasize that mindset impacts multiple levels of what we do, how we act as learning businesses. Embracing a growth mindset is good for our learners, obviously, so they’re going to get the impact out of the learning experience. It’s good for our learning businesses. We talked about that concept of capacity and impacting the capacity of the business. And then, for us as learning business professionals and especially in our work as leaders of learning, mindset is just so important.

Jeff Cobb: [00:20:36] That wraps up this encore airing of our episode on mindset.

Jeff Cobb: [00:20:47] If you enjoy the Leading Learning Podcast, please share this episode or another with a colleague or co-worker you feel would appreciate and get value from it.

Celisa Steele: [00:20:55] Thanks again—and see you next time on the Leading Learning Podcast.

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Content is everywhere, governance is slow to change, and technology expectations keep climbing—association learning businesses are feeling squeezed. Most are still operating like catalog providers in a market that now needs architects.

In this episode of the Leading Learning Podcast, co-hosts Celisa Steele and Jeff Cobb share a Rumelt-style diagnosis based on conversations with 27 association CEOs. They unpack the issues hollowing out the old education model—and what learning leaders can do to design trustworthy, employer-aligned, tech-enabled learning pathways for the future.

If you want clarity on the current landscape and what it means for where your learning business needs to go next, tune in.

To tune in, listen below. To make sure you catch all future episodes, be sure to subscribe on Apple Podcasts, Spotify, or wherever you listen to podcasts.

Download a PDF transcript of this episode’s audio.

Celisa Steele: [00:00:03] If you want to grow the reach, revenue, and impact of your learning business, you’re in the right place. I’m Celisa Steele.

Jeff Cobb: [00:00:10] I’m Jeff Cobb, and this is the Leading Learning Podcast.

Celisa Steele: [00:00:17] If you lead or work in a learning business, you already know the ground is shifting under your feet—slowly in some places and breathtakingly fast in others. The familiar offerings—conferences, catalogs of courses, CE tied to licensure—still work. Sort of. But that model is hollowing out.

Jeff Cobb: [00:00:37] This year we spoke with 27 association CEOs about the role education and learning play in their mission, their economics, and their future. One thing we heard remarkably consistently is that the old model isn’t broken enough to force change, but it’s definitely not strong enough to power the future.

Celisa Steele: [00:00:56] We have an executive briefing called “Where Mission and Margin Meet” that combines what we learned from those CEO conversations with some of our own observations. In this episode, we’re going to share a Rumelt-style diagnosis of the core problems many associations face in their learning businesses: the shift toward employer-driven demand, the explosion of supply, the drag of governance, the technology issues, and more. Think of this as a bonus audio chapter to accompany the executive briefing.

Jeff Cobb: [00:01:29] We hope this diagnosis gives you useful insight, and, for a fuller picture of how associations are thinking about learning and education, we encourage you to download and read the full executive briefing. But let’s dive in.

Celisa Steele: [00:01:41] I said we were going to do a Rumelt-style diagnosis. At the beginning of the conversation, we should explain who Rumelt is, what a Rumelt-style diagnosis is.

Jeff Cobb: [00:01:51] That probably would be helpful. Richard Rumelt is one of our favorite strategic thinkers and writers on strategy. We lean on him pretty heavily in our own work in developing strategy for organizations. He has a very elegant and deceptively simple approach to strategy in which he breaks things down into three key elements: diagnosis, guiding policy, and coherent actions. Diagnosis is what we’ll focus on today. Diagnosis means really understanding the situation. Until you do that, you can’t—or at least you shouldn’t—start making the choices that are going to allow you to solve the problems or pursue the opportunities that exist in that situation.

Celisa Steele: [00:02:38] Jeff, you said “deceptively simple,” and that’s a very good way to characterize Rumelt’s work. So much of good strategy is deceptively simple. Understanding the situation to get to a diagnosis involves simplifying the complex. The situation, everything that’s happening in the world and the environment in which any learning business operates, all of that’s relatively complex. But you have to be able to home in on what exists and what’s evolving that really matters and makes a difference for your learning business.

Jeff Cobb: [00:03:14] Once you’ve got that diagnosis, you can move to creating what Rumelt describes as the guiding policy, which is the overarching approach to what you’re going to do, given that diagnosis. How will you make choices to solve the problem or take advantage of the opportunity that’s before you? The guiding policy can be boiled down to just a few sentences that say, “This is how we’re going to go about our work.”

Celisa Steele: [00:03:42] Then the coherent actions are going to translate that guiding policy into the trackable and manageable things that need to be done. One of Rumelt’s key insights about strategy is that you can’t separate it from execution. For strategy to work, things have to be done. That’s why coherent actions are part of what he covers. But, for today, we’re going to focus on diagnosis, not the guiding policy, not the coherent actions.

Jeff Cobb: [00:04:09] And we’re going to base the diagnosis on what we heard in the association CEO interviews and what we know from broader work with learning businesses.

Celisa Steele: [00:04:19] We’re focusing on the diagnosis because we believe that big parts of this diagnosis will apply broadly to many association learning businesses. The guiding policy and the coherent actions are going to be more specific to any given association. That said, for this to be a true diagnosis for your learning business, you’re going to need to go deeper on the points that we’re going to raise. You’re going to need to think about how they apply in your specific situation. But we do believe that the eight points we’re going to cover are broadly descriptive of the situation most association learning businesses are operating in. The first point in our diagnosis already came in the intro. It’s the observation that the old model still works well enough that it’s blocking reform.

Jeff Cobb: [00:05:12] This is the classic, “We don’t have a ‘bleeding at the neck’ problem here” that you hear business leaders talk about. For decades, associations have been at the center of their professions’ learning ecosystems. They could charge reasonably for required CE or draw on member loyalty to get folks to come to conferences and courses. And they could make enough from that to fund the rest of the work that they do—or at least help to fund that work.

Celisa Steele: [00:05:39] More recently, we’re seeing attendance, renewals, and attention all dropping off. They can’t be counted on as certainly as they could be counted on in the past. Many associations aren’t getting the same level of attendance at conferences or the same number of enrollments in courses. Renewal isn’t necessarily a given anymore, and, on top of all that, simply getting member or learner attention has gotten much, much harder.

Jeff Cobb: [00:06:09] A lot of the leaders we spoke to said revenue from education is flat or even declining. At the same time, learner expectations are rising—they expect more polish and the latest and easiest tech. They expect convenience and speed. This slow bleed—remember it’s not a bleeding-at-the-neck problem—is creating a false sense of stability. The business isn’t imploding. It doesn’t look like an immediate emergency. As a result, boards and executive teams may be postponing fundamental or structural changes, postponing ponying up the investment needed for education if it’s going to continue to play the significant role in the association’s value and revenue structure that it has in the past.

Celisa Steele: [00:07:00] So that’s the first point. The second point in our diagnosis is a shift in power and focus from individual learners to employers. Many of the CEOs that we interviewed are seeing great potential in serving not just those individual learners but the employers where those individual learners work.

Jeff Cobb: [00:07:20] Arguably this has always been true—you may have an individual purchasing, but the employer has always been standing behind them as a source of reimbursement or at least as important in freeing up the time for the learner to participate. But the employer role is becoming more forefronted. A lot of companies, corporations, governmental agencies, whatever are looking to outside sources to support what they’re doing in training. Training is one of those things that can fluctuate up and down with economic conditions. If employers can look to an association in their field that has the expertise, that has the curricula that are going to serve their people, that’s incredibly valuable. And both employers and associations are starting to realize that value more now.

Celisa Steele: [00:08:07] That point leads into our third point in the diagnosis, which is that supply has exploded. There are so many more choices out there now, for both your B2C and B2B customers. Jeff, you were just talking about employers recognizing associations as potential sources for training. That’s true—but it’s also true that, in some markets, employers compete with the association. They have enough in-house staff working in L&D that they’re not going to necessarily turn to an association to help them with onboarding or upskilling. That’s one example of some competition, but there are many others.

Jeff Cobb: [00:08:44] Yes, the market’s flooded with free Webinars, YouTube videos, vendor academies, and massive open online courses. Now we’ve got AI, which can generate pretty much whatever you want in terms of a learning experience on demand. But, in the midst of that explosion of content and options, what’s scarce is trust. Some of the CEOs talked about their associations providing a stamp of quality in their marketplace, and many perceive trust as their last defensible advantage.

Celisa Steele: [00:09:17] A lot of associations are the owners or developers of standards, or they develop and own a certification. They often have peers or experts reviewing content. All of that contributes to that idea of being a stamp of quality. An association can say, “Hey, this material’s been vetted; it can therefore be trusted,” and that’s not necessarily true of a YouTube video or a ChatGPT answer, for example.

Jeff Cobb: [00:09:43] And we know credibility alone isn’t going to pay the bill for developing content. There’s been too much of a culture that’s developed over time among members of expecting to be trained or educated for free. Associations are caught between being a source but then also being a validator of quality, and, at the same time, they’re under tremendous pressure to offer content for free or inexpensively. It’s a difficult economic position to be in.

Celisa Steele: [00:10:12] What it takes to truly stand behind a stamp of quality can be quite expensive. The time and the energy that many people have to put into that review and validation can cost a lot. So we have exploding supply, and there’s this issue of trust, and, for the moment, associations tend to have an advantage there compared to the alternatives.

Jeff Cobb: [00:10:33] Our fourth point in the diagnosis is that portfolio logic is broken.

Celisa Steele: [00:10:41] What we mean by this is that many associations have landed on their current portfolio unintentionally. It wasn’t built intentionally. They’ve inherited a patchwork of legacy programs. Maybe there’s not a whole lot of apparent logic—economic/pricing logic and logic in what content is covered, about what’s in the portfolio. There’s an attitude of “We have these things; we inherited them; we’re going to keep them running.” A number of the CEOs that we talked with said they have really big catalogs, but only a small percentage is being used.

Jeff Cobb: [00:11:18] So much gets driven by committees in associations or individual subject matter experts who advocate for one course or another. As you said, it turns into a patchwork of offerings. The typical association portfolio is going to contain maybe one big or a few profitable offerings—a conference or a certification. Then there will be some break-even offerings—maybe a little online learning or some Webinars. And then there’s typically a long tail of low-margin or flat-out loss-making programs. There’s often no disciplined pruning. It’s very hard for organizations to sunset anything.

Celisa Steele: [00:11:58] One of the CEOs said that the missing capability is “purposeful abandonment.” I like that phrasing: purposeful abandonment. It’s a nice, fancy way of saying “sunsetting.”

Jeff Cobb: [00:12:09] We’ve talked about four of our eight points so far. One, the old model is chugging along, not well enough to pave the way to the future but also not badly enough to force reform. Two, market power has shifted to employers. Three, supply has exploded, but authority and trust have not, and there’s still a lot of authority in associations. And then, four, the portfolio logic is broken. Now the fifth point in our diagnosis is that technology and specifically AI are changing both production and consumption and doing it faster than most associations feel able to retool.

Celisa Steele: [00:12:54] At this point, it’s easy for a learner to turn to ChatGPT or an equivalent, maybe upload some source materials or point to an association publication and say, “Hey, give me some questions to help me prepare for the exam” or “Help explain this concept to me.” Those are things that associations have traditionally, historically done. They’ve provided the exam prep. They’ve created microlearning. So all of this raises an existential question for associations.

Jeff Cobb: [00:13:23] It really does. I talked to a CEO who did this herself—and good for her for doing it. She thought, “We’re offering this exam prep toward a certification, but maybe a learner could just go ask AI to create that prep.” So she tried that, and, yes indeed, AI created some completely viable exam prep for that certification. That shows that AI isn’t just about delivery efficiency and being able to crank out content. It’s also about AI flooding the market with credible-looking instruction, which weakens associations’ claim to be the trusted source—unless associations build technical literacy and proprietary data advantages. Back to trust. There’s trust and authority, and associations need to be able to use technology and AI tools to help surface and reinforce their trust and authority.

Celisa Steele: [00:14:15] That points naturally to an idea of an association taking all of its vetted content and creating a locked-down AI model that only draws on that vetted material. At least two CEOs that we talked with were thinking along those lines, of creating a cordoned-off large language model to deliver immediate and personalized learning support that is grounded in vetted, trusted content. But, at least for those two, that was just an idea at this point.

Jeff Cobb: [00:14:47] We’re seeing some associations implement AI, but more are still in that “just talking about it” phase. I’m also a little concerned that most of them are thinking about private AI in terms of a member benefit or something they build into their Web site. I’m not sure they’re thinking about it as professional development, as education, as something that could have a business model associated with it.

Celisa Steele: [00:15:13] The sixth point in our diagnosis deals with governance. Along with governance, we’ll throw culture in there as well. A lot of associations are structured in a way, governed in a way that rewards the status quo. It rewards continuity rather than experimentation or innovation.

Jeff Cobb: [00:15:32] During these interviews and in some other conversations I’ve had with CEOs, I’m hearing leaders of organizations question whether they should even be in the education business because they’re having such a hard time with governance and culture, feeling like they’re having to fight against governance and culture. And, in the meantime, for-profit competitors are running circles around these associations.

Celisa Steele: [00:16:00] The ability to experiment is going to be critical for association learning businesses who want to move beyond diagnosing the situation and get to those other parts of strategy that we mentioned at the beginning—the guiding policy and a set of coherent actions.

Jeff Cobb: [00:16:10] One CEO I talked to mentioned a radical restructuring of his organization, including looking at how committees are formed and dissolved. They had to change bylaws so they could be more responsive and agile. Another talked about a constant battle to cut back on committees, but no sooner do they cut some back, than others spring up.

Celisa Steele: [00:16:31] I remember that. He said it was like playing Whack-a-Mole. That question of whether associations should remain in the learning business at all is interesting because we asked the CEOs if associations were to stop offering education, what would the result be? Several of them said, somewhat sadly, that they’re not sure that people would miss it. Would anyone even notice if they were to stop? Personally, I think that, for many associations, if they were to stop offering education, that would be missed. It would be noticed. Not always, but often. That said, even if it were to be noticed, I do think there is a broader recognition issue at play. Associations aren’t recognized in the way that they perhaps should be when you think about the pivotal role that they play in adult lifelong learning, continuing education, and professional development, all that training that needs to happen after someone completes higher education—or not even higher education, if a degree isn’t involved. There’s a lot of work and value that associations are delivering, but it’s not broadly recognized by society. And that’s the seventh point in the diagnosis: The understanding of associations’ role in education and learning is underdeveloped outside of the association world.

Jeff Cobb: [00:17:54] It really is. It’s an interesting thought experiment. I suspect that if you were to turn off the tap completely on all association education, people would notice immediately that it’s no longer there because associations are playing a critical societal role in adult lifelong learning. Lifelong learning is increasingly recognized as essential in the world and the economy in which we all live. But you don’t often hear association CEOs out there talking about that and making that point. You don’t see associations referenced in articles around lifelong learning. I’ve noticed this for years. One of the CEOs made the point that so much of what associations do tends to happen in back rooms and conversations about advocacy that happen in the hallways of conferences. So what associations are doing is not necessarily visible in the way that you might see, for example, a university promoting what they’re doing with continuing education and professional development. For the university, that’s their whole identity; that’s their business versus it only being part of what associations do. Universities are going to be out there in the press and media around that. They are out there in the press and media around that. But a university doesn’t have the kind of profession/field/industry depth that an association has or that ongoing relationship and contact with a set of members, the people who are working in that field or profession.

Celisa Steele: [00:19:28] The eighth and final point in our diagnosis of the current situation for learning businesses has to do with capabilities and capacity. We heard clearly from most of the CEOs that they know they need to be more data-driven. They know they need to have some sort of organizing concept—a competency model—that drives what they’re offering, and they need to map their offerings to that organizing idea. They know that they need to engage with employers and get crystal clear on what those employers need and value. They know that they need modern technology that’s going to help create that wonderfully smooth user experience and provide ready access to rich data that they can mine internally to help make decisions. All that is clear. But having access to the money, the know-how, the time, the energy to do all of those things, that’s less clear.

Jeff Cobb: [00:20:27] That loops us back to the first point we made around the historical, traditional model. It’s not broken enough for boards and executive teams to say, “All hands on deck! We must invest the time and money in steering the ship in a different direction—hiring more people, hiring people with different capabilities, putting the technology and processes in place to be able to deliver excellent, meaningful, modern learning experiences.” All that is different from standing up a catalog and running people through an e-commerce system or standing up an event and taking registrations.

Celisa Steele: [00:21:05] You tied this back to the first point. It also ties to the sixth point, which was about governance and culture, because part of what’s at play is that acting in the way that these CEOs know they need to act is often not what’s familiar and comfortable for associations. This requires an agile mindset. It requires an ability to make decisions quickly and then to act quickly. It takes experimentation and being okay with some failures as long as you’re learning from them. And a lot of what’s needed to get the capabilities and capacity that these associations need can be slowed down by those governing structures that are committee-heavy or rely on set monthly meetings, and maybe decisions can’t really be made outside of that meeting timetable.

Jeff Cobb: [00:21:55] It gets back to the title of the executive briefing: “Where Mission and Margin Meet.” There’s a certain culture, a certain infrastructure, a certain operating model that goes with a mission-driven organization, like an association, that tends to be different from what you might find in, say, a commercial training provider or any solely revenue-driven business. Associations have to balance mission and margin, and that’s a leadership challenge. It’s one that many of the CEOs we interviewed are facing up to and wrestling with—and good for them. Unfortunately, more broadly across the association sector, that’s not necessarily happening.

Celisa Steele: [00:22:36] We’re seeing association learning businesses grapple with that mission-and-margin question that you just pointed to, Jeff. They’re thinking about how do they make sure that their portfolio is supporting their mission without draining the organization, maybe even contributing back to the organization? And how are they making sure that what’s in that portfolio truly is what should be there? What will serve the learners, what will serve the employers, what will serve society at large?

Jeff Cobb: [00:23:04] To sum the diagnosis up, the individual member-retail model that once sustained associations is giving way to more employer-driven demand.

Celisa Steele: [00:23:14] Abundant and often free digital offerings now available have created a very different dynamic in the marketplace. There is so much choice now than there was a decade or two decades ago, certainly more than 50 or even 100 years ago when some associations were being formed. And, because of all that competition, it’s noisier and harder to even get the attention of your learners. Even if you do get their attention, even if they do recognize that they need to learn something, you’re just one option in a field of many options.

Jeff Cobb: [00:23:51] Credibility remains high for associations at this point, and it helps them stand out for now, but that credibility, trust, and authority need to be bolstered and guarded.

Celisa Steele: [00:24:03] There are governance issues and cultural habits that may be holding associations back from addressing the competition, from pursuing opportunities like B2B models. There are patchwork portfolios that need to be made more intentional. There’s an underinvestment in technology, including AI, and in other aspects of capacity and capabilities, and that underinvestment is preventing organizations from being able to adapt as they need to.

Jeff Cobb: [00:24:33] The strategic core of the problem is a structural mismatch. Associations still operate as catalog providers in a market that now needs architects—architects designing trustworthy, employer-aligned, tech-enabled learning pathways and infrastructure rather than simply maintaining a catalog of programs.

Celisa Steele: [00:25:01] Be sure to check out the executive briefing that’s based on these interviews with association CEOs.

Jeff Cobb: [00:25:18] If you enjoy the Leading Learning Podcast, please share this episode or another with a colleague or co-worker you feel would appreciate and get value from it. And please spread the word about the executive briefing too.

Celisa Steele: [00:25:31] What we covered today is part of a larger story. The CEOs that we spoke with offered sharp and honest insight about what’s holding their education businesses back and what’s needed to move forward.

Jeff Cobb: [00:25:44] We hope today’s episode and the executive briefing spark some internal conversations and maybe some overdue shifts in your own learning business.

Celisa Steele: [00:25:52] Thanks again—and see you next time on the Leading Learning Podcast.

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The post Associations as Architects of Learning appeared first on Leading Learning.

Building or refreshing certification prep, reviewing prices, or expanding into new formats? This conversation offers concrete examples of how to move fast, listen well, and align your portfolio with both mission and margin.

Letty Kluttz, senior vice president of membership, education, and programs for the Association for Professionals in Infection Control and Epidemiology (APIC), talks with Leading Learning Podcast co-host Celisa Steele about launching three certification prep courses in under a year, developing a clear pricing philosophy, and introducing microlearning and microcredentials to meet learners where they are. Letty also discusses how APIC is using data and collaboration to focus on high-demand topics, building a content strategy that works and connecting education outcomes to measurable impact in healthcare settings.

To tune in, listen below. To make sure you catch all future episodes, be sure to subscribe on Apple Podcasts, Spotify, or wherever you listen to podcasts.

Download a PDF transcript of this episode’s audio.

Celisa Steele: [00:00:03] If you want to grow the reach, revenue, and impact of your learning business, you’re in the right place. I’m Celisa Steele.

Jeff Cobb: [00:00:10] I’m Jeff Cobb, and this is the Leading Learning Podcast.

Jeff Cobb: [00:00:16] Learning businesses are constantly asked to do a lot—support the mission, satisfy learners, and drive sustainable revenue. This episode offers a real-world look at how one organization is doing all that.

Celisa Steele: [00:00:29] This episode, number 466, features my conversation with Letty Kluttz, senior vice president of membership, education, and programs for APIC, the Association for Professionals in Infection Control and Epidemiology.

Jeff Cobb: [00:00:43] Letty shares how APIC developed and launched three new certification prep courses in less than a year, what they learned about listening to learners, and how they balance mission and margin in pricing and portfolio decisions.

Celisa Steele: [00:00:56] We also talk about APIC’s shift to more flexible learning formats—including virtual instructor-led programs, microlearning, and microcredentials—and how APIC is using data and collaboration to focus on topics learners most need.

Jeff Cobb: [00:01:11] The conversation offers a useful perspective for anyone managing an education portfolio that has to deliver both impact and income. Here’s the conversation with Letty Kluttz.

Celisa Steele: [00:01:27] Tell us a little bit about APIC, what it does in general. Also, I would love—given that we’re the Leading Learning Podcast—to get a high-level look at what’s in your learning portfolio, what you offer by way of education and learning.

Letty Kluttz: [00:01:40] APIC is the leading professional association for infection preventionists, or IPs, as we like to call them, and our mission is to advance the science and practice of infection prevention and control, ultimately to protect patients, healthcare workers, and communities. We have about 15,000 members in a variety of different settings—from acute care, hospitals, long-term care, home health, you name it—but they are the unsung heroes of keeping everyone safe and free from infection. So that is who we are and what we do. As far as education, as you can imagine, with an association, education is so, so important and one of the critical things that we do. Education helps our members develop professionally and personally. It also helps them stay on top of all of the things that they need to be aware of when they are keeping patients safe. It is definitely a cornerstone of what we do and what we offer. We offer a suite of different trainings—short, longer, online, instructor-led, asynchronous, synchronous, you name it—because we really want to meet our members where they are in their professional development and education journey. That’s just a very high-level overview of what we offer.

Celisa Steele: [00:02:56] One of the reasons I wanted to talk to you is that I’ve had the chance to hear you speak a few times over the last year or so about some of what you have going on around certification and some certification prep work. For the sake of our listeners, and for my own sake to get to hear it again, would you give us a sketch of what APIC has done and gotten out into the market in an impressively short period of time?

Letty Kluttz: [00:03:21] Sure, and thank you—because we look back, and we’re like, “I can’t believe we actually pulled that off.” This work began in earnest in 2022, and it feels like that should be so much longer ago than it actually is. We saw the need to update and upgrade, quite frankly, our cert prep. At that particular point, it was almost divine intervention and this perfect storm of different things happening at the same time. Our certification body, CBIC (the Certification Board of Infection Control and Epidemiology), was getting ready to launch a new certification, and we knew that the first question our members would ask is, “How do I prepare to take this certification?” That is what sped things up and got the ball rolling when we looked at “Okay, we don’t have the bandwidth or the expertise, quite honestly, to create a cert prep course for this new certification.” And then it became “Okay, our members have been asking for certain aspects as part of cert prep, from flashcards to pre-test to post-test.”

Letty Kluttz: [00:04:25] We took a step back and said, “This is an opportunity for us to upgrade the experience,” and so we reached out to the Holmes Corporation. I had worked with them in a previous life on cert prep, and we put together a timeline and a plan to bring all of this to fruition. We created three separate cert prep courses in less than a year, which I do not recommend for anybody, but it is something that we certainly are very proud of. The feedback has been fantastic. As IPs in particular and in healthcare, this whole concept of continuous improvement has certainly brought forward with our educational experience, especially with cert prep, continuing to listen to what our members want, to what they’re looking for. We just launched an updated version of our cert prep courses, so they have been exceeding our expectations, and our learners have been very, very happy with the materials that we’re providing to them.

Celisa Steele: [00:05:27] You were talking about how the feedback’s been great, how what you’re hearing is really positive. One of the things I would love to get you to talk about is about how APIC goes about listening to member needs, to learner needs, what methods or processes you might use to make sure that you’re hearing what they say they need, and then to what extent you might perhaps augment what they’re saying they need with what you know they might need that they might not even know that they need yet.

Letty Kluttz: [00:05:55] That’s a great question. We solicit feedback from a variety of different places. We have all of our cert prep take place in our learning system, and, as part of that, when someone finishes going through the cert prep course, there’s a survey that we provide to them that asks questions about what they liked, what they didn’t, suggestions for improvement. Sometimes we get suggestions that are unsolicited. When we do instructor-led, we also do a survey at the end of that. A variety of different ways where we want to hear from them. “Did this help prepare you? What are some things you would like to see as part of these courses?” To your point, it’s balancing what they say they need with what we know we can provide to them. A perfect example of that is, in the previous version, before we launched the upgraded platform, it was no audio. You just went through; you read. And that was some of the feedback we got: “We would like to be able to listen. We would like to be able to go in our car and put this on audio and study as we’re driving to whatever place or have that as an option.”

Letty Kluttz: [00:07:05] And so we did just that. That’s a good example of listening to where our members and customers are and what they’re looking for. That was extremely helpful. And flashcards—it sounds so simple. People love flashcards. They love a good flashcard because it’s a good, again, checks and balances to help make sure that they’re learning the content. Those are two examples of “We knew that this is something they had been asking for years,” and it validated what we thought. Because the other thing is that you don’t want to assume that you know what your members and your customers need, and so being able to ask the questions in a variety of different ways helps validate what you think they need at the same time, so that, again, you’re meeting them where they’re at.

Celisa Steele: [00:07:48] The reliance on post-course surveys or post-learning experience surveys feels pretty common. A lot of organizations do that. How do you go about hearing from folks that might not fill those out? Or perhaps it’s required, and so you’re getting more feedback there, but again that balance of are you hearing from the vocal minority? Or do you feel like, “Oh, no, we’re actually hearing from our membership what they need”?

Letty Kluttz: [00:08:13] What’s nice is, in order to get a certificate of completion, you have to take the survey, and you have to provide feedback. That’s a little carrot that we dangle. Part of it too is helping them understand that we take their feedback seriously, and we do something with it. It’s not just you filling out a survey for the sake of filling out a survey, but we want to make sure that we are providing information and content that they find useful, that they find valuable, and it’s worth the investment that they’re making—because it is an investment.

Celisa Steele: [00:08:43] One of the things that I know about associations and association learning businesses is that often what they offer in terms of education or learning can end up having to walk a balance beam between being out there because it supports the mission of the organization and also potentially being this revenue driver for the association to help feed some of the other expense areas of what has to happen. I would be curious to ask you about how APIC thinks about that—or how you, Letty, think about balancing mission versus margin in terms of what you offer as education.

Letty Kluttz: [00:09:20] That’s a great question. I think it’s something that probably all associations struggle with. At the end of the day, no mission, no money, but, obviously, our mission is our priority. I don’t think there’s anyone who couldn’t get behind a safer world, a world without infection, and driving the science and practice of IPC. It’s definitely a mission that everyone rallies behind, which I think is a great thing. But you do have to balance that, and you do need to look at making sure that you are bringing in enough revenue to cover the expenses that you’re providing because, again, no money, no mission. It is absolutely a delicate balance, and it’s something that we struggle with. Something that I have certainly learned throughout this process and this journey is that understanding and communicating the value proposition to the people who are purchasing your education materials is so, so important, and you don’t want to undervalue the education that you’re providing to your members. And that was an aha moment for me because you can always discount. You can’t increase pricing.

Letty Kluttz: [00:10:32] It’s having a different approach and a different thought process but having a pricing strategy as an association, as an organization, and looking holistically across the portfolio that you offer about the value proposition that you’re giving to your members—it’s such a critical part of that conversation when you’re looking at “How do we drive revenue, and how do we have those conversations internally?” But, again, educating your members on the value that they get and all of the different features and doing some competitive pricing too is a really important part of the process. Because, again, you don’t want to devalue what you’re providing to them, but you also don’t want to be like the Porsche of the education space, especially in the association, where there is so much price sensitivity, especially these days in healthcare, where everything’s being cut right and left. We want to be mindful of that. But it’s a balance, and it is a dance between the two, to be perfectly honest.

Celisa Steele: [00:11:29] I appreciate what you’re saying there because sometimes what can be missed is the idea that price is perceived, often not consciously, as an indicator of value. If something’s priced too low, sometimes ironically then the learner can be like, “Well, it can’t be that good if it’s that inexpensive.” Does APIC keep some things in its portfolio that might be only breaking even because it really does support mission? And then you might have others that still, of course, support mission, but are bringing in more. Do you have any kind of way you try to actively balance what the makeup of the portfolio looks like in terms of the revenue that’s being brought in?

Letty Kluttz: [00:12:13] Yes, I think it is a balance, and you have to look holistically. You can’t just price one thing in a vacuum. It is looking across the organization and across the portfolio, across the suite of products that you’re offering. And we offer a variety of different educational opportunities outside cert prep. We have our online learning courses. We have Webinars that are all a member benefit right now. It is looking and being mindful about what is the strategy behind what you want to price and what the overall objective is because you may have some things that, yes, are, to your point, strictly revenue-producing. Then you have others that you say, “You know what, this is the right thing to do, so we’re going to price it accordingly so that we can get more people at a lower price versus fewer people at a higher price”—having those conversations and being mindful of what that looks like when you’re putting new products and services and education material forward.

Celisa Steele: [00:13:20] How often do you revisit pricing? Is that something that’s baked into a regularly scheduled review?

Letty Kluttz: [00:13:26] It is now. I started it last year and took the time to put together an entire smartsheet with all of our offerings, and now we review all of our pricing as part of our budgeting, and we have a conversation so that the right hand knows what the left hand is doing, being very mindful of “When do we increase? When do we not?” A perfect example is with some of our signature products pricing hadn’t been raised in 10 years, but the breadth of what we had offered had grown significantly. Making sure that we are having those conversations and reviewing stuff yearly. Now it doesn’t make sense to increase every year. It just doesn’t. When you have updated content that you’re rolling out or new content, yes, that’s when you look at that, and you look, again, holistically across the suite that you’re offering and making sure it makes sense so that “like products” look like “like products.” If you have, for example, an online course, and it’s two hours, you don’t want to price it the same thing as something that is eight hours because that just doesn’t make sense. We have much more structure and an actual strategy and a pricing philosophy so that we are reviewing it every single year, every single product, and having those conversations as part of our budgeting process.

Celisa Steele: [00:14:47] As part of looking at pricing, are you also looking not just at the price tag but at the costs that go into making these products?

Letty Kluttz: [00:14:56] Yes, absolutely. Because we’re healthcare, we have to review our content every three years and update it accordingly, which is part of when we provide continuing education credit, for example. And so you have to build that factor into the budget, and you have to be mindful of “What does that look like?” As we all saw the past couple of years, you never know. I feel like change is happening so much quicker now, and sometimes those updates don’t fit that three-year lifecycle. Because there are costs associated with it, and you do want to make sure that you’re covering them as part of those conversations. When you look at updating or revising, does it make sense? That is all part of the pricing conversation—what goes into making sure that we are keeping our content fresh? One of the things that associations don’t do well—and I can pick on associations since I work at one—is we don’t do well with sunsetting material. Part of this process too…not just looking at pricing but looking at sales, looking at does this make sense to continue?

Letty Kluttz: [00:16:06] Sacred cows. There are so many sacred cows. And everyone’s stuff is so important to them—but make sure that you are making those decisions that are smart for the association and sunsetting material where the juice isn’t worth the squeeze anymore.

Celisa Steele: [00:16:22] You talked a little bit about change and how it seems like the pace of change is increasing. Tell us a little bit about how APIC is continuing to evolve its approach to revenue generation, to member value when you look at the next couple of years, given broader shifts—AI, changes in continuing education, all those things that are going on.

Letty Kluttz: [00:16:48] We seem to be in this shift of reduced attention span. I guess that’s not really recent. That’s been around for a long time. But, in a lot of ways, what I find fascinating, and one of the few positives to come out of COVID, was the thirst for virtual, for instructor-led in a virtual environment. We have so much engagement virtually, where before we didn’t really do anything that was virtual. Everything was in person. And, after COVID, we do a smattering of in-person, but most of it is all online and all virtual. Because, again, a lot of times, with our audience, with our members, with IPs, they don’t have the luxury to be able to leave their facility for three to four days, and this allows them to be able to stay at home, to not travel. It reduces costs. Virtual has been a huge game changer for us. We have gotten into microcredentials, these small, bite-sized, flexible ways of learning. That’s something that we launched earlier this year in June; we launched our first microcredential on surveillance. It’s an eight-hour course. You can do it as quickly or take a year to review the content and take the exam at the end. But that’s an example of how we are doing smaller, bite-sized learning opportunities.

Letty Kluttz: [00:18:22] We have our microcredentials. We also have microlearning. So we’re talking 10- to 15-minute snippets on very, very specific topics. You have to be specific when you have that short amount of time. But, again, meeting our members where they are. A lot of times they want just-in-time. You know that you want to learn something about this particular topic. Well, I can now go here and find that particular topic that I can spend 15 minutes on as a refresher versus sitting through a three-day course just to learn a part of the content that you want to see. Again, it’s meeting people where they are—being able to offer all of the different types of learning. We like to say choose your own adventure when it comes to your preferred method of learning and engaging with content. It gives the learner a lot of flexibility—again, to meet them where they are.

Celisa Steele: [00:19:21] Is the microlearning something that they can earn credit towards maintaining…?

Letty Kluttz: [00:19:26] Yes, it’s a couple of different things. For example, the one that we launched in June is on surveillance, eight-hour course. At the end of the course, you take an assessment, and then when you pass it, you get a digital badge. That digital badge is something that they can then put on LinkedIn, on their signature in Outlook, whatever it is. You can also—if you take those microcredentials—earn what we call infection prevention units (IPUs) for our certification that is offered through CBIC. You can use it in a variety of different ways. You can also get continuing education credit, from a nursing standpoint. There are a lot of different options for the learner, depending on what they need recertification or continuing education credits for.

Celisa Steele: [00:20:17] When you think about what’s coming, what challenges or opportunities are you seeing for APIC? What’s on your mind? What are you tracking

Letty Kluttz: [00:20:26] This political landscape we’re in right now is challenging. It’s hard, and it’s hard for our members. Healthcare in particular has been impacted by this, and so that is absolutely on the forefront. And, again, it comes down to meeting our members where they are and making sure that we’re providing educational content for them. Some of the things that we’ve been talking about and brainstorming is “How do we unbundle some of our topics?” One of the things that APIC is working on this year is having what we’re calling “expert-informed resources,” which is basically our version of a content strategy. Really focusing on specific topics to help us focus on telling our members—and this is all based on data that they’ve told us—that we know they want information on these specific content areas. That is helping us focus our time and energy into making sure we’re providing the education that they told us they want.

Letty Kluttz: [00:21:39] But it’s also looking at “What do you already have?” You never have to always create something from scratch. Taking a step back and saying, “What do we have that we can repurpose? Where are the gaps? What do we need to do? How do we collaborate across the enterprise, across the organization, to make sure that we’re putting together these different educational opportunities?” Maybe there’s a Webcast, maybe there’s a microlearning, maybe there’s a microcredential, and it doesn’t necessarily have to be all of the things for the same content area. I am super excited and really proud that we’ve taken that step. It’s something that we’ve talked a long time about. And I think it is absolutely going to come back in dividends to us. We’re honing in on specific areas where we know our members have said, “This is where we need help. This is where we need more information on….” I’m a big fan of working smarter, not harder, and that is a really good example of what we’re doing to ensure that that happens.

Celisa Steele: [00:22:42] Talking about working smarter, not harder, you said you have about 15,000 members. How big is the APIC staff?

Letty Kluttz: [00:22:49] We are small but mighty. We’re about 50 employees. There’s a lot of collaboration, as I’m sure you gathered from that conversation we were just chatting about. From a content strategy standpoint, it’s all hands on deck. Honestly, it takes a village. It doesn’t fall on one person’s shoulders to bring this forward. Going back to one of your previous questions about our membership, we were spending a lot of time talking about the member value proposition. We’re going to be doing a membership campaign, talking about the benefits of being a member, all of the things that we offer to our IPs. Because that’s also a critical part of this too—helping people understand the value and that they’re proud to be part of an association that is bringing forward all of this information to help them be better and do better.

Celisa Steele: [00:23:41] You’ve talked about positive feedback. We’ve talked some about revenue. Both of those are indicators of how you’re doing with your learning products and education products. But I’m also thinking about this idea of impact. When a learner comes in, engages in one of these microlearnings, does a microcredential, or does the cert prep, there’s the idea of impact. Are they actually learning? You even said about the mission statement is about changing practice or improving practice. Talk about how you think about the impact of what you offer in terms of learning. What are you tracking? Or what would you hope to track that you can’t currently track?

Letty Kluttz: [00:24:21] That’s another good question. One of the things we’re tracking, especially with certification, there’s a huge opportunity when you’re tracking those who go through cert prep courses, who obtain their certification—how do you tie it back into metrics that impact infection prevention? How do you tie it back into reduced-HAIs (hospital-acquired infections)? We have a research center, and they have been doing so much research in that regard. They launched a staffing calculator. You put in data specific to your facility; it then spits back a report that says, “Here’s the recommended number of IPs that you should have on staff.” And the data they’re pulling back from that show that there’s a direct correlation between the number of IPs you have on staff and a reduction in the number of infections. That’s golden.

Letty Kluttz: [00:25:23] There’s been so much work in collaborating with our research center with our EIR (expert-informed resources), making sure that we are all tying it back to how we can help them be better and do better. You also get the testimonials and anecdotes, not the hard and fast metrics, but stories that people talk about, how it helped them do X or Y. We have two publications that we offer: AJIC (American Journal of Infection Control), which is our scientific magazine, and Prevention Strategist, so we always encourage members to submit their stories, submit what they did to demonstrate the value of the practice of infection prevention and how it impacted patients’ outcomes, what they’d done so others can learn from their own experience. It is holistically bringing in all of those different stories to show people how what they learn and put into practice has an impact.

Celisa Steele: [00:26:34] That’s great. It sounds like you’re doing really good work to be able to make that clear connection between “Here’s what we’re helping you learn, here’s what the IPs provide, and this is what it means in terms of reduced infection.”

Celisa Steele: [00:26:45] This is Leading Learning Podcast, so we always love to ask folks who come on a little bit about their own approach to lifelong learning. Do you have resources, practices, or habits that help you stay up-to-date and on top of your game?

Letty Kluttz: [00:26:59] Yes, I’m a huge proponent of lifelong learning. You never know everything. I think having that mindset and that perspective of “You can always do better and learn more” is important to being a better human and employee. I really do. Whether it’s learning about leadership or infection prevention, how you can better serve your members, being a sponge and constantly reading the articles that are submitted for our publications and reading the research agenda and the stuff that comes out of our research center and staying informed makes you be a better, informed consumer of information too. I read our magazine all the time, making sure I am listening to what our members are telling us.

Letty Kluttz: [00:27:53] As you can imagine, there’s never a dull moment with what’s coming out of the White House right now, so being on top of current issues is so important, but making sure you are approaching it and hearing all different sides. It’s easy to fall into—especially in the political environment we are in right now—listening to one side and not understanding what everyone is saying about different things. That’s a really important perspective, especially in the healthcare space, to have that lens of “Okay, today I’m going to listen to this particular news. Tomorrow I’m going to listen to this one. I want to hear what’s going on.” Our members aren’t shy. They will share their opinions with us, which is a great thing. Yet again, I’m a huge, huge proponent of continuous learning. It’s also the nature of healthcare—performance improvement, continuous learning, continuous improvement. Having that perspective, you have to carry it forward when it comes to learning and continuing to develop as a leader.

Celisa Steele: [00:29:00] It sounds like you’re walking the walk. If you’re going to be talking to your members about continuous improvement, you need to embody it yourself. We’ve covered a fair amount of ground, so if you wanted to make sure listeners took away one, two, or three points, what would you point them to? What would you want to reinforce?

Letty Kluttz: [00:29:20] I would say don’t undervalue what you provide your members. Making sure you are reviewing pricing holistically across your organization on a regular basis—that’s so important. The third thing is listen to what your members and customers are telling you, and then meet them where they are.

Jeff Cobb: [00:29:52] We’re not done quite yet—stick around for our recap.

Celisa Steele: [00:29:54] Check out APIC’s Web site and Letty’s LinkedIn profile. And Letty is happy to chat and share from her experience, as she is a big proponent of sharing to help others learn.

Jeff Cobb: [00:30:11] If you got value from this episode, please share it with a colleague or leave a rating and review. Those actions help others find the Leading Learning Podcast and support the work we’re doing.

Celisa Steele: [00:30:23] Thinking about all that Letty shared, I was really interested to hear that APIC’s research center has data showing the direct correlation between the number of infection preventionists on staff and a reduction in the number of infections in that setting. That’s the kind of real-world outcome and impact that learning businesses need to be able to show.

Jeff Cobb: [00:30:45] Another thing Letty said that’s very well aligned with our thinking is her admonition to not undervalue what you offer. We’re big proponents of value-based pricing and understanding that price is often unconsciously correlated with value—low price, low value; higher price, higher value.

Celisa Steele: [00:31:03] And even though our podcast is free, rest assured that what we offer is high-value stuff. Thanks again for listening—and see you next time on the Leading Learning Podcast.

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Unsure about AI guardrails, AI data risks, or which artificial intelligence project to pick first? You’re not alone.

Tori Miller Liu, president and CEO of the Association for Intelligent Information Management (AIIM), talks with Leading Learning Podcast co-host Celisa Steele about treating artificial intelligence initiatives as data initiatives, picking one to three practical use cases that augment people (without replacing them), writing a lightweight AI usage policy that’s easily understandable and updatable, and balancing mission and margin with a simple product profitability lens. They also touch on how AIIM’s portfolio supports information leaders who are turning messy, unstructured content into fuel for generative AI—and improved performance.

To tune in, listen below. To make sure you catch all future episodes, be sure to subscribe on Apple Podcasts, Spotify, or wherever you listen to podcasts.

Download a PDF transcript of this episode’s audio.

Celisa Steele: [00:00:03] If you want to grow the reach, revenue, and impact of your learning business, you’re in the right place. I’m Celisa Steele.

Jeff Cobb: [00:00:10] I’m Jeff Cobb, and this is the Leading Learning Podcast.

Jeff Cobb: [00:00:17] If you’re grappling with how to start or how to continue responsible AI use in your learning business, this episode can help. If you’re unsure about guardrails, worried about data risk, or struggling to pick the right first project, you’re not alone.

Celisa Steele: [00:00:31] This episode, number 465, features my conversation with Tori Miller Liu, president and CEO of the Association for Intelligent Information Management (AIIM). She’s very passionate about collaboration with people, collaboration with technology, and how people can collaborate effectively with technology. AIIM helps organizations turn messy, unstructured information into fuel for performance, and Tori brings a pragmatic, personal lens to AI adoption.

Jeff Cobb: [00:01:00] Tori talks about why data access and data quality are the real gating factors, how to pick one to three concrete AI use cases that augment people rather than replace them, and why a lightweight AI usage policy you can revisit beats a 12-month strategy document.

Celisa Steele: [00:01:19] Tori and I also talk about mission versus margin trade-offs, product profitability, and how AIIM’s portfolio supports its learners.

Jeff Cobb: [00:01:28] In short, there’s lots in this episode to help you take action, so let’s roll the interview with Tori Miller Liu.

Celisa Steele: [00:01:41] For listeners who may not be familiar with the Association for Intelligent Information Management, give us a short version of what AIIM does and the problem it exists to solve or the resource it exists to be.

Tori Miller Liu: [00:01:56] We were founded in 1944—recently celebrated our 80th anniversary—and we are a nonprofit organization that serves information leaders in over 67 countries around the world. Our vision is to create a world where every organization can benefit from information management. For those who are not as familiar with that terminology, information management is the management typically of unstructured and semi-structured data. That’s what people might call “dirty data” that’s typically outside of your tidy databases. E-mails, invoices, contracts, engineering schematics, text messages, social media posts, even videos and audio—that’s all unstructured data. These days, it is absolutely the fuel for generative AI. It’s gotten quite a bit more focus in the last three years than it had before that. But folks have been doing unstructured data management since before even the 1940s, since the establishment of our organization, and it started with records management and archivists, but it’s expanded well beyond that.

Celisa Steele: [00:03:01] Tell us a little bit about how you came to lead AIIM and the path that got you there.

Tori Miller Liu: [00:03:08] I started with AIIM in November 2022. And I should mention that AIIM looks at the practice of information management through the lens of technology. We’re very, very focused on artificial intelligence and automation. AIIM, when they were looking for a new CEO, specifically wanted someone with a technology background, and my background happens to be in IT. I was formerly a chief information officer for an association, so that was a natural fit. And I’ve been really pleased and happy to help AIIM grow. We help people understand this landscape of information management through certification, resources, research, and training. It’s all that kind of stuff that I loved doing as a CIO that I now get to help our members with.

Celisa Steele: [00:03:52] You mentioned certification, training. Go ahead and give us a fuller picture of what AIIM offers in terms of education and learning resources.

Tori Miller Liu: [00:04:05] We have a Certified Information Professional certification, and that’s a certification that’s for experienced technology-focused practitioners in the unstructured data management space. For our events and educational programs, we have our hallmark program, which is our annual AI+IM Global Summit. That’s a recently redesigned and rebranded event that serves a 400-person group of individuals who want to explore the intersection between AI and information management, and we do that through interactive sessions, hands-on workshops, and also cohort-based learning. We have about 40 to 45 cohorts that are meeting throughout that annual event, and they also meet beforehand and afterwards. It’s a very interesting educational program.

Tori Miller Liu: [00:04:55] Beyond that, we have regional events. We have forums that are day-long, problem-solving events that feature roundtables and solution mapping. And then we have regional exchanges that are two-hour roundtable events that are focused on critical trends. We also have a wealth of virtual programs. We do live virtual training workshops around M365 (Microsoft 365) and also preparing for our certification and the exam. We also do Webinars and insight series that explore critical trends in the space. And we have an online training library and several different certificates, including an AI certificate, and about 45-plus and growing on-demand courses as part of that library.

Celisa Steele: [00:05:37] It sounds like a pretty robust set of offerings. Tell me about the size of the team that is behind making all of this possible.

Tori Miller Liu: [00:05:46] Small. We’re a staff of five. As part of my role as CEO, I did have to lead the organization through some transformation. We’ve reorganized/reduced workforce over the last three years. Now we have a very efficient and stellar group of staff that are doing a ton of work in keeping a big ship moving with that skeleton crew.

Celisa Steele: [00:06:12] That’s impressive to hear all that you were able to outline in terms of what AIIM offers and then to hear that that’s being done with five staff behind it. Impressive. The other thing that I heard when you were talking through those offerings is that emphasis on collaboration. It sounds like you have a lot of these cohorts; you have these round tables. Prior to you joining AIIM, has that been something in the DNA of these folks who work in information management, or has that been more of an intentional shift towards more peer-based learning in more recent years?

Tori Miller Liu: [00:06:47] I would say it’s really an intentional shift and probably a reaction. It’s ironic. While we talk a lot about AI and automation—you could say we’re pro-AI; I’m pro-automation, of course—we also understand that the way that you learn about emerging technologies and feel comfortable with them is often through human-to-human, peer-to-peer learning and understanding and being able to talk through case studies and talk to peers and crowdsource your problems. It’s been a very, very deliberate shift over the last three years to make sure that that’s at the heart of all our educational programming. We also do community conversations on an informal basis, but, on a formal basis, we found a lot of success with virtual live training workshops and all the roundtables and cohort-based learning.

Celisa Steele: [00:07:38] For many learning businesses that are part of an association, there can be a bit of a tension between mission and margin, especially when it comes to education offerings. Where does AIIM sit in terms of how you think about the education and learning that you provide, in terms of supporting mission versus generating revenue? Which one is more important?

Tori Miller Liu: [00:08:02] Our organization has been in a period of financial transformation, and we’re finally beyond that hurdle and in a position where we can stop worrying about keeping the lights on and focus on thriving. That said, we didn’t have the luxury of not thinking about product profitability, and a lot of small associations, even the large ones, have been in a similar situation. I think if you’re so focused on mission that you’re not focused on whether or not your business is healthy and functioning, you’re delusional. The business model of constantly eating into reserves is not sustainable, and part of our responsibility as association executives is not to just fulfill the mission but also to protect the legacy of this organization and its sustainability. So I’m a little torn. We’re a mission-first organization. We always ask, when we’re introducing new programs, “Is this advancing our mission, fulfilling our mission?” But if there’s no profitability, we are not doing it. We’re not moving forward.

Celisa Steele: [00:09:04] That sounds like it’s part of the initial discussion around standing up a product—is it supporting mission, and is there a business model that can support it? Talk a little bit about, once a product’s out there in the market, if it turns out to not, perhaps, be bringing in the revenue, is AIIM intentionally looking at things like sunsetting or periodically reviewing the portfolio to say maybe we need to recall some of these things?

Tori Miller Liu: [00:09:27] We do, yes. Our board and finance committee have been instrumental in helping me do that. We do have a product profitability matrix, where we’re looking at both the direct and indirect costs of the products that we produce, and it’s a pain to constantly update, but it is helpful in at least starting that dialogue. We do have one or two products in our portfolio that aren’t necessarily meeting our profit margin that we would want, but the board has at least intentionally had a discussion of, “No, this is core to our mission. We do need to see if we can improve the profitability, but we are unwilling to sunset this.” And, in other cases, we have stopped programs because they were not worth the squeeze. “The juice is not worth the squeeze,” as one of my old bosses used to say.

Celisa Steele: [00:10:15] You’ve mentioned AI and how that has changed a bit of the focus in your area of information management, how that’s become so much more important in the AI era. I know you’ve written and spoken a lot about AI and about how there’s AI aspiration, but then there’s this gap between that aspiration and reality. What do you see as the biggest barriers to being able to use AI in the way that you think organizations should be? Is it governance, skills, fear, or something else?

Tori Miller Liu: [00:10:53] I appreciate all the thought leadership that’s occurred around shifting culture and changing mindsets and change management around AI. While I appreciate it, and I agree with that, people are fundamentally critical to successful technology implementations. As AIIM’s president and CEO, I’m really focused on a paramount obstacle, which is data quality and data access. When we lack access to content for AI, that’s huge. If you can’t put data in a large language model to train it, then you’re already shooting yourself in the foot. The other side of that is, when you’re permitting access to content that should not be permitted, you are jeopardizing your association.

Tori Miller Liu: [00:11:40] Organizations have been rolling out tools like Microsoft Copilot, which is a great tool. That’s one of the biggest hurdles that you have to overcome—that it’s shining a spotlight on security issues. And then the third thing, is your data even good quality? Are you missing metadata? Is it an old version? The funny thing about all this is none of this is a new problem. We’ve been doing data analysis for over a decade now. And, as organizations were rolling out tools like Tableau and Power BI, that was shining a spotlight on content access and content quality. Really, what AI has done is point an even bigger spotlight on those preexisting issues, and so there does need to be quite a bit of attention paid to data.

Celisa Steele: [00:12:31] There needs to be attention paid to data. How does an organization go about doing that? They want to be able to embrace what AI can offer. They come to the realization that their data isn’t in the best shape. What are some of the practical steps or ways that an organization can start addressing that?

Tori Miller Liu: [00:12:49] First of all, don’t allow yourself to get paralyzed by the magnitude of the task. It’s unreasonable for a leader to come in and say, “Oh, well, data is the problem, so fix all of the data.” That is not attainable unless you have a ton of resources to back up that challenge. It’s really about managing scope. With an AI project, you want to identify a use case first, look at the data that you need to be successful with that use case, and manage the scope. Then it becomes a much smaller dilemma to deal with. You can learn from that experience. You can learn from saying, for this particular AI project—maybe it’s, say, a matchmaking AI system, where I’m going to give it all of my membership data, and I am going to give it all of the sessions for our conference, for instance, or all of the interest areas for our members, and now I have three sets of data that I want to look at, and I want to help match people who might have similar interests.

Tori Miller Liu: [00:13:51] That’s a much more manageable project than saying, “Oh, I need to look at all my finance data.” “I need to look at all my publications data, events data.” Etc. Keep it small, keep it focused, and then focus on how good is good enough. You don’t need the data to be perfect for AI, but it does need some fundamental things, especially around metadata. It needs to know, is this data the most current version? There might be other metadata fields that you need populated, depending on the circumstance and the use case. But there are consultants that can help you with that, if all of that still seems overwhelming. And there are also certainly quite a number of certifications and data certifications that you could look at to help build those skill sets and understanding, not just from AIIM, but groups like DAMA [Data Administration Management Association). There are lots of groups that offer really good training that can help you feel a little more confident.

Celisa Steele: [00:14:42] You also mentioned security and risk when you were talking about some of those barriers to AI implementation and getting to where organizations might aspire to be. Recognizing that there are those risks in potentially sharing data that shouldn’t be shared with the AI, all of those things, but then also seeing the potential for what AI can do, where do you put yourself on that spectrum between AI enthusiast and AI skeptic—you can name the endpoints on that spectrum with other terms if you prefer—but how do you describe how you like to think about AI and your opinion of it?

Tori Miller Liu: [00:15:18] I don’t know if this is an option on this spectrum, but I’m probably an enthusiastic skeptic. I’m very pro-AI. Fundamentally, it can help us make better decisions and help us process and make use of really large sets of data that were not humanly possible for us to make any use of before. When it comes to diagnostic care in healthcare, or when it comes to helping us make decisions about an association—of all these proposals, which proposal helps us most meet this critical learning objective—those are all cases where it’s a ton of data, and it’s great for us to have AI as a tool. I’m very skeptical when it’s AI replacing human creativity. In a responsible AI world—and I hope we’re investing in implementing responsible AI—I think humans are responsible for providing oversight and context.

Tori Miller Liu: [00:16:21] I also think that my biases are probably against AI replacing human creativity. I have a background in the arts, so I don’t love when AI is replacing writing, film, audio, or images. Humans are best, still, at providing that level of creativity and ingenuity. But I am skeptical also for implementations, and that’s the role of information managers and data managers. I love that the Project Management Institute (PMI) talks about every AI project is also a data project. Every AI project needs someone who is curating and stewarding the data, and they are best as skeptics. You want them to be skeptical about the quality of the data; otherwise, they’re not really fulfilling the role on that project. I think having that healthy dose of skepticism around content quality, content accessibility, system interoperability is healthy when you’re trying to implement successful AI.

Celisa Steele: [00:17:19] There’s a lot of potential for AI to help organizations with what they’re trying to achieve. You’ve been throwing out some examples, which are great to think about—the potential ways that an organization might make use of AI. If you think about an organization that might still be on the sidelines, maybe dabbling a little bit in AI but not in any sort of systematic or full-fledged way in trying to explore what it might do, what do you see as the cost that comes with sitting on the sidelines and not trying to think about AI adoption at this point?

Tori Miller Liu: [00:17:58] There’s a part of me that feels like it’s so naive that people think that it’s even a choice of if. It’s a choice of when and how. You’re not delaying the decision or deciding we’re just not going to use AI. You’re just running the risk of inviting shadow AI into your organization. Your workforce is going to adopt the use of AI, whether you like it or not. Your members are going to adopt the use of AI. I even had a member a couple weeks ago that—and this wasn’t a bad thing; I’m not judging them for doing this—took one of our research papers and created an AI application to help them better understand the research. It was a really interesting dilemma. But that’s an example of shadow AI. And I don’t want to take us off course talking about how I managed that, but it’s going to happen whether or not you like it. Couple that with your vendors are already rolling out AI features, and, in some cases, they’re not giving IT leaders a choice in whether or not those AI features are exposed to users or not.

Tori Miller Liu: [00:18:53] The big point is you saying, “Well, we’re not ready for AI” is just you delaying the inevitable, and then the problem is, when you’re lacking direction and intentionality, there’s a cost for that. The cost is going to come first and foremost through an impact on employee satisfaction and member satisfaction, which is eventually going to trickle to market share. It’s essentially the equivalent of—let’s time-travel back to the mid-90s—if your association was saying, “Well, we’re not going to create a Web site.” Eventually, we all did, and you lost some market share while you were dragging your feet on creating a Web site. I think that’s going to repeat itself. We have been here before with Web sites, with social media. I don’t think, fundamentally, it’s all that different from historical scenarios.

Celisa Steele: [00:19:48] When you think about the next 12 to 24 months and you’re thinking about AIIM and AIIM’s future, what are the opportunities and the challenges—which may or may not be tied to AI and all that we’ve been talking about—what are those challenges and opportunities that you’re thinking about? And then also adding that lens of education and learning, how might that impact what you’re offering to the market in terms of your learning portfolio?

Tori Miller Liu: [00:20:17] Our biggest challenge right now is our research is showing that the practitioners themselves are changing, so we’re moving away from a lot of the traditional titles of records manager and document manager. The titles are all over the place. I have members who are engineers and developers now. And the organizations are also all over the place, so a lot of our members are no longer in legal or inside an insular, little records management team. They’re in the IT, marketing, or HR teams. That’s all to say the state of the practice is really changing. They’re being pulled into AI projects. We’re looking at what’s happening to the people that we serve and recognizing that they’re transforming from information managers to information leaders in the AI era.

Tori Miller Liu: [00:21:10] It’s a much different educational challenge to train someone on “Here are best practices in information governance and records management” to “Here is how we prepare you to sit at the table of an AI project and be that data logistician, that data steward.” A lot of our certification and education improvements and enhancements are wrapped around that. It started with us rolling out an AI certificate in the past 12 months, but it’s going to continue with how we update our certification exam, what new courses we introduce. It’s even impacted the education strategy that my staff has developed for 2026—to make sure that the education that we do is focused on how do you prepare that person for that seat at the table of an AI project.

Celisa Steele: [00:21:59] That’s great. It seems like you have a lot of clarity, despite the fact that there’s so much shifting and changing in the roles, but this idea of, okay, imagine this person at that table helping make decisions about those AI projects, that then allows you to step back and understand what education, what learning, what resources do they need to, and then you’re making those available. It sounds really smart and on target.

Tori Miller Liu: [00:22:21] I want that sound bite: “It sounds like you have a lot of clarity.” I can play it on repeat in the morning as morning affirmations. Because when you’re doing it, it feels like you’re swimming in chaos. So I need Celisa saying, “Sounds like you have a lot of clarity,” and I’ll just play that 30 times to make myself feel better.

Celisa Steele: [00:22:39] Great. Glad I could give you that.

Tori Miller Liu: [00:22:40] Thank you.

Celisa Steele: [00:22:42] Again, if we have organizations, wherever they might be in their AI journey at this point, but if there’s something they could do in the short term—next week, in the next seven days, or so—what is it that you would recommend that an organization do to help them get a little bit more AI-ready in that near term?

Tori Miller Liu: [00:23:04] I’ll keep it simple for folks because it’s so easy to get overwhelmed with all this nonsense. Challenge yourselves, if you haven’t already, to come up with one to three good use cases, focusing on complementing human potential and not replacing it. That would be step one. You could do that with your leadership team, with your board, whomever. The other big thing is—if you don’t already have an AI usage policy—do some research into that. Again, you can keep this really simple. I am firmly against comprehensive strategies and comprehensive policies around AI because it’s going to change, and it’s going to adapt. This technology is moving so quickly. If you’re investing 12 to 18 months in developing a strategy or developing a usage policy, it’s wasted effort. So keep it really simple. Challenge yourselves to put down the very basics of what you need to feel like you’re responsibly implementing AI and have that conversation with folks.

Tori Miller Liu: [00:24:07] I did, over the summer, work on a facilitation guide with Alex Mouw with Amazon and Thad Lurie with the American Geophysical Union (AGU), and it’s literally a conversation guide—this is how you have conversations with stakeholders, your board, and your staff about AI. You can download that. I’m happy to share it with folks. But there are also other resources out there. It’s really about having the conversations. And then, beyond that, once you have use cases identified, once you have the guardrails around how you want to approach AI, you can start thinking about AI maturity and readiness. And that comes with looking at the available data, looking at its quality, looking at its accessibility, and focusing on your staff. Do they have the data literacy and information literacy to advance your use cases, to make use of AI or automation to accomplish the goals? I always worry that still feels really complicated, but it’s not. You can talk to folks like me. It’s not as bad as you think it is.

Celisa Steele: [00:25:11] That conversation guide is an excellent resource, and we can make sure to make that available to listeners. I might be misremembering the number of points, but you also shared AIIM’s AI usage policy at some point, and it’s five points or something. It’s a very short thing.

Tori Miller Liu: [00:25:27] Yes, it’s so simple. We had to update it again. I just updated it with my staff four months ago because, even though it was only a year old, it was already out of date. This stuff is changing so rapidly.

Celisa Steele: [00:25:40] Just out of curiosity, do you remember what you tweaked, or what changed in the policy?

Tori Miller Liu: [00:25:44] Yes, before it was binary around…. When we first came up with it, it was really early days of ChatGPT. This was early 2023 when we were thinking about this, and we originally said, “We’re going to disclose any time we use AI.” That is not a sustainable task or a requirement of my staff because now it bleeds into the work. We don’t copy and paste AI. It’s really hard to distinguish how much of this was AI editing versus human authorship. It’s impossible. So that we removed. Unless we can confirm this is 85-percent AI—then we’ll probably disclose it.

Celisa Steele: [00:26:29] This is the Leading Learning Podcast, and so, when we have a guest on, it’s always fun, at least for me, to get to ask them how they tend to approach their own lifelong learning. Tori, do you have practices, habits, or resources that you like to use to help you continue to learn and grow?

Tori Miller Liu: [00:26:50] I like treating association management almost like a scientific or academic discipline. For me, that means that—even if we don’t have scientific journals for association management—I’m seeking out new research and thought leadership almost as a daily practice. That comes from ASAE Collaborate, Associations Now, CEO Update, Association Charrette, LinkedIn, anywhere where I can get it. And I find it interesting. For me, I’m too chaotic to say, “Oh, I’m going to spend an hour every day doing this.” It’s almost like every time I pick my phone up, I’m like, “Oh, let’s see what people are talking about now.” But I do it on a daily basis. And then, beyond that, I have challenged myself for the last three years to set one big educational goal, and sometimes that ends up in me getting a certificate in something. This year, I was focused on, specifically, executive leadership in uncertain times, which directed where I was spending my own professional development dollars. But, in prior years, I’ve gotten a certificate in objectives and key results. Last year, I got a certificate in facilitation. Those are the big goals that I like to set annually.

Celisa Steele: [00:28:06] We’ve covered a fair amount of ground in our time. If you were to point listeners to one specific thing—or two or three things—that we’ve touched on, what is it that you would hope they would walk away with from listening to this conversation?

Tori Miller Liu: [00:28:21] Three things. One, and probably the most important, is, for associations to continue to thrive, we have to focus on what makes us unique in the AI era, and that means human connections, human creativity, and human-generated content. First and foremost, focus on that, and then that can feed into what’s the appropriate use case for AI and all that good stuff. The second one is keep it simple with AI. Like I said, if you’re doing the usual governance stance where you’re spending 12 months developing strategies and plans, that’s not going to work. Keep it agile, but keep it responsible. And then remember that responsible AI starts with data and information literacy. You need to understand data to be able to be successful with AI but also to be responsible with AI.

Jeff Cobb: [00:29:15] We’re not done quite yet—stick around for a recap of this conversation with Tori Miller Liu.

Celisa Steele: [00:29:20] Check out the AIIM Web site, the AI conversation guide that Tori mentioned, and her profile on LinkedIn.

Jeff Cobb: [00:29:33] If you got value from this episode, please share it with a colleague or leave a rating and a review. Those help others find the show and support the work we’re doing with the Leading Learning Podcast.

Celisa Steele: [00:29:44] Tori did a very nice job of summarizing three key takeaways, so I won’t reiterate those. Instead I’ll say that I appreciated her reminder that AI efforts are really data efforts, and having access, governance, and a mindset of “good enough” quality for specific AI use cases are what are going to enable real results.

Jeff Cobb: [00:30:06] I’ll echo Tori’s skepticism around AI replacing human creativity. Like Tori, you and I have backgrounds in the arts, and I’d prefer for songs and poems to remain human. So I appreciated her suggestion of picking one to three practical use cases where AI augments and doesn’t replace people, doing something with them, and learning from them.

Celisa Steele: [00:30:31] Thanks again for listening—and see you next time on the Leading Learning Podcast.

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The post Responsible, Pragmatic AI with Tori Miller Liu appeared first on Leading Learning.

Artificial intelligence often magnifies what’s already happening in an organization. If your metadata is a mess, an AI recommendation engine might help you give prospective customers recommendations faster, but those recommendations aren’t likely to be effective.

In this episode of the Leading Learning Podcast, co-hosts Celisa Steele and Jeff Cobb place AI in the Learning Business Maturity Model to help you pick the next move for where your learning business is. While AI can’t fix an immature learning business, used thoughtfully, AI can help a learning business on its path to greater maturity.

To tune in, listen below. To make sure you catch all future episodes, be sure to subscribe on Apple Podcasts, Spotify, or wherever you listen to podcasts.

Download a PDF transcript of this episode’s audio.

Celisa Steele: [00:00:03] If you want to grow the reach, revenue, and impact of your learning business, you’re in the right place. I’m Celisa Steele.

Jeff Cobb: [00:00:10] I’m Jeff Cobb, and this is the Leading Learning Podcast.

Celisa Steele: [00:00:17] Dr. Philippa Hardman, AKA Dr. Phil, has said of AI, “If early 2025 was the age of rapid adoption [for learning], late 2025 is looking like the age of constructive AI pessimism….” And I feel like “constructive pessimism” does describe what we’re seeing with learning businesses.

Jeff Cobb: [00:00:37] Yes, we do seem to be past any artificial-intelligence-as-silver-bullet kind of thinking. And arguably we never should have been there. AI is a technology. It’s a tool that can be used for many things, and it can be used well or less well.

Celisa Steele: [00:00:52] Right, and AI often magnifies what’s already happening, what’s already in place. If your metadata is a mess or your catalog of courses is cluttered with offerings that should have been sunset years ago, then an AI recommendation engine might help you give prospective customers recommendations faster, but those recommendations won’t necessarily highlight the best path for the learners or result in any higher sales.

Jeff Cobb: [00:01:19] Today we want to talk about AI and its use in learning businesses by placing AI inside our Learning Business Maturity Model. We believe this can help you pick the next move for where your learning business is.

Celisa Steele: [00:01:34] AI is not going to fix an immature learning business, but AI, used thoughtfully, can help a learning business on its path to greater maturity.

Jeff Cobb: [00:01:43] So here’s what we’d like to do in this episode. First, we’ll offer a short Learning Business Maturity Model refresher with stage-by-stage AI plays mixed in.

Celisa Steele: [00:01:54] Then we’re going to look at base requirements that you’ll need to address before making progress with AI, and we’ll talk about a few pitfalls to watch out for.

Jeff Cobb: [00:02:04] We’ll close with immediate steps you can take plus a rolling plan for the next 60 to 90 days.

Celisa Steele: [00:02:11] So let’s talk about the Learning Business Maturity Model as a quick refresher. This encompasses four stages of maturity across five domains. The stages are Static, Reactive, Proactive, and, ultimately, Innovative. The domains covered are Leadership, Strategy, Capacity, Portfolio, and Marketing. AI shows up in all five of those domains, and the use of AI influences how mature a learning business is, whether it’s stuck in that Static stage or whether it’s able to advance to the Innovative stage.

Jeff Cobb: [00:02:49] We’ll offer some quick descriptions of the stages. Just hearing these may help you self-place while you listen, but we also have an assessment that you can take to gauge your learning business’s maturity.

Celisa Steele: [00:03:02] We do. Be sure to check out the show notes. There you’ll be able to get access to fuller descriptions of the stages and the domains. And you’ll also be able to find out how to access that self-assessment that Jeff just mentioned. But, for now, we’ll do short descriptions.

Jeff Cobb: [00:03:21] The first is Static. The static learning business primarily maintains past practices, with limited response to changing learner needs or market conditions. At this stage, processes may not be strategically aligned to the changes occurring in your market. Growth efforts tend to be ad hoc, and opportunities for innovation, operational improvement, and learner engagement may be flat out overlooked.

Celisa Steele: [00:03:48] That’s the first stage. The next stage is Reactive. A reactive learning business is actively responding to market conditions, but it’s often doing so in a short-term, tactical way rather than thinking long-range strategy. At this stage, organizations may meet immediate needs and do that fairly effectively, but they may struggle to proactively shape offerings, build long-term relationships, or consistently align what they’re offering in terms of learning with their broader strategic goals.

Jeff Cobb: [00:04:22] At the next stage, a proactive learning business has shifted away from primarily reacting to market conditions and moved toward a more deliberate and strategic approach to managing and growing programs and services. At this stage, an organization has already established fundamental processes and is optimizing its offerings with foresight, innovation, and efficiency.

Celisa Steele: [00:04:46] And then the fourth and final stage is the Innovative stage. Once you have an innovative learning business, this organization is really leading. It’s setting trends. It’s continuously innovating, evolving to meet learner and market needs. At this stage, the organization has a strong foundation of processes, and it’s actively shaping the field or profession or industry that it serves through its offerings, strategic foresight, and collaborative ecosystem, where it’s trying to position learning as a core driver of growth and impact. Keep those stages in mind as we now talk about how AI use might look at each of those stages.

Celisa Steele: [00:05:35] At the Static stage, AI tends to be used, if it’s used at all, in isolated instances, and it’s primarily used to solve immediate problems rather than being part of a broader, longer-term strategy. We’ve got sporadic AI adoption—no real, clear strategy or integration into the core functions of the learning business. Maybe AI is used to address surface-level issues, but it’s not being used to drive more fundamental business operations or transformation. And even though AI might be providing some data or helping a learning business to assess a situation, decision-making is still largely manual. AI data might be one input along with others.

Jeff Cobb: [00:06:22] All of this means that AI tools operate in silos, which is characteristic of static learning businesses in general. Those AI tools are being added to the silos, and that leads to inconsistent results. There’s a lack of AI expertise among staff, and that results in suboptimal implementation. And there is no long-term AI adoption roadmap.

Celisa Steele: [00:06:44] In terms of what AI might be doing in a static learning business, it might be doing things like automating transcription. If you have recorded educational sessions, Webinars, or instructor-led online classes, you might be using a tool—if you’re at this Static stage—to capture what’s being said, create automatic AI-driven transcripts. Possibly you might also be making use of something like a chatbot to help with customer service inquiries, but odds are, if you’re doing that, it’s probably more internally focused and used rather than being something you forefront for any of your customers or learners. You might have some data analytics and data dashboards that are offering some AI-generated insights. Maybe you’re also making use of AI to help with some aspects of content curation. Maybe it’s helping suggest tags for learning materials, for example, and so you’re getting some auto-tagging happening.

Jeff Cobb: [00:07:42] Celisa, you were somewhat cautious in saying “might” before you went through that list of potential uses. Call me cynical if you want, but I think that most static learning businesses aren’t doing much more than that automated transcription. Maybe they’re using an AI-powered chatbot to help with customer service, but, in the case of learning businesses embedded in associations, for example, that bot is often owned and managed by another part of the association, like Membership. We know in general from our research—the data we got back last year and, so far, this year—that a lot of organizations are either not discussing AI at this point or are discussing it but have no clear plans for implementation. So far, that’s about half of the people responding to our research this year, and these static businesses are almost certainly going to fall in that 50 percent.

Celisa Steele: [00:08:37] You’re talking about research that we do on an annual basis to look at the learning business landscape. We’ve talked about that research in past episodes. We’ll definitely be talking about the data we’re gathering currently in a future episode, so stay tuned for more about that. And, yes, it’s absolutely worth pointing out that a static learning business may not be using AI at all. For a static learning business, AI use goes from zero up to what I mentioned. And most of those use cases that I was mentioning, even if they are in play, it’s probably largely because those AI features are baked into platforms that the organization is already using. Transcription of an online meeting might be because it’s easy to have an automated AI transcript created. Or, if you have data dashboards that you look at, the system behind that probably is making use of AI. It’s a little bit of a hidden use of AI. You might not even, as a static learning business, be totally aware of the use of AI.

Jeff Cobb: [00:09:43] So you’re not, in that case, probably fully benefiting from it. Part of becoming a more mature organization is becoming a more conscious organization and being intentional about having access to these tools and using them. To continue with AI in that static learning business context, a static learning business might have, as a goal, things like establishing guardrails and looking for one widespread efficiency win with AI if it is going to bring that AI in. To do that, you might do something like create a short, plain-language AI policy. Certainly a good thing for an organization to have at this point. Identify safe tools and make that list available to the relevant stakeholders. Offer some internal training—maybe something on prompt hygiene or a do/do-not session.

Jeff Cobb: [00:10:35] You might establish a dedicated AI working group or task force to explore AI applications. You could begin cleaning up your metadata. You mentioned metadata earlier, Celisa. You need good solid data to use with AI. It doesn’t have to be all your metadata but some. Clean up your titles, your summaries, your tags for your top products. Pick a number of them or a percentage of them that you’re going to tackle. You can begin tracking AI-generated insights on a more consistent and intentional basis for decision-making validation. And you might pilot AI-driven personalization in small-scale learning experiences. All aspirational things that a static learning business might want to try to strive for with AI.

Celisa Steele: [00:11:22] Yes, with all of these stages—from Static all the way up to Innovative—be thinking about how you’re going to measure and see what progress you’re making. Given what you were talking about, Jeff, at this point, at this stage, key performance indicators would be something like the percentage of staff trained on your AI policy, or you mentioned that do/do-not session. How many of your staff have attended a training like that? It might be that you’re looking at how we reduce response time if you deal with customer service inquiries about your learning products and services. Or we were talking about metadata—what percentage of your metadata has been verified and cleaned up?

Jeff Cobb: [00:12:08] A major message is, even at that Static level, just start engaging with AI at some level. Even if you’re not directly applying it to your learning programs or actively into how you’re running your learning business, just getting your staff, your volunteers experience with it. We’re big fans of Ethan Mollick, and he talks about needing to spend that initial ten hours with AI to get a feel for what it can do. That’s going to be a big step for a lot of organizations seeing the path beyond Static as a learning business. So that’s the Static level.

Jeff Cobb: [00:12:41] Let’s talk about the Reactive level, the next stage in the maturity model. At the Reactive stage, AI adoption expands, at least in theory, to improve efficiency and automate repetitive processes. AI becomes that operational enhancer.

Celisa Steele: [00:13:00] At the Reactive stage, AI might help with things like automating some administrative or operational tasks. Maybe there are some standard e-mail responses that need to go out. That’s the kind of thing that AI might help with. Maybe AI is taking a look at your learning analytics, and that’s helping you make some decisions about what you offer. Again, that’s probably, at this stage, still AI playing a role and not yet being a real core driver of decisions but making sure that the AI insights are included in what you’re thinking about. You’re probably beginning to have AI tools integrated into some of processes at this Reactive stage, but you’re probably not yet fully connecting those AI tools to all of your processes.

Jeff Cobb: [00:13:47] Some common uses, again, in a lot of cases, are going to be things that are baked into software and processes that organizations already have, but you may be becoming a little bit more intentional about it. You might have AI-driven recommendation engines that are suggesting content based on learner behavior. You might have AI-assisted LMS automation doing things like grading or feedback generation. AI-powered e-mail marketing personalization. Or basic AI-driven learning analytics to identify trends. Again, you might find all of these things already existing in platforms that you’re using, and you’re starting to take advantage of them.

Celisa Steele: [00:14:29] At this Reactive phase, to make a little bit more progress, a learning business might be trying to standardize what’s working. Where are they beginning to see some benefits from use of AI and AI tools? They might want to look at creating a roadmap that shows how the different AI-powered systems might feed into one another and become more integrated so that you’re better able to leverage the AI insights. You might begin to explore using AI for some adaptive learning. Is there a way that you can help personalize those learning experiences a bit based on what you know about the learner and the content that you have on hand? And then, certainly, a reactive learning business is going to be providing more training for staff. How can you help them get up to speed more fully on the tools that you already have in place specifically but also the general uses and possibilities of AI?

Jeff Cobb: [00:15:26] Some simple key performance indicators (KPIs) here—in addition to what we’ve already mentioned for Static—might include things like time to create your learning experiences. That might be the total time that’s required to create a particular learning experience, a number of hours. It also might be the length over time. Does it take one week, or does it take eight weeks to get something done? Has AI helped you to collapse that process? Or things like reduction of routine tasks. If you know it took ten steps to get something done before, and now you’re getting it done in six, that’s a gain.

Celisa Steele: [00:14:29] We’ve talked about what AI can look like in static learning businesses and then in reactive learning businesses. Now we’re going to talk about stage three, Proactive. At this stage, organizations have begun to embed AI into their strategic decision-making processes. AI is playing a role in things like program design, personalization, and even business strategy. You’re making use of predictive analytics to drive learner retention, to even inform curriculum adjustments. And you’re using automation, powered by AI, to help with marketing, operations, and learner engagement.

Jeff Cobb: [00:16:49] Yes, this Proactive stage is probably where AI really starts to sing, so to speak. When we hear about organizations that are at this point implementing AI in one way or another, and it’s showing up in our research, this is the type of role that AI is playing. Some common AI use cases are things like adaptive learning systems that tailor content dynamically to learner preferences. When we ask people how they’re going to use AI, being able to adapt to learners and provide that more personalized experience is always top of the list, and they’re starting to do it in this Proactive stage. Next would be AI-powered career path recommendations, based on skill gaps and industry trends. Another one would be predictive analytics that forecast learner retention. Are they going to be coming back? Course demand and pricing models even. AI-assisted instructional design, using it to do things like generate your first drafts of learning materials and even going beyond that in many cases—obviously looping in your subject matter experts in that process. Finally, AI-driven customer segmentation for targeted marketing strategies—making sure you’re reaching those right audiences, making them aware, driving conversion with them.

Celisa Steele: [00:18:05] And because AI is starting to sing in this phase, there are challenges or things to be aware of. I talked about constructive pessimism at the opening of the show. Being aware of some of the limitations or biases and making sure you’re addressing those. Thinking about ethics, bias, and compliance issues will be important at this phase because you are trying to rely on AI for some core and important things. You got to make sure that you’re doing that in an ethical way, that there’s not untoward bias in there, and that you are complying to whatever guidelines you need to comply to for your learning business. You want to make sure that the AI-generated insights are being used effectively for decision-making, that they’re not necessarily dictating the decision but that they’re being used to inform the decisions. Of course, there’s going to be some challenges to look at around scaling the solutions that you’re finding across your portfolio or throughout your learning business. This is about taking what’s been working and trying to institutionalize it and make sure that it is there and happening at scale.

Jeff Cobb: [00:19:17] To advance in this stage with AI—and remember, at this stage, we’re talking about organizations that are reaching the point of being conscious and intentional in how they’re thinking about their maturity and the different domains in it—you’re going to want to look at integrating AI across all five domains and measuring the outcomes you’re getting. You want to implement AI governance frameworks to ensure ethical AI use. You’re going to want to invest in deeper AI-driven learner analytics and experience mapping. You’re going to want to develop AI-powered business models, such as AI-generated courses or AI-enhanced credentialing programs or AI experiences themselves. It may be something more like a custom GPT becomes your course environment rather than the traditional course or credential.

Celisa Steele: [00:20:11] In terms of what you’re measuring at this stage in those key performance indicators, you might be looking at things like, “Is our use of AI changing our completion stats? Are we seeing more learners complete? Are we seeing the satisfaction of learners improve? Are we converting more of our prospects into learners who sign up for and complete a learning experience? Are we seeing changes in the time-to-certification or the time-to-competency?” Whatever you’re measuring there, but looking at what is the larger-scale impact of the use of AI?

Jeff Cobb: [00:20:45] So that’s that Proactive level. Finally, we get to the Innovative stage of the maturity model. To extend our metaphor, if AI is starting to sing in that proactive stage, this is where we start to hit four-part harmony. Things are really coming together here. In that Innovative stage, AI contributes to differentiation and, you guessed it, innovation. AI is central to business operations, product innovation, and competitive differentiation. At this point, you can use AI for things like autonomously identifying markets. You’ve given it the power to go out and do the research and find new opportunities for you. AI is going to be enhancing learner experiences through hyper-personalization, getting down to that individualized learning path that so many organizations are striving for right now. And then AI-driven insights are going to be used to continuously refine your business models and to drive your revenue growth.

Celisa Steele: [00:21:51] This could look like, in action, AI-generated course content that is adapting in real-time to learner progress. Back to your point about individualization, that course is responsive to what I, Celisa, am doing in that moment, and it’s adapting and giving me the just-right content for me. AI might be powering coaching or even mentoring systems. I don’t know how many folks out there are Duolingo users, but there’s the Lily video call feature now in Duolingo, and this is where you have on call someone who can respond in real time to you—an AI agent, but it’s someone to assist, to coach, to mentor in real time. You might be using AI-driven business intelligence to inform new product development. What products should you be developing, and what should those products look like? You’re leveraging AI to help with automating decision-making, especially lower-level, very clear decision-making, but also to help with the predictive modeling so that you’re not only making the right decision in the moment but you’re trying to think about, “In the future, where do we need to be, and what should we be doing now to make sure we’re in the right spot down the road?”

Jeff Cobb: [00:23:08] AI can easily take you through all sorts of scenario planning along those lines to play out what might happen with particular products and audiences. But, of course, this does come with challenges. You’re going to need to be able to do things like ensure that AI dependency doesn’t lead to a loss of human oversight. You need to keep humans in the equation there. You need to manage the risk of AI-driven automation errors. As you start to give up some control to AI, start to use AI agents more, you’ve got to have those mechanisms for checking for errors and then maintaining a balance between AI-driven efficiency and human-centric learning experiences. You’ve just got to keep the human in mind. You can’t create a learning experience that’s so efficient that it takes the inefficient human out of the equation.

Celisa Steele: [00:23:59] If you’re at this stage, if you’re an innovative learning business, to help advance your use of AI, you’re going to want to continue investing in AI research and AI development so that you can use that for ongoing innovation. You’re going to make sure that you have good policies in place that help govern your use of AI and help ensure that you’re using it in an ethical way, that you’re being as transparent as you need to be with stakeholders about how you’re using AI. And then you also want to be thinking about ecosystem partnerships and how can AI help you in extending your market influence and your reach through some of those partnerships. You might be doing scenario simulations for practice. You might be integrating some copilots with employers so that you are surfacing just-in-time resources. You might be leveraging those coaching experiences. There are a lot of ways at this point that AI use could play out once you’re at that Innovative stage.

Jeff Cobb: [00:25:01] And you want to continue to develop KPIs that are a match for this stage. Obviously, you can build on everything that we’ve talked about for the earlier stages. But you’re going to want to look to the percentage of revenue that’s coming from AI-enabled products as you start to introduce those products. You want to look at the renewal and the retention rates around those products and what AI is helping to drive. And you want to be able to measure demonstrable performance gains. If you’re starting to individualize those learning experiences, those pathways, what kind of performance gains is that resulting in? Of course, you’re going to want to use those in your forward-looking marketing.

Celisa Steele: [00:25:40] To summarize, the story of AI use in learning businesses moves from zero, if we want to start there…

Jeff Cobb: [00:25:47] …and we probably should start there because we know a lot of organizations are at zero right now.

Celisa Steele: [00:25:51] This is no conscious use of AI up to ad hoc use of AI, where it’s much more hit or miss or gets used sometimes but not by everyone. Then it moves to inconsistent use without clear goals at the less mature end. And then we’re moving towards much more consistent, embedded, strategic use of AI as we move towards the higher ends of maturity and up to that Innovative stage.

Jeff Cobb: [00:26:16] The movement is from initial engagement to experimentation to operational enhancement to strategic support to playing a real role in differentiation and innovation for your learning business.

Celisa Steele: [00:26:31] It’s important for us to acknowledge here that we don’t see doing nothing with AI as a viable option. Even if your learning business decides to do nothing with AI, AI still arrives. It’s going to be that curious (or rogue) staff person who’s going to be engaging in the use of AI. Or AI is going to be baked into some tool that you are already using. Again, it doesn’t seem viable to us to say, “We don’t use AI.”

Jeff Cobb: [00:27:02] No matter where your maturity is, you’re going to need to have some things in place if you’re going to take advantage of AI. There are some base requirements for any kind of AI use case that you might pursue.

Celisa Steele: [00:27:14] You want to have these prerequisites in place. First, you need that AI policy, and we advocate for being short and clear so that it’s the kind of thing that someone’s eyes don’t glaze over as they’re trying to read through it. You want it to be short and understandable. You want to cover what’s allowed, what’s off-limits. You want to have some rules around sensitive data. You want to make sure that there’s a path for a staff person who, if they want to do something that’s not covered by the policy, who do they go to to either request a special use or to potentially say, “Hey, I think we need to change this in the policy.” And you need to have a plan for revisiting that AI policy on a regular basis. It needs to be a short-time window given all that is happening with AI. We have a forthcoming episode where I talk with Tori Miller Liu, the CEO of AIIM, and they have a very short and sweet AI policy. It’s a good model in terms of having a handful of bullet points about how you can use AI. You’re going to want that AI policy. You’re going to also want a list of safe tools and let your folks know how to access those. What are the approved apps? Some of these might be embedded in systems that you’re already using.

Celisa Steele: [00:28:34] If it’s more of a freestanding AI, then you’re going to make sure that folks know how to access it and sign in and log in and specify any settings that they might need to use in the tool. For example, checking a box that says, “Hey, don’t share my data back with the company that’s creating the AI tool.” You’re going to want to make sure that you are clear on privacy and intellectual property and accessibility issues. What type of content is someone working in your learning business able to share with AI? What sort of consent, if any, do they need? What are the copyright issues? Those sorts of things. And then you’re going to have to have internal training. If you have this policy, if you have the safe tool list, you need to make sure that folks are aware of all of that. In that internal training, you might also get into some things like prompt basics and covering the intellectual property and the personally identifying information do and do-nots. There’s that, and then there’s also the data hygiene issue, which we’ve mentioned before—cleaning up your metadata, making sure that the inputs that AI is going to be using are accurate so that the AI then can make good recommendations because you know that what you’re feeding into it is accurate.

Jeff Cobb: [00:29:57] There are two realities that you always need to plan for. This goes back to being conscious and intentional. First, shadow AI. People are going to use unsanctioned tools unless you provide safe options. To go back to those policies and planning, make sure you’re providing those options. Second, ambient AI. As we’ve already alluded to, vendors are baking AI into the tools that you already own, so you’re probably using AI without necessarily being conscious and intentional about it. You want to raise that up to the conscious and intentional level. And your policy and your safe list should cover both the shadow AI scenario and the ambient AI situation.

Celisa Steele: [00:30:43] We’ll touch on a handful of common pitfalls, things to try to avoid as you’re going further with your use of AI in your learning business. First, doing nothing or the thinking you-can-do-nothing pitfall. We’ve already covered this, but basically doing nothing doesn’t seem viable. AI exists in your organization, so don’t think that you gain anything by not taking the time to create that AI policy and do the other things that we’re talking about.

Jeff Cobb: [00:31:11] Definitely. As much as we encourage people to experiment and to pilot, you need to watch out for what we call pilot purgatory—lots of tiny tests, but nothing gets scaled or institutionalized. This is very easy to fall into because, once you start playing with AI, it’s easy to leap from one thing to another. “Oh, it can do this, and, oh, it can do that.” But you have to be strategic and figure out what is the thing that we need it to do for us right now.

Celisa Steele: [00:31:37] Another pitfall to avoid is feature shopping when it comes to what you might be looking for from platform vendors. If you are in the market for a new technology system, it can be exciting to see those shiny features around AI that a particular platform offers. But what you need to be thinking about is what are we trying to achieve? What are the outcomes that we want? And then how do we get to those outcomes, which may or may not be through those shiny, exciting features? There might be a non-AI way to do it or a better way to do it with AI.

Jeff Cobb: [00:32:13] It’s the same thing that occurs repeatedly with technologies. We’ve seen it with learning management systems again and again over the years. You go after the shiny bells and whistles, and you forget about what are those outcomes you were trying to achieve. Another one is basically the garbage in/garbage out data rule. Anybody who’s used any form of AI, mainly the generative ChatGPT-/Claude-type models, knows that you have to be careful about what you feed into it, how you contextualize what you feed into it, or what comes out the other end can be junk or worse.

Celisa Steele: [00:32:50] The last pitfall that I’ll mention is you want to avoid taking a set-and-forget approach or trying to totally offload to AI. You need to make sure that you or someone on your team is reviewing what comes out of these AI tools, that you’re making sure to review for bias or other issues, and that you remain engaged in actively assessing what’s working, how it’s working.

Jeff Cobb: [00:33:17] It’s probably worth saying at least a word about the sequencing of getting AI into your learning business, and we’ll propose a simple order of operations for that. First, start with policy. Make sure you’ve got those policies in place. Second, data. Make sure you’ve got your data in order, anything that’s going to be fed into the AI, that you’ve got that cleaned up, that it is good data, that you know how you’re going to contextualize it going into the AI. Then do those pilots. We said be careful with those, but you do need to do them to get your footing and figure out what the next steps are going to be. Next, review the results that you’re getting. Then, and only then, move on to trying to scale the positive that you’ve achieved out of leveraging AI. And then possibly—and this is not always the end game, but it may be an end game, and it’s something you should definitely keep in mind—productize. If you come up with something as you’re implementing AI that does represent a product that can be put out to your marketplace, you want to be able to go there. Be clear about ownership and responsibility, like anything else you would ever implement. You want clear roles. You want clear measures. You want clear KPIs at each step.

Celisa Steele: [00:34:31] With AI, things move fast, which means plans can age fast. That means you probably want a relatively short window for your AI planning—maybe a 60- or 90-day window. We’re talking months, not years. You’re going to want to revisit any plans or policies that you put in place—maybe that’s even as frequently as on a monthly basis. Just a quick look to see, “Okay, do we need to refresh the scope of what we’re covering or any of the tools in our safe list?” Or “Has anything changed about how we feel about risk related to any of our use of AI?”

Jeff Cobb: [00:35:08] We haven’t used the term so much here, but it’s being serious about your AI governance. How are you managing AI through your organization over time?

Celisa Steele: [00:35:17] We said we would talk about some next steps, both in the shorter term and then the slightly longer term. In terms of what you might do this week, first is identify your learning business’s maturity. You can either use the quick descriptions of the stages that we offered or—and we would love for you to do this—take the online self-assessment that will allow you to see your maturity, both overall and in terms of the five domains covered by the maturity model: Leadership, Strategy, Capacity, Portfolio, and Marketing. Once you know where your maturity is overall and in terms of those domains, you want to pick what’s the domain where you might have the highest amount of leverage if you were to begin using AI or to use AI in a more conscious way in that domain.

Celisa Steele: [00:36:09] This might be where you’re seeing some of your biggest bottlenecks, or it might be the area where you see a promising opportunity. You could also aspire, in the next week, to set up a meeting where you’re going to run through potential use cases that will speak to that high-leverage domain. You’re going to want to get the right folks in the room, you’re going to want to generate some ideas and use cases that AI might help you with, and you’re going to want to then narrow it down to just one. As part of that group meeting, define a KPI of what it looks like to have achieved something meaningful with that use case. Again, you can figure out your maturity, and you could begin to put the mechanics in place of having a 60-minute use-case workshop—get that on the calendar with the right folks.

Jeff Cobb: [00:37:03] Once you’ve done that work, you can move into a rolling 60- to 90-day plan to run the pilot that you’ve sketched out. In the first month of that, you’re going to want to get your ducks in a row; make sure you’ve identified all the elements of the situation that you’re trying to improve upon. Go beyond those use cases to flesh out what is the situation here? How are we trying to change things? Whether that’s making something better or filling a gap, or something needs to be created that wasn’t there before. Make sure you’ve got all your data in order, cleaned up—anything that’s going to be used as part of this, whether it’s learner history or meta-tagging. Whatever the case is, get that data cleaned up, and then lock in on those KPIs that you’re going to use to measure the success of the pilot. In your second month or maybe beginning in that first month, you’re going to be running the pilot, going through the necessary motions, collecting the outcome data that you get from it to be able to compare against that baseline situation that you had defined. And make sure all along you’re documenting what you learn in the process.

Jeff Cobb: [00:38:06] Then sometime in month two going into month three, if it’s all working, then you start looking towards scaling. That may mean investing more in it, putting more resources against it. It may mean ramping up marketing and communication around it if you’re going to take it out to a marketplace at that point. Or, if things aren’t working, making that rapid and disciplined decision to sunset. But be sure to recycle what you have learned in the process of that pilot—that’s one of the main reasons for running pilots—and then take that back to any backlog ideas you have and start the process over again with a new pilot. Now, the guiding principle in all this—to borrow a phrase that Mike Moss, who’s the president of the Society for College and University Planning, used—is that you have permission to play. This is something his organization gives to staff and volunteers at SCUP. You’ve got that permission to play, but make sure you’re learning from that play and carrying those learnings forward.

Jeff Cobb: [00:39:11] We’ll wrap up in just a moment with a recap of what we’ve discussed in our look at AI’s place in the Learning Business Maturity Model.

Jeff Cobb: [00:39:34] If you enjoy the Leading Learning Podcast, please share this episode or another episode with a colleague or co-worker you feel would appreciate and get value from it.

Celisa Steele: [00:39:44] AI won’t magically fix an immature learning business, but AI, used thoughtfully, can help a learning business on its path to greater maturity, on that move from Static to Reactive to Proactive to Innovative.

Jeff Cobb: [00:39:57] AI can play a role in all five domains covered in the Learning Business Maturity Model: Leadership, Strategy, Portfolio, Marketing, and Capacity.

Celisa Steele: [00:40:07] We hope that thinking about AI within the context of the Learning Business Maturity Model will help you think about where AI might responsibly help you progress in the near term.

Jeff Cobb: [00:40:17] Give that question some thought on your own and with your team: Where can AI amplify your maturity in the next 30 to 90 days?

Celisa Steele: [00:40:26] Thanks again, and see you next time on the Leading Learning Podcast.

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Do you want your learning business to be more than a provider of programs, to truly operate as a learning-centric organization? This episode of the Leading Learning Podcast offers a real-world example of how to do just that.

Mike Moss, president of the Society for College and University Planning (SCUP), joins co-host Jeff Cobb to talk about how SCUP is reshaping itself around learning. They discuss revising bylaws and governance, deconstructing curriculum, experimenting with membership and communities of practice, and investing in staff and volunteer development. Mike also shares how SCUP balances revenue with risk-taking and why giving people permission to play and experiment is key to fostering curiosity and continuous improvement.

To tune in, listen below. To make sure you catch all future episodes, be sure to subscribe on Apple Podcasts, Spotify, or wherever you listen to podcasts.

Download a PDF transcript of this episode’s audio.

Celisa Steele: [00:00:03] If you want to grow the reach, revenue, and impact of your learning business, you’re in the right place. I’m Celisa Steele.

Jeff Cobb: [00:00:10] I’m Jeff Cobb, and this is the Leading Learning Podcast. 

Jeff Cobb: [00:00:16] Many organizations say they want to be learning-centric, but making that real requires structural change, cultural change, and a willingness to experiment. 

Celisa Steele: [00:00:26] Our guest in this episode, number 463, is Mike Moss, president of the Society for College and University Planning. Under Mike’s leadership, SCUP has intentionally restructured itself to operate as a learning-centric organization. 

Jeff Cobb: [00:00:40] In our conversation, Mike shares the journey SCUP has taken, from revising bylaws and governance to committing to staff professional development and giving permission to play. He talks about how the association is experimenting with curriculum, membership models, and communities of practice. 

Celisa Steele: [00:00:56] You and Mike also get into revenue and risk—how SCUP is balancing financial sustainability with its commitment to experimentation. 

Jeff Cobb: [00:01:05] That’s right, and Mike offers practical advice for leaders who want to start down the path toward becoming more learning-centric. 

Celisa Steele: [00:01:13] If you want inspiration for how to reimagine structure, culture, and revenue around learning, then you’ll want to listen with care and curiosity to this conversation with Mike Moss. 

Jeff Cobb: [00:01:29] Can you briefly describe SCUP and the focus of its work and then also how you came to lead it? 

Mike Moss: [00:01:36] Yes, certainly. SCUP is a professional association, so we’re 501(c)(3), and we are a community of practice focused on the integrated planning approach for higher education. The key component of that is this is a new mission statement. Being a community of practice is an intentional design statement in our mission, and being learning-centric and led through learning is an intentional outcome of that mission. This is all put into play with our strategic plan that launched in 2024. We are 4,000 strong as individuals, about 650 campuses with representation, and about half of our members are corporate or other non-campus entities who support both the built environment of learning as well as learning outcomes of students and student success. We have a nice, blended community of both for-profit, nonprofit, practitioner, and those of us that work on the adjacent side of higher ed. 

Jeff Cobb: [00:02:28] You and I have had a chance to talk at length before, and you’d made the point that SCUP didn’t just adopt that philosophy of being learning-centric. You reshaped the structure, the systems, the talent to make that real. Listeners here would probably love to know what that transformation looked like and what were the tough choices you had to make along the way. 

Mike Moss: [00:02:54] Thanks, Jeff. I think what I would offer to start is that, as you outlined in your question, it was a very intentional journey with structure, then systems, then talent. In doing that—to jump to the non-dramatic ending—it did not mean we had to completely replace and replenish talent. The talent was on the journey of creating a learning-centric structure with systems that support it. By the time we got to talent, it was more about our own professional development as an organization to continue the journey, not to reset the journey. In this community of practice commitment, it’s all about the standard practice of the learning-centric approach—do, reflect, do differently, at the very base level. We wanted to lead with curiosity and experimentation with the community-led learning initiatives. We do not have a credential; I think that’s an important piece to offer. We are a peer-based learning environment and always have been, but we were structured in a more traditional “Committee does this; committee does that; these volunteers are set for this.” It was a very hierarchical if not silo-driven operation, and it worked great. There was nothing dysfunctional about that environment other than we felt that the best way to move the association into the 2030s would be to start now, especially post-pandemic, with peer-driven learning. 

Mike Moss: [00:04:19] Learning is social. Social comes from all the different modalities. Take the modalities out, and it’s just about people doing, reflecting, and doing differently, with both comparable and aspirant peers and institutions. In order to structure that, we had to go back and change our bylaws. We had to give some agility and be agile in our governance to allow the peers in the community to define how they wanted the modalities of learning, what those topics were. We got really good at correlation, and we get the members to work really hard on causation. That balance is how we’ve become learning-centric in operation. The stated goal of this plan is that we will operate as a learning-centric organization. That is a strategic goal. We didn’t have a vote on it, Jeff. The organization decided this was where we were going, so that community of practice actually became the driver as much as any of the specific learning modalities that we put into place over the last year and a half. 

Jeff Cobb: [00:05:14] What was it about the old structure that was holding you back from where you saw you needed to go as an organization? Was it just a matter of giving more power to the people in a way? Or what happened there?

Mike Moss: [00:05:29] Great question. I do think it was as simple as, in the old governance structure, it said, “Name of committee, these types of roles, this charge,” but it was codified. In the governance, it was codified as to how we structured ourselves for a set of outcomes that were driven from that structure. What we wanted to do was not determine the structure. Let the peer community determine the structure. Obviously, the board has voice. We have a SCUP council, which is a group of volunteers who help us directionally on a year-to-year basis. But the fluidity of what’s needed, particularly in a high-volatile environment that we’re serving in higher education, things shift very quickly, and we didn’t want to end up having to sunset a committee, to create a committee, go through a governance process to be compliant with what we’re supposed to do to run when what we needed to do was allow the peer community to rise and fall with what they needed when they needed it in the modality that served them best. So it’s not unique. This isn’t an innovative practice. But, for us, it was innovative because before we were pretty scripted. 

Mike Moss: [00:06:30] We had a scripted set of outcomes that meant you did integrated planning. What we’ve decided to do with the approach is it is an approach; it is not a script. For that approach to find its enculturation on campuses where you can put in your own culture. If you want to be siloed, and if that works best for you, then go for it. But in the old scripted, it would say, “No, that is a failure to the discipline.” The approach works for what the culture of the campus requires, and that is going to be peer-driven on their campuses, so it should be peer-driven in the learning environment of the association that holds the approach. We flipped the script a little bit and said, “Let’s be really agile with this and see where the community wants to take it.” 

Jeff Cobb: [00:07:09] I want to come back to that culture question here in a minute. You mentioned earlier that part of this journey, part of the transformation was a professional development component to it for the talent, for the staff, and, I assume, the volunteers as well. What did that look like? What sort of professional development had to happen to support this kind of change? 

Mike Moss: [00:07:28] The first thing had to do with truth and facts. The fact is we stated truthfully that the professional development budget for staff is not going to be cut, regardless of what the world throws at us. We are committed to a dollar amount per person per year for three years, and it will not be touched. And, after the first year, when we had some financial duress and stayed firm on that commitment, it helped reinforce that cultural value now of do, reflect, do differently, and that requires professional development. We are committed to that budget component. What I would offer is that the only thing we did different than most associations that I’ve worked with in the past is we made the upfront commitment that, no matter what happens, you have professional development dollars for this year. Everything else we will figure out. We flipped that script. We were still service mindset—obviously, we weren’t going to cut things that hurt the service of the membership—but we were really committed to that talent training. What it looked like was a non-negotiable commitment, which it was. 

Mike Moss: [00:08:27] When the board and the management team committed to that, and the staff then saw what we were allowing, which was they’re going to tell us what they need training on, not us telling them that “Mike wants to run this committee structure; therefore, go learn this committee structure,” it was more like, “The organization and its peers require this,” let’s figure out how we want to run that through experimentation, curiosity. Let the curiosity drive your professional development, not some predetermined outcome, because we really don’t know what the outcome is going to be. We were managing a set of inputs for people’s training. The outputs being that they have ideation, and that ideation could drive the outcomes for the service requirements we have for members as opposed to having that predetermined destination. We wanted it to truly, in an agile, waterfall way, let it flow. And that’s some things, some of the experiments have been amazing, and some of them probably “Let’s let that one go and not talk about it again,” but we did it. 

Jeff Cobb: [00:09:27] What you were just talking about you’ve described as permission to play in SCUP, encouraging the staff and volunteers to do those sorts of experiments. As you just referenced, are there some examples of where that did not work, where it failed? And are there other places where you were surprised by how successful it was? 

Mike Moss: [00:09:45] Yes. I mentioned we didn’t have credentials. We still don’t have credentials, but we have curriculum. It’s not like the approach is completely as loosey-goosey as I may be implying. We have a curriculum by which we’ve done some great training for decades around the integrated planning approach. But, with what’s going on in higher ed, the speed of decision-making required, the talent investment we all have to make so quickly, we’ve deconstructed that. We took the curriculum, as many of us do, and we deconstructed it, and we decided to let member voice decide which components come up. In a four-day course, maybe you only truly need an hour of it because you’ve been tasked with “Jeff, go write a contingency plan for this scenario,” and that’s all the training you need. You’re not going to go pay for a four-day course. But, as we deconstructed it and then had the peers running the courses, they would share experiences on how they deconstructed their own immediate decision-making to that moment. Let them go talk that out. We formed working groups, and some of those working groups on paper, I’m like, “Oh my God, this is everything for SCUP,” and no one signed up. And then there are other ones that were like, “Man, that feels routine; that feels kind of like we didn’t try,” signed up with a waiting list. 

Mike Moss: [00:11:00] We learned quickly that our assumptions based on past learning performance at the organization did not apply to current situations for our members’ needs. The investment cost was low; it’s not zero—there’s time that staff put into it, that volunteers put into it—but it’s a quick rise and a quick fall. That one working group that we spun up, and no one signed up for, we could spin it down quickly. It was time lost on the calendar, but not months. It was a matter of weeks. So we’re trying to get into that cadence of rise quick, fail quick, all those normal things that we do in project management, but doing it at scale and being driven by the members’ voice, not our metrics of how we used to measure learning success. Now, at least one person’s already shook their head and said, “But, Mike, you have to make revenue.” Yes, we have to make revenue. That’s also part of our operational equation. That doesn’t necessarily mean that’s the driver for all things that we’re testing. 

Mike Moss: [00:11:59] Some things that we’re testing truly go to that whole mysterious box of the undefined member value that they know about that they haven’t told you about. And we are thinking that the successful ones, even if it’s not a financial success, the learning that we get out of that has driven communities of practice that have been formed naturally by the members that we never would have imagined would have been on our radar. The staff, data, and the staff experiences would not have said that was going to happen. The lesson I’ve learned the most, which is probably something I should have learned decades ago, is get out of the way. A lot of our curriculum-based education in the past was very well done. But, in the current higher education needs, we needed to get out of the learners’ way and let them deconstruct it, reconstruct it so that they could solve the problems that were on their campus that we didn’t have exposure to but yet our discipline can help them with. 

Jeff Cobb: [00:12:51] I want to make sure we come back in a minute to the question you raised around revenue, and pricing can be tied to that as well. But, before we get there, you, internally as an organization, had to change a lot and rethink things and change the way that you were doing work. What’s your sense of how your members then experienced that? Was it a change in culture for them? Do they perceive more value from the organization? And how do you know? 

Mike Moss: [00:13:24] We’re still learning that, honestly. The experimentations that we’ve done at conferences would be the most obvious because they have the largest single-moment impact. And so reprogramming how we structure the flow of the conference, introducing active learning versus the more traditional session-session-lunch-session,-session-dinner formats, and trying to experiment a little bit more with active learning but bringing in the social aspect—those things we’ve had immediate reaction to because it’s a large event in a point in time, easily measured. The harder things to measure have been these things where every other week there’s a community of practice call, there’s an emerging leader program that has monthly calls, but those take a minute to find their pulse each year, each cohort. It’s been harder for us to say that all of those have been great or none of them have been great. But all of them have been active. 

Mike Moss: [00:14:11] What we’re tracking is that there’s a more active voice among our members now that we can see in social media. Is that a metric of success? I don’t know, but at least we’re being talked about differently and talked about more collectively as a learning entity as opposed to a modality or a mode entity. It’s great that you mentioned our conference. What’s better is that you mentioned all the amazing things that you met and had happen at that conference. It happened to be a conference. It could have been a virtual Webinar. It could have been a working group. It could have been a coffee shop meeting. We’re having local meetings now; for us, that’s new. We don’t have chapters, but, all of a sudden, we’ve got these local things spinning up by members serving members. Those are the metrics we’re watching. It’s too soon to answer that question definitively, but we can definitely see a new behavior in a set of our members that we were hoping for, but we aren’t quite sure how to capture that for scale yet. 

Jeff Cobb: [00:15:06] If I’m listening to this as your average listener, I’m probably thinking, “This sounds great. This sounds very dynamic. This sounds like what learning should be. But it also sounds a little bit messy.” When I’m thinking about neatly monetizing education, it’s nice to have courses and conferences and curriculum that you can just put a price tag on and say, “Pay this, and you get this.” It’s a little messier to think about a community of practice. How do you approach the monetization of this? How do you think about factors like pricing in your world? 

Mike Moss: [00:15:39] That’s the everything question. We have six conferences a year. We believe we’re already at a price threshold, and have been for a while, so the price is what it is, and we all know that the operating costs for all these things are going up. We are also mindful of how we can schedule those to make sure that we can at least get close to maximum capacity for the nets that we require. We are anchored by that traditional practice of having these six conferences. We also still have, as I mentioned, that curriculum with a set of courses. Those are still running, but they’re running a lot less frequently because the demand has dropped for having people out of office for three and four days at a time. The market has said, for what they’re dealing with on campuses right now, that may not be the best opportunity for them to leave and then come back. This deconstructing is allowing us to come to them. The monetization of coming to them largely is virtual, and, as we all learned in the pandemic, we can scale those prices accordingly. Our operating costs are lower, but the frequency that we have to run those is higher. That experimentation about do, reflect, do differently is not just about the curriculum. It’s about the curriculum, the user experience, and also the revenue—what’s the net? 

Mike Moss: [00:16:52] What we’ve experimented with in the last six months is taking some of them and making them free to members, and that’s it; nobody else can participate. All that normal A/B testing that you do—other ones that are fee-based for everyone, some that are this, that, and the other thing. Having those A/B tests across those come-to-you moments has helped us find a price range that keeps things in a net, but we aren’t quite at the frequency we want to be at yet to hit the fiscal year goals. So we’re on a path. It’s not going to be a hockey stick moment. I don’t think those happen very often anymore in life—the huge spike in revenue—but we are consistently growing the revenue. More importantly, we’re consistently maintaining an audience. And it’s not just the same 10 people. There’s a consistency of the level of service we’re providing on campus, meaning that type of role on a campus is showing up more frequently. Now it’s on us to figure out how we convert them from a learning moment to a participation moment. Because, to your point, the community of practice comes from it’s not the same 10 people running the courses all the time. That’s what courses are for. The community of practice that we’re monetizing is that more and more peers are willing to participate, share experiences, and it scales from that growth, which is much more organic and in a much lower net than we’re going to get off of a set of courses. The frequency question has to be answered still as we go into the next year. 

Jeff Cobb: [00:18:21] Is the community of practice approach separate from membership, or has any of this impacted your membership structure and fees at all? Or is it separate from that? 

Mike Moss: [00:18:32] Never one to not be curious, so I love my staff because they’re just as curious as I am. We also are experimenting with a new membership model. We are working on lowering the cost of entry so that we can improve the ability for access to the learning. Because the whole point of the community of practice is not to have a membership community; it’s to have a learning community of practice. Last year we built community by putting programming in place that helped people find their comparables and aspirants in a comfortable environment where they could share. This year, ’25 into ’26, we’re building the learning around that group of peers because that’s the goal: peer-based learning. What we’re doing on the membership side is that, in order to allow that to happen, you can’t spend 50 percent of your PD budget just to get in. You need to be able to have that money available for the experiences of the learning, not just the access to learning. So we’re lowering the paywall. And it’s an experiment. 

Mike Moss: [00:19:30] On our Web site, it’s still very much the same model you’ve seen for decades at SCUP, but, on phone call recruitment and pilot, we have others joining in this new model, which is a much lower cost with much higher access. So we’re running an A/B test on the membership model. A lot of our members prefer the traditional model, and others are experimenting with this new approach, where it’s a learning community of practice that they’re investing in, not a membership in an association. It may sound like semantics, but it’s two completely different programs. Over the next couple of years, we’re going to keep running this experiment and see which of those levers gets pulled the best by the industry, and we’re hoping it moves towards the community of practice more so than the traditional enrollment model that we’ve had for 60 years at SCUP. 

Jeff Cobb: [00:20:17] It occurs to me, behind all of this, you must have a pretty forward-looking board that you’re working with. A lot of boards would resist this kind of thing happening in an organization. How has this been in conversations with your board? 

Mike Moss: [00:20:32] Obviously, I wouldn’t be talking openly on a podcast if this wasn’t supported. This was a part of the strategic journey that the board had put together when they assembled the strategic plan that launched in 2024, and it was mostly born from the experiences that we had as an organization during the pandemic and the few years leading into the pandemic. We had made a commitment in 2018 to become learning-centric. We didn’t codify it into a plan until 2024 because of the pandemic. But, at that point, because of how we learned about how our community responded to volatile times, we needed to codify it so that it is in writing—this is the direction we’re going.

Mike Moss: [00:21:11] The board has been super supportive through several election iterations. And that’s the other piece—I’m never going to undersell how lucky and supported I am by an election process that continues to bring in board members who support and modify. We always are adjusting but modifying a strategic direction and not taking a 180 on it because it’s hard or because it’s a bad numbers year. The board has been very supportive of, to support higher education, we also have to be learning-centric. That is what we ask of them—to serve our students. And so that mindset that the board has, they’ve maintained that themselves. They run the governance. We’re a slate process, so there’s a governance selection committee that does the slate for election every year for board members. It’s attribute-driven. Those attributes keep getting reinforced and adjusted as the strategic direction moves forward by the board. So, to your point, the process by which the board was assembled, and the process that they’re maintaining to stay strategic—their goal is to stay three years out on their work—has reinforced the opportunity for us operationally to do this experimentation. 

Jeff Cobb: [00:22:18] One of the points you mentioned in an earlier conversation I had with you is moving SCUP towards what you characterize as a relational matrix in how it operates. I think some of that’s embedded in what you’ve talked about already. But can you talk a little bit more about what you mean by that and how that plays out for SCUP? 

Mike Moss: [00:22:36] The more appropriate way to describe it, probably than I did in the past, is that we’re a branded house. We’re SCUP; this is what we do; here’s who we serve. By 2030, we want to be in a house of brands. It doesn’t mean that we’re all under a brand, like a holding company. There are a million ways to do this; there are a bunch of examples out there in the market. This is not innovative; it’ll just be different for SCUP. But what we had imagined in this house of brands is that we all have our independent brand. We have our reasons for being. We have our missions. But we are absolutely interconnected on how we deliver to the campus for student success. In order to do that, it’s not just a random selection of X number of brands to do this—the relational matrix. It’s driven by all of our missions that have that interconnectedness and serve each other’s mission. For simplicity’s sake, if each association is a LEGO, they all fit; they fit the right way at the right time, to come to a campus. 

Mike Moss: [00:23:32] The other part of what we want to do in this house of brands is that it’s not meant to compete with our consultant members. We can’t do our work without our consultant members. This isn’t an either/or; it’s an and. And, with the good work that they do, we can start coming to campuses in this house of brands to really go deep into the enculturation of each discipline that’s represented for hopefully getting out of “new president, new plan,” out of personality-based driven outcomes and helping to do what we all have pledged to do, which is create sustainable systems for student success on campus. In order to do that, we’re imagining a different time here soon, where, if you’re not coming to the campus in this consortium mindset to solve the problems, they’re not going to be able to come to seven different conferences to get that same information. That’s what we’re working through. And it’s partnership. It’s coalition building. There are a million ways to do it. But what we hope for, as a planning entity, is that we’re horizontal to all these vertical disciplines that are important. How can we help connect that into this relational matrix that comes to campuses and helps embed practices for student success? 

Jeff Cobb: [00:24:40] You’ve made the point before that associations need resilience right now. There are a lot of stresses on the system. And even things like mergers and closures should be on the table; there are sectors where there are just too many associations serving that sector. For you, what does association resilience look like in practice, and what do boards and leaders need to be thinking about now and dealing with now about what the 2030s are going to look like? 

Mike Moss: [00:25:07] We’re constantly contingency and scenario planning. What we have to be honest about is—as much as we feel like we’re on solid footing now and as much as our reserves and all the key metrics that we have as associations would say, “We’re going to be fine for a minute”—don’t count on that. The external factors that are facing us now are materially different than they were five years ago, if not five months ago. Depending on what industry you’re in, there’s a lot going on. We are constantly looking at that. We’re planning. What happens if we’re approached? We shouldn’t be surprised if we’re approached. We also shouldn’t be surprising people if we approach disciplines that make the integrated planning approach stronger. Data is a huge part of what we do, but we rely on others for that now; maybe we should bring that inside. We’re constantly having those planning exercises where we’re like, “What would it look like for X, Y, and Z to approach us? And what would be the causation for us to say, ‘Yes, let’s have that conversation’?” So being prepared for the conversations and planning, but not as a plan. 

Mike Moss: [00:26:06] Right now, transparently, SCUP does not have a merger plan or an acquisition plan, but we have scenarios by which we would entertain having those conversations. That’s something that we keep in the forward part of our internal and board-level conversations, that proverbial “What if?” What if we do need to consolidate? What if the three conferences that feed us best go away because of external factors we can’t control? I don’t know if that’s a very good answer to your question because the answer was planning, planning, plan, plan. But I do think there’s an exercise in there for every association to be prepared. I don’t know anybody who’s in such a place of comfort that they shouldn’t be having some version of those conversations. But I would hope that anybody at any level of the association, even on a team-based conversation…. If I’m running a team—I used to be a product manager—I would be having conversations with my team. “What if they decide not to run our product? What can we still offer the association? What skillsets do we need to go get training on so that we still provide value to what’s still here?” Really making it org-down conversations—what if?

Jeff Cobb: [00:27:20] You’re obviously very much walking the walk as a learning-centric organization—it’s what you represent. My view is that associations can/should play such critical role in lifelong learning, as the organizations that tend to stay with people throughout their careers. What’s your perspective on the association role in lifelong learning? What role do associations need to be playing, and what do they potentially risk if they’re not playing that role going forward? 

Mike Moss: [00:27:53] Everything you said I strongly support. I think associations are not in our last 50 years of existence. In fact, we’re probably just now figuring out what the next 50 years mean for us. I do think associations are absolutely at the center of education and professional development, and all the things that we’ve said for the last 100 years are more important now. What we didn’t have when we were founded 60 years ago, for example, at SCUP was this technology hockey stick, and technology really is on that hockey stick evolution. Every three months, there’s a year’s worth of AI development or some crazy thing like that. Moore’s Law feels slow now. All those things. And, as we look at those moments, the association community is more powerful than ever to bring people together to have the shared experience of what it means to be a learner. Obviously, I represent higher education. I’m also fortunate enough to have a bachelor’s degree. Many of my colleagues have master’s and beyond. But I also realize that there’s a huge part of my personal life community that was best served by not going to college, and I know a lot of them are getting their professional development for whatever they’ve chosen to do through associations. Sometimes they don’t even know it was an association that they got it from. 

Mike Moss: [00:29:05] There’s an opportunity for us to not just be branded and remind people that “Hey, that association got you that job,” but that we’re available at a community level. It’s what we can do better, I think, as associations and other constructs that exist. We can be at the community level of service with formal education, with formal for-profit business. We are that connective tissue that keeps a community viable. Whether you call it workforce development or professional development, associations are in the mix of all that. What we might need to do differently is get a little more comfortable with being interconnected and not independent. The crowded spaces often are that there are 42 ways in that industry to do something, so there are 42 verticals to support it in the association space. It goes back to your previous question. We may have to configure ourselves a little differently to still support all 42 of those paths, and it may not be all 42 independent associations. But that association structure, the nonprofit service that we can bring in, we need it more now than ever. And because of the speed of change, people need a place with connective tissue. And associations connect the speed of change with opportunity. That’s where we can do some amazing work moving forward. 

Jeff Cobb: [00:30:23] What would you say to an association CEO, a peer leader, who is still looking at learning as just a product line of the association, as one function siloed there? What’s the danger of that at this point from your perspective? 

Mike Moss: [00:30:42] As soon as the community shifts to a different learning modality, they won’t remember your name. I don’t mean to sound harsh on that, but I’ve experienced that in my career, where another competitor came in with a better way to be up to speed, and no one remembered the association’s name. To do that is not wrong, but to do that in the absence of exploring and being curious about what’s next is your risk. Running a credential that’s run for 100 years the same way and is still working, why would you stop? But you definitely have thought about “What if I had to stop?” That’s the risk—that you become too comfortable with taking last year’s budget and adding 10 percent. I don’t think we should be doing that sort of thinking anymore is what I would advocate. 

Jeff Cobb: [00:31:27] If you could give listeners one practical step that they could make in their organization to make it more learning-centric tomorrow, next week, what would that be? How do you get started with this? 

Mike Moss: [00:31:41] It’s permission to play, as you said earlier, Jeff. And, in that permission to play, don’t count on trust. Trust will be the outcome of what you’ve done. It’s not going to be the input that makes it happen. What will make the permission to play happen is facts, and the fact is, when someone messes up, what is going to be different about their “mess-up” than it was in the past? How do you reinforce the learning moment in that versus the corrective moment? Hopefully, if we do our little sprints that we do here, sometimes they lose money, but they’re not losing a million dollars. There’s calculated risk, and there’s scaled risk. But you give the permission throughout the organization to take those scaled risks as a learning moment, not as an immediate corrective action—“Where are you going to get the money next?”

Mike Moss: [00:32:25] The trust that builds up is born from those facts of “Oh, I got to do this, and I got to learn from it, and I got to do it differently.” As they have that experience with you in leadership of being allowed to be curious, being then given permission to try something different, and then being given the empowerment of learning from it, it starts to take care of itself where then the risk is “Oh my God, there are 17 experiments going on at once.” The scaled risk of everybody being empowered is a risk that I think we should all embrace and see what the outcomes are. I don’t want to oversell it—SCUP’s on a journey too. We’re two years into this. It’s going well now, but external factors can kick in tomorrow that we have to make adjustments on. But what we now have is the permission to make adjustments and not have to make corrections. That’s a huge difference that’s come out of this learning-centric approach. It’s about making adjustments, not transformations. 

Jeff Cobb: [00:33:21] As we’re wrapping up here, I’ll switch gears a little bit but still staying learner- and learning-centric, talking about you as a learner. I like to take the chance when I can to ask guests about their own approaches to lifelong learning—your own habits and practices, maybe favorite resources that you rely on to make sure that you’re learning and evolving and can continue to get what you want to out of life. 

Mike Moss: [00:33:47] Probably not unironically, I listen to a ton of podcasts. I do listen to a lot within our association discipline, but I also listen to a lot that have nothing to do with either my profession or those I serve. I want to learn from all the industries to find those nuggets where I’m like, “Oh, I wonder if that would work with ours.” So a lot of podcasts. A voracious reader. All the things you would expect. But what I’ve learned the most in my learning journey was to give myself permission to do things differently because it didn’t often come from my boss. I do not advocate that anyone be disrespectful or any of that. I’m not asking you to go rogue. But what I learned to do better in my career was go do all that learning, do all that stuff, and then bring in a proposal. Don’t bring in a question. Instead of saying, “Hey, boss, is it okay if I do Lean?,” come in and go, “I think we can do this. Oh, by the way, it’s because you’re going to pay for me to be Lean certified” and getting it back into the application that our supervisors are always looking for, which, is how do we move our mission forward? 

Mike Moss: [00:34:45] That’s been my approach now for a very long time. And, so far, it’s not without mistakes, but I still think it’s a thing I would advocate for my own child to do, which is learn everywhere, but then apply it for the permission to play. Don’t just say, “Hey, I read all these books. I deserve a raise.” Prove it. There are probably some tough moments for all of us to learn when we do lifelong learning because the whole point is what I used to know no longer applies and accepting that has been something I’ve learned from colleagues like Lowell Aplebaum, friends like that in the business. They’ve really helped me understand that, “Yes, you used to be really good at that, but the key word is ‘used to.’ What are you doing differently now because things have changed?” Having that application of movement in learning is something that I’ve learned from my peers. That’s definitely helped me on my journey as well. 

Celisa Steele: [00:35:39] That wraps up our conversation with Mike Moss, president of the Society for College and University Planning. But stay with us another minute to catch our recap. 

Jeff Cobb: [00:35:48] On the SCUP Web site, you can find Mike’s phone number and an e-mail address if you want to reach out to him. 

Celisa Steele: [00:36:01] If you found this episode valuable, we’d be grateful if you’d share it. That helps more people find the show and benefit from it, and it supports the work that we do. 

Jeff Cobb: [00:36:10] In our conversation, Mike shared how SCUP is working to be truly learning-centric, changing its bylaws and governance, deconstructing curriculum, experimenting with membership, and supporting staff and volunteer development. 

Celisa Steele: [00:36:23] He emphasized the importance of curiosity and experimentation—giving people permission to play, learn from mistakes, and adjust. 

Jeff Cobb: [00:36:32] He also mentioned that associations and other learning businesses have to balance revenue with risk-taking and that learning should be more than a product line—it needs to be part of the culture. 

Celisa Steele: [00:36:43] Inspirational stuff if you ask me. Thanks for listening—see you next time on the Leading Learning Podcast. 

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The post Becoming a Learning-Centric Organization with Mike Moss appeared first on Leading Learning.

If you’re concerned about how your learning business can keep pace with rapid change—AI, growing risks, shifting learner expectations—this episode of the Leading Learning Podcast can help. Associations, credentialing bodies, and other learning businesses face mounting pressure to do fewer things of greater value, and success requires both courage and careful risk management.

Glenn Tecker, chair and co-CEO of Tecker International, joins co-host Jeff Cobb to talk about the forces reshaping continuing education and credentialing. They discuss how adaptive learning platforms are blurring the lines between education and assessment, why it’s essential to shift from an education mindset focused on information delivery to a learning mindset focused on application, the governance structures and culture of inquiry needed for innovation, the role of boards and staff in managing experimentation, and what it looks like to anticipate future competencies rather than react to the past.

To tune in, listen below. To make sure you catch all future episodes, be sure to subscribe on Apple Podcasts, Spotify, or wherever you listen to podcasts.

Download a PDF transcript of this episode’s audio.

Celisa Steele: [00:00:03] If you want to grow the reach, revenue, and impact of your learning business, you’re in the right place. I’m Celisa Steele.

Jeff Cobb: [00:00:10] I’m Jeff Cobb, and this is the Leading Learning Podcast.

Jeff Cobb: [00:00:16] Learning businesses are facing tremendous pressure to adapt. Technology, shifting learner expectations, and crowded markets are challenging the long-standing models of education, certification, and governance.

Celisa Steele: [00:00:29] Our guest in this episode, number 462, is Glenn Tecker, chair and co-CEO of Tecker International, a multinational consulting practice that has worked with associations around the world for more than 40 years, primarily on strategy. Glenn is also co-author of three textbooks published by ASAE (the American Society of Association Executives), and those textbooks are required reading for the CAE (Certified Association Executive) credential. And he’s a long-time advisor to association CEOs and boards.

Jeff Cobb: [00:01:01] Glenn and I talk about major forces he sees reshaping continuing education and credentialing—from adaptive learning platforms powered by AI to new security risks to the accelerating pace of change for knowledge and competencies.

Celisa Steele: [00:01:16] You and Glenn also dig into governance and culture and talk about why a culture of inquiry matters, what enables and blocks innovation, and how boards can be more effective partners to staff.

Jeff Cobb: [00:01:28] And Glenn emphasizes the role of risk management and experimentation, showing how organizations can move forward with confidence even in uncertain times.

Celisa Steele: [00:01:37] This conversation can help you, dear listener, develop a clearer picture of the forces shaping the future of learning in associations and other learning businesses. And that clearer picture can help you act more effectively.

Jeff Cobb: [00:01:56] Glenn, you’re somebody that I’ve wanted to talk to for a very long time now because of all that experience you have with organizations in the association world in areas like leadership and strategy. But, of course, my interest is primarily in learning. Serendipitously, I’d seen you weigh in on some learning topics recently, and I think we’ll be able to dive into a few of them here. Specifically, you had commented on a post in an ASAE forum, and the post was about AI and learning. You said, and I’ll quote you here, “The future of much adult learning will be adaptive, curated by AI, and integrated with peer and mentor interaction.” I agree completely, but I’m interested in what led you to that conclusion. What are you seeing that makes you feel like that is definitely the direction we’re going in?

Glenn Tecker: [00:02:48] The evolution of adaptive learning platforms, particularly with a kick from AI, is moving to the point where continuing education, assessment of the education, assessment of the learning, and provision of the credential are blending into a single place. The traditional barrier that existed between membership organizations who provided continuing ed and credentialing organizations who provided certificates and certifications is melting away. There’s law and procedure. ANSI [the American National Standards Institute] and a variety of other accrediting agencies still require a degree of insulation so that the politics and economics of a membership organization do not influence the delta weights, validity, and reliability of assessment methodologies, but technology is about to drive significant change in that area. What led us to understand that is we have been involved with adaptive learning technologies that are being used already, primarily by the medical community. A significant one is available for internal medicine. A significant one has been created, interestingly enough, by The New England Journal of Medicine, which is owned by the Massachusetts Medical Society—not a lot of people know that. It’s also being used in engineering.

Glenn Tecker: [00:04:15] What’s fascinating about it is that it recognizes that the wall that used to exist between teaching and learning has now come down. And, when you move from viewing what you do from teaching (the provision of information) to learning (access to information), the modalities that are available for learning and adaptive learning platforms are unlimited. It could send me to printed copy. It could send me to a simulation. It could send me to a group of mentors that would talk to me about an issue. It could send me to a project that a small community of learners would engage in. All of those things are possible. In the adaptive learning platform, what they’re also doing is assessing the preference of learning strategy that works for you. When it gets to the point where you’re having a difficulty, it will give the learner advice on which learning modality would work the best for them in that situation. What it also does is it has identified the fact that when people fail on something three times, they’re done. It never takes you back the third time to the same thing you failed on last time; it gives you another methodology to use so that you don’t click off.

Glenn Tecker: [00:05:38] That, along with the other two things that we’re seeing, one of which is the blending of AI and what’s often referred to as “quantum computing”—there are many names for it—is going to create major security issues for certification bodies because nothing will be secure. Not even blockchain and encryption will work. The third is the fact that the body of knowledge of most areas is progressing so rapidly, mainly because of AI but not only. What we are seeing is the need to figure out how to anticipate what the necessary skills, competencies, and understandings will be that may not show up in a traditional practice analysis, which looks at what people are doing now. It’s really the issue of how can you begin to think about how you will prepare for these circumstances?

Jeff Cobb: [00:06:42] We’ve been seeing something similar, and not necessarily AI-driven all the time, but those walls between the learning function and the credentialing function are getting harder to maintain because of the way that learning happens now and needs to happen now.

Glenn Tecker: [00:06:58] What’s interesting to us is the depth and breadth of potential assessment mechanisms that are available in the adaptive learning platform are superior to the scope of assessment mechanisms that tend to be available for most of the current credentialing programs.

Jeff Cobb: [00:07:20] Yes, that’s true. We want to have these neat little boxes—you do your learning here; you do your testing here—but it just doesn’t work as well that way anymore.

Glenn Tecker: [00:07:28] Yes, particularly if you’re moving to the ultimate level of learning. You move through what they need to know to what they need to understand to what they value and appreciate to the level of be-able-to. And, if you’re going to assess the level of be-able-to, you’re going to need some sort of application or simulation. That’s highly potential within the adaptive learning platform whereas, up to now, it’s only been possible if you’ve been face-to-face demonstration.

Jeff Cobb: [00:07:58] You’re not just speaking theoretically here, I know because you’ve had a platform in place for a number of years now, which you call Howspace.

Glenn Tecker: [00:08:07] We have been using it, yes. It is an online platform specifically designed for group work and decision-making. Its value is that it can be used synchronously and asynchronously. It also has the ability to engage in polling, assessment, and testing. It’s integrated into it. We use it now in face-to-face meetings, hybrid meetings, and fully virtual meetings. We’ve used it for strategic planning. We’ve used it for education. We have used it for a membership meeting. We’ve used it for what we call Critical Issue Summits. We’ve used it now with over 150 associations, not even counting our private sector clients. And we’ve been using it over three years. Every year it gets better.

Jeff Cobb: [00:09:00] How have you seen it change the trajectory of a group’s work when they’re using that as the basis for moving forward?

Glenn Tecker: [00:09:08] Good news and bad news. The good news is, in terms of engagement, we see it dramatically increased. Even when it’s entirely virtual, we will use Zoom, create small groups to do work together, and document their work and be able to interact with each other in the workspace. It essentially has gotten rid of flip charts forever. The second thing that we see is, sometimes in the asynchronous work, if we haven’t done a good job in moderating the conversation and focusing on critical content, we get a signal for that because the participation in the asynchronous work tends to reduce a little bit. We’ve learned how to pump that up still. The other thing that we see that’s of great value, particularly in virtual groups, [is that] participation using the workspace has made the experience and level of contribution of individuals, regardless of whether they are in the room or participating virtually, much more equal. An organization is able to get a much wider array of differentiated perspectives involved in the conversations and the thinking.

Jeff Cobb: [00:10:23] This requires a different mindset on the part of the learner and on the part of the facilitator, and maybe a little bit of a different skillset too, to really take advantage of working in this way.

Glenn Tecker: [00:10:34] What we’ve found is the skillset is pretty much already obtained by participants. If you use Facebook, if you use any of the social media platforms, even e-mail, then this is easy to use. It doesn’t require loading any application. You simply get an e-mail with a link, you click on it, and you’re there. We are finding more and more folks, particularly in the scientific communities but not only, completely comfortable with this kind of sharing of information. What’s different is the AI that is integrated into it, which is mostly but not entirely a large language model, allows for near-instant curation of the ideas that are being generated. It facilitates the group being able to build on and build from what they’ve already learned or what they’ve already been suggesting. Interestingly enough, this platform was originally created in Europe. It began in Finland. Its primary use in Europe is in companies who use it for ongoing continuing education targeted to the particular needs of their staff cohort. We’ve adapted it for our uses in associations, primarily with strategic planning and problem-solving.

Jeff Cobb: [00:11:59] If what you’re describing is the future—and I believe it is along with you—what does that look like for your average association who’s still basically relying on conferences and Webinars? They see that as what’s manageable, what’s easy, and what scales, but they need to shift in this direction. What does that look like, and what happens if they don’t, from your perspective?

Glenn Tecker: [00:12:22] If you are driven by revenue and not by learning, then the traditional online Webinars and traditional sit-in-a-room-and-listen, maybe with a Q&A, are probably going to be your best bet. If, however, you want to position yourself to continue to thrive in an environment where folks now are demonstrating less ability to find the dollars and the time to participate, then you’re going to need to move to more interactive programming and a commitment to folks actually learning rather than simply being exposed. What we know, for example, is that traditional online learning reaches the levels of awareness and understanding, but it never reaches the levels of be-able-to. If your learners are looking to be able to execute something as a result of the investment in what you’re providing, and you’re not giving that opportunity, they’re going to go somewhere else.

Jeff Cobb: [00:13:26] And you’re seeing it as a hard tradeoff from a revenue standpoint? Are there revenue models in your mind that would support this type of learning approach?

Glenn Tecker: [00:13:36] Yes, there are. The reason being the savings of online environment are not that greater than the savings of the use of this technology, which is far more interactive. Again, it can be used in face-to-face. We use it that way. It can be used in hybrid. It can be used in fully virtual. But this platform is not the only one that’s emerging. What I believe is that, in the future, most associations are going to have to do fewer things of greater value for more targeted groups of people. And, if that’s the case, then what we’re going to find is that their employers and their constituents are going to demand that investment of time and money, whatever it is, enable them to do something different or better—not that they can just go to the staff meeting and talk about what they learned about, but, in fact, they’re able to execute something well. People will take that risk when they previously had an opportunity to try their hand at executing it so that, when they are doing it for real, it’s not the first time they’ve done it. That’s a fundamental tenet of adult education as it’s been discussed for the last 25 years. Now there is an economic driver behind the need to attend to that.

Jeff Cobb: [00:15:10] How engaged are you seeing associations’ CEOs and boards with this sort of shift that’s happening? Do they really engage with learning as a strategic driver, in your experience?

Glenn Tecker: [00:15:22] I’ll draw a distinction now between the credentialing organizations and continuing education organizations. Unless the continuing education organization is what we call well heeled—it has substantial revenue and participation—it’s lagging. The credentialing organizations are either already moving in this direction or thinking seriously about it. That’s occurring at the governance level. My suspicion is that the membership organizations, which are primarily continuing ed and maybe offer certificates but not necessarily an accredited credential, are increasingly going to find board members—if they are composing their board members of individuals with some expertise in the business lines of the association and not political representatives of the various components of the organization—they’re going to find their boards asking questions along these lines, and their ability to provide alternative answers to those questions is what’s going to position them for success. “If this is the issue that the board is raising, then here are some of the alternatives. Here are the advantages and disadvantages of each alternative, and here’s the one that may work best for us.”

Glenn Tecker: [00:16:41] That provides the board with knowledgeable information upon which to make a decision that they can feel comfortable with. Some of these things some boards think are high-risk. The critical ingredient here is that staff provide a risk management process along with a commitment to experiment so that each step in the development of this new way of doing things is accompanied by a set of criteria that you have to get a yes to before you move to the next step so that, if it’s not working, you’re able either to abandon or to adapt before it becomes a sunk course. For staff being able to provide that—a laddered or sequenced risk management process—tends to allow governance to be willing to take the risk because they know if it’s not working, we’re going to get it early on, we’re either going to fix it, or we’re going to try something else.

Jeff Cobb: [00:17:47] What governance structures do you find either enable or block the adoption of these types of new approaches to anything? (But we’re talking about learning, obviously.)

Glenn Tecker: [00:17:56] What we are finding in common is increasingly a movement to ensure that, on the board, there are some individuals with experience and expertise in the business lines that the association is involved in—not necessarily instead of representation from the “owners” of the association, whether it’s chapters or components or multiple associations, but along with. What’s interesting to us is this is a metaphor for what for-profit companies have been doing for decades. On the for-profit boards on which I’ve served, we’ve got two kinds of directors. We’ve got inside directors, who are the staff and representatives of the major stockholder groups, and outside directors, who are there because they possess independent expertise in particular areas of importance to the organization. The differentiation in perspectives and experience creates a more holistic view of the possibilities and the challenges. Those are the boards that we find are most able, at the governance level, in consultation and partnership with staff, to engage in the three purposes of a board: to set direction, to establish strategy, to provide oversight, including making sure that the allocation of investments matches what it is they’re trying to accomplish in the strategy. That’s a trend we are seeing in composition in all three or four of those kinds of nonprofit organizations.

Glenn Tecker: [00:19:42] It’s a movement to creating a knowledge base so you can have additional confidence in the judgments that you’re making. We’re seeing some transition strategies being used. A lot of organizations do not understand that a board has the authority to invite anyone to participate in its meetings it wants to. Even if you’re using Robert’s, O. Garfield Jones, or Sturgis, the board has that authority. They can participate as equals in the conversation. You just can’t give them a vote. Having that kind of expertise available in the conversation is possible without necessarily fighting a bylaws change. Some groups are moving to do this either in policy or simply in practice. And then, once the organization becomes comfortable and enamored of what it enables decision-making to do, then it may move to memorialize it in a bylaws change. Now, associations have always asked advisors to come or contracted with consultants for particular activities. This is different because this is asking for an individual, like all board members, to stay apprised of the theme and direction. That’s strategic thoughtfulness. Strategy is about seeing patterns. Strategy is about looking at alternatives and being able to see the pros and cons in each, given what you anticipate current and future circumstances will be.

Glenn Tecker: [00:21:15] If you have someone who’s able to do that relative to the major business lines you’re involved in, particularly education because it is changing so rapidly and under such duress, it is essential. I say “under duress” because the primary problem that adult education is facing at the moment is too much. Literally, the field is saturated. There are so many alternatives of huge variance in terms of quality, price, and acceptance that the very choice of where to go is increasingly a question that people are asking Copilot, ChatGPT, or whatever AI system they are using. Now, what AI does here is, in those cases where you’re asked for recommendations, its choice tends to be based on what it harvests from that body of information based upon what’s there the most. Unfortunately, in the continuing ed area, most of the stuff there are promotions by people who are offering or selling it, so it has little to do with quality.

Glenn Tecker: [00:22:33] The last observation I would make in regard to this, we are seeing more and more not-for-profit organizations recognizing the value of distance learning as it’s been practiced by higher education for over a decade. If you are looking for the objective of your learning to be people not just being aware of and understanding but being able to, then what we are seeing and what our market research continues to affirm is that what most folks are looking for is access to learning that is affordable, that is reasonably accessible (online), but they also want to be able to spend time with their peers and with the experts from whom they are learning. In most cases, they would prefer that that time be face-to-face. If it cannot be face-to-face, then the technology of the distance learning classroom—which is a series of periodic gatherings with work that occurs during the gathering and in between the gatherings, executed by subgroups of the full group as an application of what they’ve learned from each other or the expertise—tends to be what most folks are looking for.

Jeff Cobb: [00:24:00] Yes, we’ve felt for years that there’s not been enough focus on cohort-based learning going on in the association world. As you’re saying, the academic world got that a long time ago, probably because it’s built off their traditional models so well, but they’ve gotten good at it. In many cases, we’re seeing that academic continuing education departments are booming right now. The rest of academia is under fire, but continuing education is doing great, and they’re in a position to eat the lunch of many associations in different markets.

Glenn Tecker: [00:24:30] Yes. If associations don’t abandon the old habit of simply providing Webinars in response to one of the three demands, which is easy access and affordability, they’re going to be, I believe, left in the dust by the other providers of learning. Associations are still in the information provision business. They have not yet, many of them, graduated into the business of creating opportunity for learning. We’re seeing, for example, some movement towards things like open space learning, where folks can get together online or face-to-face and ask questions of each other, and there are major caveats there. The major caveat is, if there’s no one in the group with experience and expertise in the area, then essentially what they’re sharing are common practices, and common practices are not effective practices. It’s the old expression that used to say, “Practice makes perfect.” Practice doesn’t make perfect. Practice makes consistent. If you’re doing the wrong thing 100 times, I’m fairly certain you’re going to do the wrong thing again the 101st time. That’s the dilemma, the caveat that exists with the movement towards not exemplary but innovative methodologies that are attractive. They’re innovative because they’re different, but they don’t meet our definition of innovative.

Glenn Tecker: [00:26:00] For us, an innovation is a change that makes something better. If it doesn’t make it better, it’s not an innovation; it’s an experiment. You can learn from it, you can grow from it, but it’s not an innovation. What we’re really seeing is those places that are succeeding in continuing ed, in certification, in credentialing—whether it’s certificates or certification—are those organizations that are recognizing that an innovation requires that the change makes something better. Assessment and evaluation at the level of the individual’s ability to effectively apply what they have learned becomes increasingly important. Now, if you tie this back to the history of associations, associations that provide certificates carefully warrant that the certificate does not guarantee that the individual’s performance will be any better as a result of attendance. It warrants they’ve been exposed to the information. Credentials even don’t warrant that it guarantees the individual’s performance will be improved. The warrant in a credential is the individual has demonstrated mastery of the body of knowledge they’ve been exposed to. But that’s different than assessing the ability to apply.

Jeff Cobb: [00:27:32] What role does culture play in all of this? Because everything we’re talking about is going to require overcoming a lot of “We’ve always done it this way.” I’m not sure associations are more susceptible to that than other organizations, but they certainly are susceptible. They’ve got to break through culturally to make the shift that we’re talking about.

Glenn Tecker: [00:27:52] The culture change is to move to what we refer to as a culture of inquiry, where the expectation is that hard questions will be asked about what we’re doing or anything that’s proposed. It’s the individuals who are known for saying, “Is there a downside here? Can you imagine if…? I wonder what would occur when…. Have we considered alternatives?” The process of thinking strategically is the application of the discipline of strategy at all levels of the organization. Strategy is a discipline, not an event that produces a product. The culture change is to move to a strategic mindset from an analytical mindset, even from a creative mindset. That tends to address the issue of “We’ve always done it this way.” Being willing to experiment. Here again what we observe is many boards have policies that commit them to innovation, but that policy also needs to commit the organization to experimentation—not many associations have done that. They will commit to experimentation if part of that commitment is requiring that risk management process be part of any proposal of a new initiative or experiment. That gives them a level of comfort. The simple way to put it is, if you say to the board, “We want to try something new,” what’s the first question the treasurer is going to ask?

Jeff Cobb: [00:29:29] What’s it going to cost? What’s the downside?

Glenn Tecker: [00:29:31] And, if you say to the board, “We’ve tried it; we tried something, and it didn’t work,” what’s the first comment the treasurer is going to make?

Jeff Cobb: [00:29:40] How much did that cost?

Glenn Tecker: [00:29:41] Exactly. What we’re looking for is a methodology that allows folks to be able to track that potential problem before it occurs. That tends to create the willingness to take the risk.

Jeff Cobb: [00:29:55] Yes, I like that focus on the risk assessment component. You mentioned that earlier in the conversation as well. That does get overlooked so much. If you get the pieces in place, if you’re an organization that is forward-looking, what should it look like, say, five to ten years out? What should the learning function of a successful organization, an organization that wants to stay relevant, what’s that going to look like in your mind?

Glenn Tecker: [00:30:19] Jeff, you just hit what we find to be the most frequent and egregious error of thinking groups, planning groups, design groups within association communities. It’s the failure to take the time to agree on the outcome we are trying to achieve before we end up in debate about what paths to take. It’s the failure to create an envisioned future of what would constitute success before we begin to assess, “What are the potential paths to get there?” And when you fail to agree on the outcome first, two things happen. One, anybody can be right or wrong because you have no benchmark against which to make the judgment. Second, you usually end up saying yes to the idea that’s presented by the loudest mouth that talks the longest or the idea that is supported by the individual who talks last before we have to adjourn so we can make a decision and get home. What we are teaching organizations to do, particularly as it relates to these issues of evolution within continuing education, is to make sure that you agree on what will constitute success before you begin the conversation about what paths you should take to get there.

Jeff Cobb: [00:31:45] If you’re somebody in an organization—this is going to describe probably a lot of our listeners—where you’ve got some authority, maybe you’re a senior leader, but you’re not yet the CEO, you’re not in the C-suite yet, and you’re trying to drive innovation, strategic thinking through the organization to get people to buy into that outcome that you’re ultimately going to try to get to, what’s your advice to that person? How can they help to drive that sort of innovation and strategic thinking in the organization?

Glenn Tecker: [00:32:16] It’s traditional and classic advice. One, identify what would constitute a benefit or accomplishment for the individuals whose influence or participation you’re trying to seek. Make sure that you are able to identify how the movement you are suggesting will in fact add to the things that are important to them. Second, you want to use incremental success. You want to demonstrate what’s possible by taking small steps to get there. Once you’ve taken a couple of small steps and earned the reputation for being able to achieve the promise that you’re making, then it’s much more likely that you’ll be given the opportunity to increasingly take larger steps. What you want to avoid is making a promise that you can’t keep. Honesty is critical here. If there are risks involved, make sure you identify them. If there are bumps along the way, make sure that, when they occur, you have a methodology for figuring out how to overcome them. Demonstrating that you have in place a plan—a plan that’s sufficiently flexible and nimble to be altered based upon changes and circumstances—is absolutely critical. This is a point in time where assuring that you have the core competencies involved in being nimble is an essential ingredient for any organization or unit that wants to commit to an innovative approach.

Jeff Cobb: [00:33:58] I like to ask guests, whenever I can, about their own lifelong learning and what their habits, what their practices are for staying sharp and continuing to grow. What are some of yours?

Glenn Tecker: [00:34:12] I am a sponge for information. A significant portion of my time is spent taking a look at thinking that other people are doing. A large portion of my time, and the reason I so much enjoy what we do as a firm, is that we are constantly learning from our interactions with the folks that we serve. We work with our clients in a partnership. We’re not a group that flies overhead as a helicopter, takes a picture, and tells you what to do. Our process is one where we’re in partnership. We consider what the choices are—and sometimes we know more about them than our clients—and then, with our clients, make the choice about what the best paths are to get there. That process itself is an immensely rewarding process for learning. I have the neurodivergent attributes of being dyslexic and ADHD. My dyslexia has required me to learn from context, so I tend to be very sensitive to things that are occurring around me, and my ADHD has made it uncomfortable for me to spend the same time anywhere, one place at once. So I’m always moving and active. Being sensitive to what’s going on around me and being constantly active in interacting with others, those are my primary learning strategies.

Celisa Steele: [00:35:45] That wraps up our conversation with Glenn Tecker, chair and co-CEO of Tecker International, but hang around for our recap.

Jeff Cobb: [00:35:53] Visit Tecker International to learn more about Glenn’s work.

Celisa Steele: [00:36:10] If you found this episode valuable, we’d be grateful if you’d share it with a colleague. That helps more people find the show and benefit from it, and it supports the work that we do.

Jeff Cobb: [00:36:19] In the conversation, Glenn highlighted the powerful forces reshaping learning and credentialing: adaptive platforms powered by AI, looming security risks, and the accelerating pace of change in knowledge and competencies.

Celisa Steele: [00:36:33] He reminded us that thriving in this environment requires not just new tools and structures but a culture of inquiry at the governance level and a willingness to experiment.

Jeff Cobb: [00:36:43] And to make experimentation possible, staff need to provide clear risk management processes. That way, boards can move forward with confidence, knowing they’ll learn quickly from what works and what doesn’t.

Celisa Steele: [00:36:56] Thanks again for listening, and we’ll see you next time on the Leading Learning Podcast.

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If you’re wondering what role artificial intelligence should play in your learning business—or how to prepare your people and processes to use it effectively—this episode of the Leading Learning Podcast is for you. Many learning businesses are just beginning to grapple with AI’s implications, and the gap between the potential and the current reality is big.

Amith Nagarajan, chairman of Blue Cypress and founder of Sidecar, joins co-host Jeff Cobb to talk about how learning businesses can build the capacity they need to thrive in an AI-driven future. They discuss patterns from past waves of technological change, where associations stand today with AI adoption, and the risks of standing still. Amith also shares practical steps for leaders to get hands-on with AI, the importance of reducing friction, and how AI tools are reshaping knowledge, insights, and personalization.

To tune in, listen below. To make sure you catch all future episodes, be sure to subscribe on Apple Podcasts, Spotify, or wherever you listen to podcasts.

Download a PDF transcript of this episode’s audio.

Celisa Steele: [00:00:03] If you want to grow the reach, revenue, and impact of your learning business, you’re in the right place. I’m Celisa Steele.

Jeff Cobb: [00:00:10] I’m Jeff Cobb, and this is the Leading Learning Podcast.

Jeff Cobb: [00:00:17] Technology is always reshaping the world and therefore how learning businesses operate—from the early days of the Web, through mobile and social, and now with the rise of artificial intelligence. These shifts create both opportunities and challenges for learning providers.

Celisa Steele: [00:00:33] Our guest in this episode, number 461, is Amith Nagarajan. Amith is the chairman of Blue Cypress, a family of companies that help associations embrace AI and transform how they deliver value. He’s also behind Sidecar, which aims to educate a million association professionals in AI by the end of the decade.

Jeff Cobb: [00:00:54] Amith and I talk about patterns he’s seen across multiple waves of technological disruption, where associations stand today with AI adoption, and what leaders need to do to be prepared for the future.

Celisa Steele: [00:01:06] You and Amith also get into some of the applications his companies are building and what those tools reveal about how associations can use AI for knowledge, insight, and personalization.

Jeff Cobb: [00:01:18] And we close with a focus on the human side of all this—how learning businesses can lean into the distinctly human opportunities that AI won’t replace.

Celisa Steele: [00:01:28] If you want to better understand the implications of AI for your learning business, then this episode is for you. The conversation kicks off with Amith talking about what he’s done and is now doing with his companies.

Amith Nagarajan: [00:01:45] I’m probably known originally, or perhaps best known, for having started an AMS company in this space back in the ‘90s called Aptify, which I sold about 10 years ago. Since then I’ve been focused on a family of companies called Blue Cypress, an AI-oriented shop. Essentially, we have a number of different brands within our family that provide a combination of AI learning, AI services, and also AI software to the association sector very, very specifically, and we’ve been doing that for about 10 years. We’ve been in AI for a long, long time (in AI speak) and are very deep in it. That is the focus for me—how do we take AI and help associations not just incrementally improve but radically transform their business models, their value delivery, and how they operate internally as well?

Jeff Cobb: [00:02:37] We’re going to talk about AI more. You’re definitely somebody to be talking to about AI. But I was struck, as you were talking, that it’s already been a decade since you sold Aptify. I know you were in the association world for years before that. I believe Aptify was your first company, if I’m correct.

Amith Nagarajan: [00:02:55] Yes. I’m from California, grew up in Silicon Valley, have been programming computers since I was in single-digit years, and started my first company at the age of 17, which was Aptify. It did not start out in the association market. I didn’t know what an association was back in ’93, when I started it. But, back in those days, I had a knack for software development, and I decided to build a toolset that would help people build database apps. That turned into a robust platform in the early and mid ’90s. And then I happened upon the association market in the mid ’90s and just fell in love with it over time and focused exclusively on it for quite a while.

Jeff Cobb: [00:03:33] So you have been doing it for quite a while. As you said, it wasn’t your original intent, but Aptify took you there, and you’ve been there all the way through Blue Cypress, which has a portfolio of companies that serve associations. What’s kept you engaged with this sector over that period of time?

Amith Nagarajan: [00:03:52] The purpose-driven nature of the people. The community is fantastic. The people in this market are focused on trying to have an impact in the world. By helping associations do what they do better, we feel like we’re making an impact. I feel like I’m having an impact. There are lots of different sectors, lots of different niche markets that you can focus on as an entrepreneur. I happened to find this one by accident. It wasn’t an intention. I just happened upon an association once upon a time back in the ‘90s and then found another one and then found another one, and I said, “Oh, well, this is actually like a whole market.” I stayed because it’s a great business opportunity. It’s a robust marketplace. Once you get to know the market, you realize it’s quite substantial, especially when you look at it globally.

Amith Nagarajan: [00:04:37] But I stayed, and I came back to it after selling Aptify because I felt a really deep connection with the space and wanted to help people in this space not just survive or stay relevant but rather thrive—drive aggressive, transformative change. That’s what I’ve always been about. It’s always been exciting to me to help people do big things, and that’s what we’re trying to do at Blue Cypress. I’ve been doing AI stuff since the early 2010s. We started getting into AI at Aptify in the years preceding the sale of it. We started getting pretty heavily into AI and then ended up spinning out those technologies into what became rasa.io, which was our first AI software company way back in the day. We still own that company and are growing it. It’s doing well. It’s been a while, but we’ve seen AI from lots of different stages of development and applicability to the market.

Jeff Cobb: [00:05:27] I’d forgotten you had gotten into it that early. In some ways, our stories are similar because I too was building a piece of software that was not intended for the association world and found myself in the association world and have been there ever since. But you were there a little earlier than I was. You’ve seen some pretty big shifts from the rise of the Web. You started out in the early ‘90s; the Web was still in its infancy then. Then into the social media craze. I remember that hitting associations, and everybody thought it was going to put associations out of business. And now AI. As somebody who’s observed all of that, are there patterns you see repeating or lessons that you think leaders should draw, particularly right now, if they’re thinking about “Oh, AI is hitting. What do I do with that?”

Amith Nagarajan: [00:06:11] Yes, there are definitely patterns. Going through those major transitions—obviously the Internet and the Web, e-commerce, mobile, social, all these big shifts, and now AI, as you mentioned. Common patterns are, first of all, that people tend to overestimate the near-term impact but radically underestimate the long-term impact of technologies that are truly representative of phase changes. They’re not just an incremental innovation, where you went from the iPhone 15 to the iPhone 16, and you got some new widgets on your screen, but rather something that can fundamentally transform the economic relationship between buyers and sellers. And I mean that in the broadest possible sense. If you think about what happened in each of those transitions over the last 30+ years, you’ve had a significant shift in terms of information, information advantage or disadvantage on the demand side or the supply side of the curve. You look at distribution.

Amith Nagarajan: [00:07:09] I talk a lot about AI as being the third exponential curve following two others. One is the compute curve, which everyone talks about, often known as Moore’s Law, the exponential rise in compute power relative to cost. And then what ended up happening with the Internet was the distribution curve. We flattened out the cost of distributing nearly anything that can be digitized down to essentially zero. But now what’s happening with AI is the cost of reasoning, the core component of what we consider intelligence, is going to zero. We don’t know what to do with that. But coming back to the question of pattern recognition, as costs approach zero for something that was once scarce and is now becoming abundant, it reframes the relationship between consumers of value and producers of value—or buyers and sellers, to put it another way. People often don’t anticipate the magnitude of the impact long term, but they think about the hype cycle, and they’re like, “Oh my God, this is going to change everything.” And then they wake up a year later like, “Well, actually things haven’t changed that much.” It’s a false sense of safety in the status quo that it gives people.

Amith Nagarajan: [00:08:12] I’ll come back to my thoughts on AI on that at some point in this discussion, specifically because it is moving faster than these other curves. As crazy as the Internet and mobile and all that was, it’s nothing compared to AI in terms of speed. My main point that I’m trying to underscore in terms of the trend line across these various changes over time is that, when people get this sense of security, that it didn’t really change that much, and then the bigger tail on the change, the transformative impact comes along, that’s when they get caught off guard. Back in the ‘90s, people were saying, “Oh, associations are going to be out of business pretty soon. There are all these companies that are going to be coming out with verticalized Web sites that are going to take over associations.” Associations were still there in the early 2000s, and they’re like, “Well, that didn’t happen.” But, sure enough, the Internet has displaced the activities that associations have historically done in many ways, and AI will do that as well.

Amith Nagarajan: [00:09:08] My general observation is that people tend to not move quickly enough because they get…. Associations are generally not the first adopters of anything. We’ve talked about that before in our conversations before this pod. It’s a frustration to technologists and to people who are trying to push the boundaries of what’s possible. Some associations move a little bit faster than others, but generally they’re slow movers for the most part. Slow movers tend to have their perspectives reinforced by the initial hype cycle being greater than the initial return, and then they get totally caught off guard because the bigger wave is coming on the back end of it—that underestimation of the long-term impact that I’m referring to. We can’t afford to do that with AI is the bottom line.

Jeff Cobb: [00:09:52] What are examples of organizations in those earlier waves that either got it right—they timed it correctly; they saw what was going on and reaped huge benefits by what was happening with the Web, social, or whatever—or, conversely, maybe one or two that didn’t and got clobbered by it?

Amith Nagarajan: [00:10:14] There was a pretty big shift to the world of education delivery online back in the whole phase of Internet and mobile. You know that world far better than I do, Jeff. But the concept of people delivering traditional classroom-based, synchronous training when asynchronous was getting better and better and better, more dynamic, more capable, the learning outcomes were increasingly achieving the goal of the student. And so a lot of associations back in the ‘90s were like, “No, distance learning, remote learning,” as we used to call it back then, “is just not as effective.” Of course there are definitely, still to this day, tremendous advantages of synchronous, in-classroom, face-to-face learning, but the modalities have improved so much that many of the people who were thinking the old way—they weren’t even willing to dabble in online asynchronous learning—got crushed. You see associations where they had significant revenue declines, where they weren’t focused on that yet. You see, for example, medical specialty societies. There’s a number of them that I’m quite familiar with that have thrived in this era because they’ve invested in making it possible to do distributed learning well through the Internet, through mobile, but embracing the modality for what it is.

Amith Nagarajan: [00:11:20] You can say to me, “Oh, well, AI will never replace humans for X, just like the Internet will never replace face-to-face for X.” That’s true to some extent. Maybe eventually it’s not. People might say, “Oh, you’ll never stream video on the Internet. It’s far too slow.” That’s just a matter of time. But that’s just an example. There are certain things that are fair to say, like our biology mandates that we have connection, that we are in close proximity with others in our species. It’s not psychology; it’s biology that dictates that. We’re always going to crave elements that technology doesn’t displace. And that’s good, I think. That’s really, really good. The point would be that people forget about the new. They’re saying it won’t displace the old, but what is it going to do that’s different, that’s either complementary or, in some cases, crowds out the need for the old, even if it’s not exactly the same? It’s still a substitute good if people buy X instead of Y even if X is not an exact substitute in terms of its functionality if people stop buying the other product.

Jeff Cobb: [00:12:27] Where do associations stand right now with AI adoption, and where do you think they should be?

Amith Nagarajan: [00:12:35] If I were to use a report card type of metaphor, I’d say it’s not looking so great today, but I’m optimistic about the future. The way I would look at the current state of affairs is that I think about education as the leading indicator for associations’ ability to adopt AI. You can go to vendors like ourselves or any other company and buy software, get help with services, et cetera. There are lots of great things you can do that way, but that doesn’t improve you. What we are always focused on—and we do some surveys around this—is how much education are people taking in, whether they’re the CEO or a first-year grad coming into the workforce? What level of investment, in terms of time and dollars, are people putting into learning? And it’s very minimal right now. It’s very, very minimal. People are doing almost nothing on average. Now, there are some associations that are putting some effort into this, and that’s fantastic. They’re going to see tons of dividends from that. The bottom line is that no vendor, no vendor at all, can solve your problem for you. You have to be knowledgeable about this stuff.

Amith Nagarajan: [00:13:38] The way I describe it is, let’s say we’re off to a board retreat, you and I, along with our board, and we’re association execs. You’re the CEO. I’m the COO of some association. We’ve got 10, 20, 50 board members coming, depending on the size of the association’s group. We’re going to figure out what the next year [or] two, three years looks like. How in the world can you and I possibly stand a chance at doing a good job in building a strategic plan if we don’t understand AI quite deeply? Maybe not down to the bits and bytes, but we need to understand its capabilities. And the way you understand its capabilities is by unpacking it, working with it, learning it, and you can’t delegate that. You can’t delegate that to a technologist. You can’t delegate that to an outside vendor. You have to make the investment in time.

Amith Nagarajan: [00:14:26] The good news is it’s not a PhD. You don’t have to go to school formally. You don’t have to spend months or years doing nothing but AI learning. That’s impractical. When I speak on the subject, Jeff, I always tell people block off 15 minutes a day every day. Listen to a podcast. Watch a video. Play with a particular tool. Read a book. Whatever makes sense. Hopefully a mix of those things. There’s nothing quite like hands-on. Use the mix of learning resources, but do it every day. Just like working out, just like anything else you practice, you get better and better. If you practice with AI at least 15 minutes a day every single day for the rest of this year, by the end of the year, I would be willing to bet you’d be amongst the top 10 percent of the knowledgeable people in AI. We’re recording this in the late summer timeframe, so you don’t have a ton of time. But, if you get started now and spend 15 minutes a day, you’ll be further along.

Amith Nagarajan: [00:15:17] There are lots of free resources. There are resources like Sidecar’s (my main focus these days), which try to help associations learn AI at scale. In fact, our mission for the next four and a half years, by the end of the decade, is to educate a million association professionals in AI. Whether it’s at the top tier of our AAiP [Association Artificial Intelligence Professional] certification or if it’s attending a free Webinar or downloading a free book, we don’t really care. Our goal is to touch a million+ association folks in that time. But that’s still a drop in the bucket compared to the number of people that work in the space, both as paid staff and volunteers. To me, the report card—going back to that—is not great today, but the good news is we can change it quite easily.

Amith Nagarajan: [00:15:57] My bottom line for the prognosis for the future is, if associations make that investment in education and put on their creative thinking hats, they have all the opportunity in the world. AI has lowered the cost of everything. It’s lowered the cost of software development, of writing, of building anything from scratch. The barriers to entry for associations to get into completely new lines of business with completely different ways of thinking in order to solve the problems that their members will have in one, two, or three years are better than ever. If you’re willing to think creatively, take a little bit of risk, do some experiments, to, most importantly, invest some time, I think the future is extremely bright for any association that wants to play in the game. But a lot of people aren’t playing in the game at all. A lot of them are sitting on the sidelines.

Jeff Cobb: [00:16:42] What do you see as the cost? I’m looking at it from the standpoint of the learning business and organizations that provide educational learning, what AI is doing there in terms of providing adaptive learning experiences, personalization. If you’re not getting on board with that, somebody is going to outpace you in your market. What about more generally for associations? What’s the opportunity cost if they don’t do what you’re talking about?

Amith Nagarajan: [00:17:06] You become obsolete pretty quickly. Many associations have the most reputable brand, the best content, and the strongest community in their vertical. Let’s say your vertical is a particular profession, maybe bounded by a particular geography, where you are still the number one game in town for, let’s say, a given state and a given field, or maybe nationally, maybe internationally. And so, in your niche, whatever that is, your brand and your content are very strong. Yet you decide intentionally—even though it may not be because of any malicious intent, but it is intentional—that you’re going to make it really hard for people to get your content, to find what they need. To gain actual value from your organization is going to be tough because you’re going to make your Web site a Byzantine structure. You’re going to make it so that your Web content for learning isn’t particularly up to date. I say it in this very directed manner that it’s a choice because all things in life are a choice in terms of where you invest your energy and your dollars.

Amith Nagarajan: [00:18:10] Part of the problem is associations try to do too many things. They try to solve 15 problems. Of course, that goes back to governance, where, in these strategy retreats, everyone wants to have their little pet project on the table, and they don’t want it to die. But you have to go pick two or three things and do them well. So there are some tough choices that have to be made. My view is associations create a lot of friction, and friction is an enemy—number one enemy perhaps in some contexts—to helping your audience gain value from you. If I say, hey, Jeff, I know you guys have unbelievable expertise in education and learning. In fact, for us, that’s super relevant because we run a certification program on AI for associations. I’d love to learn from you. You make it quite easy because your content is pretty easy to access. It’s pretty well organized. You have podcasts. You have written-format material. So I can find you easily. I can find your content easily.

Amith Nagarajan: [00:19:08] Even if you had great content, but you made it really, really hard for me to get to it, I’m not going to come to you as an authority on the subject, even if I know you and respect you and think you’re the greatest source of information on it. Same thing with an association. There’s a certain tolerance people have for friction. Think about it this way—why did Google completely freak out? They lost it when ChatGPT started rising because they realized that is a displacement of their business if they don’t catch up and do something. They put some serious horsepower into it now, and I think they’re doing some good stuff. But, when you see a momentous shift like that, you have to pay attention to it. Associations have this issue that their stuff is hard to get access to. It’s hard to find things. Almost every association CEO I talk to says, “Yes, the number one complaint I get from my board or from close-in volunteers is that it’s hard to navigate our Web site.” They’re like, “Oh, let’s go spend half a million dollars on a new Web site with some vendor.” And then six months after that Web site goes live, they’re like, “Yes, it’s like glossier and shinier and smells better,” but it still basically sucks in terms of being able to access the content they need.

Amith Nagarajan: [00:20:12] You’re not going to solve it with a new version of a horse and cart. You need different approaches to solve the problem. Because the problem isn’t that anyone has anything but the best of intentions; it’s that it’s a really complicated problem. You have a lot of content, you have a lot of different people to serve, so you need AI to personalize. You need AI to curate. You need AI to make things conversational. And that’s the opportunity in front of you. Five years ago, it would have cost you a fortune to do any of this, and it would have been pretty low quality. Now it’s extraordinary quality, and it’s very accessible even to very small associations. But you have to start by understanding what it can do. You can buy things and start slapping them on your Web site, but it’s much better if you spend some time learning first.

Jeff Cobb: [00:21:00] You run a lot of programs to help people in associations with AI. What have you learned from that around what hangs people up around AI? What are their hopes, fears, blind spots?

Amith Nagarajan: [00:21:13] With Sidecar, we’ve got an audience of about 30,000 people that consume our content on a regular basis, whether it’s our three-times-a-week newsletter, which is totally free. We also run a weekly podcast called the Sidecar Sync. A lot of listeners tune in there regularly to learn and get updates. We’ve got a free book called Ascend, which is an AI book—full-length business book about AI for associations—totally free to download, and a ton of other stuff. So we put it out there. We’ve got about 30,000 people who regularly consume this stuff, and it’s growing quite rapidly. That’s almost double in size from this time last year. Clearly, there’s a lot of demand there.

Amith Nagarajan: [00:21:47] What I’ve learned from it on my end personally is that people are hungry for this, but that it’s unbelievable how fast people become experts. We have people that we’ve brought into our ecosystem that started off going, “I don’t know which way is up when it comes to AI,” and now these are people that are writing blogs. They’re leading sessions. They’re connecting with others. Part of what we do is help folks do that, and it’s amazing. It’s so incredibly rewarding to help people in their journey. They’re doing things in their organization, punching way above their weight class, and some of these are from very small associations. There is a perception that we can’t do it because of X, whether it’s “Oh, we’re not that technical” or “We don’t have a big budget” or “We’re a very small association.” There are all these obstacles. Those are all psychological. The reality is that the tools are accessible, fairly easy to use if you’re willing to put the time in. You don’t need to be a technician to be fairly good at this stuff fairly quickly, which is the exciting part.

Amith Nagarajan: [00:22:43] One thing I would share with your listeners, Jeff, is that a big impediment is fear of the organization not wanting the staff to do stuff with AI. There are still a lot of associations who have outright banned AI. There are still people who’ve done that. Good luck with that one because your people are using AI, FYI. They’re just doing it with personal accounts, most likely free personal accounts, which have zero security, and your content is being fed to those free accounts. If you are banning AI, you’re essentially saying, “Hey, would you like to use DeepSeek and send all of your association’s content across the Pacific Ocean? Cool. Go for it.” The reality is that, if you don’t set policy, people will just do whatever they want to. There are some people who will do nothing. Don’t get me wrong—some people who are the rule followers will say, “Well, my organization said, ‘Thou shalt not do AI,’ so I won’t.” But there’s a large number of people who will. And it’s stressful too. It’s super anxiety-inducing if you want to use a tool that you know could potentially help you.

Amith Nagarajan: [00:23:45] Then there are the people out there who don’t want to change anything, but they don’t necessarily like drudgery either. They might be afraid of losing their job. There are all those kinds of issues where people are thinking, “Well, if you’re so good with AI, then I don’t need to do my manual job anymore, which is repetitive.” It might be white-collar labor, but it’s very repetitive, and there are a lot of jobs like that. It’s your job as a leader to envision that future, to find the roles where people’s experience, knowledge, and unique contributions to your culture can add value. Most associations aren’t looking to cut tons of jobs or any jobs, but people assume that that’s what they’re going to do. That’s another obstacle. There’s a big leadership gap here, both in terms of basics, like figuring out what your AI policy is going to be. We’ve got templates for that, by the way, on our Web site that are free—you can download them on Sidecar—that will help you figure out what your policy should be.

Amith Nagarajan: [00:24:33] It’s basic stuff, by the way. It doesn’t require a lawyer. It doesn’t require tons of work. But it’s, hey, is ChatGPT allowed? Is Claude allowed? Are you going to allow meeting notetakers? In this Zoom call, you have a meeting notetaker that’s helping you record the notes for the pod, and it’s going to help you put together all that kind of stuff, which is great. But do you want to allow that in general when you have a Zoom call or Teams call, especially if the notetaker is one you’ve never heard of? Because a notetaker can show up from any company that anyone happens to use, and where’s that content going? There are all these things you need to think through. Again, it’s not a gargantuan task, but the absence of such policy is an impediment to adoption, and it’s also a major stress point for your team. Fix that. You can do that in the next 30 days easily.

Jeff Cobb: [00:25:15] Your comment about how quickly some people learned and became experts just by participating, I find totally true. You mentioned later making that 15 minutes a day. I’m sure you’re familiar with Ethan Mollick, who says, “Just roll up your sleeves, and do that 10 hours.” Once you do that, you start to realize this is doable, and you can get so much out of it. I was in a mastermind group we run just the other day, and somebody was lamenting the fact that their organization won’t pay the $20 for the ChatGPT subscription each month. If you look at how much that adds up to in terms of cost annually, it’s trivial compared to most other things they’re doing with software, and the potential returns are huge. But the organization hasn’t made the kind of decisions that you’re talking about and put the structure in place.

Jeff Cobb: [00:26:05] I did want to also dive in, in addition to Sidecar, to two of the applications that are part of the Blue Cypress family. And you’re welcome to talk about others if you’d like. These two jumped out at me, partly because I was at ASAE recently and noticed them there. But also one of them we’ve referenced in our work recently, and that’s Betty, which is the chatbot-type application.

Jeff Cobb: [00:26:27] We’re now at a point where I believe that traditional, formal, structured courses are going to decline significantly. There is certainly a role for them. They will not go away. But these unstructured learning activities, where the learner is able to engage how they need to engage at that point in time to solve the problem, learn what they need to learn, a chatbot is a great vehicle for that. We recommended it as one of the solutions in an engagement recently. We’re also very big on data these days. Traditionally, the folks in our audience (the learning business audience) have not done enough with data, either to understand their market or to make learning that adapts to their market. Betty is one of your applications; Skip is another, which I know does data analysis. Can you talk a little bit about what those two applications do? And, again, if there are others you feel it’s relevant to mention to our audience, feel free to do that.

Amith Nagarajan: [00:27:27] I’ll talk about three categories, and I’ll mention our offerings in this space, which we know better than we know anything else; I can speak to them the best. The three categories I think are critical for all associations are knowledge, insights, and personalization. We have a knowledge agent in Betty, we have a data analytics agent in Skip, and we have a personalization engine in a product called rasa.io. I’ll talk about each of those briefly. Associations have, for hundreds of years in some cases, been the center of knowledge for their community. A knowledge agent—imagine a being. In this case, it’s a computer, but it’s an entity that has the deepest and best, most contextualized knowledge in your field of anyone on the planet and is available all day, every day, and can be available as an assistant, as a tutor, as a writing partner. That’s exactly what Betty is. Betty has been around since late 2022. We’ve been working, as I mentioned, with AI for a lot longer than that, but we knew this moment in time would be coming because we’d been working with both predictive AI and generative AI for years prior to the ChatGPT moment.

Amith Nagarajan: [00:28:44] But when ChatGPT launched, we said, “Okay, we need to pull the trigger on doing this knowledge agent/knowledge assistant concept now.” So we did. Betty has over 100 enterprise associations using the product. It’s growing extremely fast. Basically, what happens is this—an association says, “We want to train Betty,” and so Betty will learn your content. Your content could be all of your past journal articles. Your Web site might be all of your online courses. It could be all of that. It could be lots of different things. Betty learns that, and Betty stays up to date on all that material as it continues to change. Betty provides grounded answers to your community. “Grounded” is a very important term. You’ve probably heard the term “hallucination” in the world of AI, and that’s when the AI essentially makes something up—that’s both a bug and a feature in some respects. Not in this context. It’s not a feature to make something up when someone’s looking for answers. It can be a feature when you’re doing brainstorming and being creative about “What kind of business ideas could I come up with? How can I possibly do a better marketing campaign?” That’s where the AI’s creativity is helpful.

Amith Nagarajan: [00:29:50] Context, knowledge retrieval, and answering particularly mission-critical questions—it’s completely unacceptable, and, unfortunately, there are many AI solutions out there that still allow for this concept of hallucinations to seep through. At Betty, our number one priority has been accuracy of the knowledge because associations—especially in medical or engineering—cannot tolerate inaccuracies. Every answer that Betty provides, whether it’s through chat or through agentic AI, which is when you connect Betty to other systems—this is not just the chatbot; that’s one way to surface Betty, but you can connect Betty to the rest of your critical business infrastructure—Betty always cites her sources and is always able to refer back to the knowledge retrieved and the thinking process that went into formulating the response. It’s not some black box where you’re hoping and praying that it’s going to answer your members’ questions correctly. It’s grounded on your content, only your content. It’s not using the Internet. It’s not using random Web sites. It’s a very powerful solution, and it’s purpose-built for this sector, where fault tolerance is critical in terms of availability, where the tolerance for any risk is very low, for good reason.

Amith Nagarajan: [00:30:57] Betty’s been an incredible hit. We expect to see Betty grow for years to come because the problems she solves are ultimately different than the problems you can solve through classical means. I mentioned earlier the difficulty of accessing the information people want. Well, Betty completely solves that. Rather than having to put in the right keyword into some search tool—even if it’s a great search tool, and you get 50 articles back, that’s not necessarily helpful—you go to Betty and say, “I’m working on this problem,” and Betty gives you an unbelievable answer. You’re going to come back to that. If you’re a member and you have that experience, you’re going to come back to that. Some people say, “Well, how can the association compete with ChatGPT?” The answer is two things. Number one, your private content, and number two is your brand. People will trust your brand, for good reason, if you are grounding your answers on the basis of your proprietary and uniquely high-quality knowledge base.

Amith Nagarajan: [00:31:55] You asked about data and insights, so I will pivot to that next. We also identified what we consider one of the grand challenges of association management: insights into really anything. It can be classical database questions like, “How many members did I lose in the last month?” or “What’s my renewal rate?” or reports from events, where it’s like, “How many attendees do I have that were an attendee at some prior year, but not this year?” All those kinds of things. Those are fairly straightforward to do traditionally. Part of the problem is that people have this explosion of systems. It’s not just an AMS, LMS, or CMS; it’s those things, but it’s also probably 5, 10, or 50 other systems that are used for different specialty things. That’s not going to go away. People have been trying to fight this since the beginning of computing. There have always been specialty systems because they do the job really well. So the question is then how do you solve for a widely distributed source of truth in terms of data? How do you make it so that people can ask any question—like with Betty—and have a rapid response with a well-thought-out, reasoned answer? It’s not just for technicians; it’s specifically for business users.

Amith Nagarajan: [00:33:07] Think of Skip essentially as like Claude or ChatGPT, where you have a conversational interface, and Skip is living, though, in a secure data platform. It’s an AI data platform that we have in the market called MemberJunction, which is a totally free open-source data platform we publish and maintain. What it allows you to do is to easily ingest data from all your different data sources. If you’re using Salesforce, and let’s say you also have an AMS, and you have a financial management system, and you have 10 other SaaS products that are out there, maybe some spreadsheets and other things to throw into the mix to round it out, you can ingest all of that data very easily into MemberJunction and keep it up to date. Skip lives on top of that and has secure access to all that data and is smart enough to figure it out. The problem for us humans is that that many systems are too complex for us to know, “Oh, well, this data lives over here, and this data lives over here, and how do I connect it and make sense of it?”

Amith Nagarajan: [00:34:04] Skip’s an incredibly powerful AI and has the ability to look across any complexity of schemas and then write queries, write code, and ultimately come back to you with what we call components—reports and dashboards—that, if you like them, you can save and rerun them however often you want, or you can ask for new ones each time you use it. Skip typically takes anywhere from two to five minutes to produce an answer, sometimes a little faster, sometimes slower, depending on how much code Skip has to write. Think of Skip essentially as a software development team coupled with an MBA-level person. You take a brilliant business strategist and analyst coupled with a data scientist and a great programmer, combine them all together in a team, and make them available 24/7 and able to respond to you within a handful of minutes. It’s pretty amazing. You can start to get insights. What I love about Skip is that we’re trying to reignite curiosity. We have all been conditioned to not expect much in terms of data because it’s hard; we have to go to a vendor, or we have to go to IT, and we’ve got to wait. By the time we get an answer—because some custom query or report has to be created—even if you have the dollars to spend, typically, you wait two weeks, four weeks, eight weeks. You don’t ask the question because you’re like, “Well, I need to know now. And, if I don’t know the answer now, I’m not going to wait in my own workflow for two weeks to get the answer.” As a result of that, many of the curiosities people have about their data to gain insights and to leverage insights are stamped out over time. That’s what we’re excited about with Skip.

Amith Nagarajan: [00:35:39] Finally, one of the most important things to get right is this idea of getting the right piece of information to the right member through the right channel at the right time. That’s this idea of personalization. This is the original problem we’ve been working on solving in the AI realm, going back to the early 2010s. This is before rasa was an official company. But, back at Aptify (the AMS business I used to own), we were sitting on top of these massive, large-scale databases of information, and our belief was, “Oh, well, we could make these Web sites better and make online communities better and make the education process better if we could personalize. So let’s use all the information in the AMS to do that.” That was the original idea in 2013, 2014, 2015.

Amith Nagarajan: [00:36:23] By 2016, when I sold the company, we had spun out the technology assets that became rasa and ended up focusing in one particular narrow category at first, which was e-mail newsletters. It’s almost like an afterthought, but people forget about the fact that the newsletter is one of the most valuable things many associations provide. The lowly newsletter, which goes out maybe to 20,000, 50,000, 100,000 people a week or even daily, is your most frequent point of interaction oftentimes. How often do people come to your Web site? Even a wonderful Web site? Maybe once a week. Probably once a month would be extremely high. Most of the time people come to your Web site when they want to register for your annual conference or renew their membership or something like that. Maybe they do a lookup to try to find an article and go away after they’re frustrated. That’s happening three, four, five, six times a year. But your newsletter hits their inbox every day, perhaps, and it’s an opportunity to deliver value or an opportunity to frustrate.

Amith Nagarajan: [00:37:21] The problem is, if I have 30,000 people at Sidecar, for example, and, yes, they’re all association people, mostly association people, and mostly they’re interested in AI because they wouldn’t be part of Sidecar if they’re not, how do I then make it relevant to them? How technical are they? How far along in the journey are they? What’s their level of proficiency in different tools? What’s their area of interest? Are they a finance person, a marketing person, or a CEO? Are they entry-level? There are all these dimensions of what makes you and me individuals. This goes way beyond the idea of segmentation. This is infinite segments, essentially, and it’s dynamic. The idea was to say, “Hey, can we really target the individual?” That’s what we’ve proven with rasa for a decade now. If you send e-mails that are deeply personalized, the funny thing that happens is people ask for more of them. Associations often say, “Oh, we can only do a weekly newsletter because we send too many e-mails.” That’s true if your e-mails annoy people. If people are getting something that isn’t value-additive to them, they say, “No more.” But, if you give people something that’s improving their life, they’re going to want more of it.

Amith Nagarajan: [00:38:30] Of course, I want more free ice cream. Of course, I want more free whatever. It’s great. It’s wonderful. It’s utility. If it’s negative utility, they say, “No more.” If it’s positive, it’s very simple. Sure enough, with rasa-based e-mail newsletters—and this is over 10 years with hundreds and hundreds of association customers and non-associations as well—we’ve shown a couple things. Number one is your unsubscribe rate is cut down by an order of magnitude, literally a 10x decrease in unsubscribe rate because we’re sending relevant content every single touch. Number two, your open rates go up by about 2x. And, number three, your click rates go up between 5x and 10x. That’s an enormous improvement in engagement. Many people have quoted that they value the newsletter as the number one benefit of membership after they implement a personalized newsletter. It’s a tremendous, easy thing to do. And that’s why I like to talk about it because it’s proven. Hundreds of associations use it. Many of them make a lot of money because of it.

Amith Nagarajan: [00:39:25] If you sell ads in your newsletter and all of a sudden you have five times as many clicks and two or three times as many opens and a bigger audience because there are fewer unsubscribes, it’s really good for your advertising metrics, and you’re going to make more money. But, ultimately, you serve the member better. Most recently—last thing about rasa—we broadened the technology. We’ve had a 98-percent retention rate year over year for a decade now. The number one complaint people have had is “Well, I wish you could send more e-mails, not just the newsletter.” And that’s the thing we’ve been working on for a couple of years. The AI has gotten powerful enough where it can personalize anything. It’s not just newsletters anymore, but now you can send any e-mail through rasa. It’s a product called rasa Campaigns. There are two different things: rasa Newsletters and rasa Campaigns. Rasa Campaigns is a direct replacement for old-school e-mail blast software that doesn’t personalize or doesn’t personalize well. It’s cost-comparable to those kinds of packages, and it allows you to do any kind of campaign, sequence-based campaigns. But the key to it is personalization, deep personalization.

Amith Nagarajan: [00:40:29] A couple quick examples. In your world of learning, rather than promoting a course and saying, “Hey, Jeff, you should attend my upcoming course,” I can specifically tell you why. I can give you a subject line that’s handwritten for you by AI. I can give you three bullets about lessons in the course that are going to be super, super relevant to you. Same thing for annual meetings, same thing for volunteer opportunities, and on and on and on. I actually get excited. I love all these products. They’re all my children, essentially, so it’s hard to say which is a favorite. I don’t have a favorite. But the idea of personalization doesn’t quite have as much sizzle, but the value creation is absolutely enormous.

Jeff Cobb: [00:41:14] Many people are worried that as AI becomes more and more powerful, the human role starts to shrink, and we’re going to have issues with that. But, of course, associations and learning businesses are supposed to be fostering human growth. That’s what they’re about. Where do you see the uniquely human opportunities that AI is never going to replace? Certainly I’ve got learning in my mind, but, more broadly, how should organizations lean into the human opportunity that is still there with AI?

Amith Nagarajan: [00:41:46] You lead the thought process with where will the customer naturally go? Do customers still go to Blockbuster, or do they stream on Netflix? It’s the latter because it’s more convenient, and the value is better. There’s more choice. It’s faster, easier, cheaper, better. No matter how great your video rental store is, doesn’t matter. The flip side of that is what would people continue to do with people? Connecting in person, synchronous learning. Even if you can automate almost all of asynchronous with AI tutors and AI-generated content, synchronous experiences with experts are deeply valuable. You mentioned a mastermind that you guys run; we do one as well. That kind of cohort-based learning is incredibly powerful, deeply human connections. There’s more opportunity to do that. At Sidecar, for example, with our audience of association AI professionals and people who are going through the certification process, we get a lot of customer service inquiries—very similar to member service, same idea. We’re working on automating all of that. We love our team, and we’re not planning on letting anyone go. In fact, we’re going to add more team members.

Amith Nagarajan: [00:42:44] But what these people are going to be doing, instead of answering rote e-mails, as we get more of this agentic AI up and running, is to make proactive outreach part of what they do. They’re going to call customers and say, “How can I help you improve engagement amongst your team? How can I help you get everyone in your association staff and your close-in volunteers up to speed on AI? How can we increase that level of service?” In the world of education—again, this is your domain far more than mine—we’ve known for a long, long time, for thousands of years, that one-to-one tutoring has been the gold standard for the ultimate way of achieving outcomes in terms of learning, knowledge transfer, skill accretion, and all that. Yet that’s not scalable. Not all of us have an expert we can go sit with and hang out with all day and learn from and have discussions with. But now we can. One of my favorite use cases of Betty, I briefly mentioned, is Betty as a tutor.

Amith Nagarajan: [00:43:39] In fact, if you come to the Sidecar Learning Hub, which is all our asynchronous content, we’ve got the 10, 11 hours of content you mentioned on AI stuff, and, in there, Betty is hanging out. If you have a question, you can talk to Betty, and Betty knows, not a ton about you, but a little bit about you, soon will know everything about you, and Betty does know where you are in the course and what you’ve studied so far and the lesson that you’re on. When you talk to Betty, Betty is also primed to not give you the answer but to take a more Socratic approach to say, “Well, Jeff, let me walk you through it. What do you know about it? How can I help you learn this?” and try to ultimately get you to the right outcome but to be much more of a tutor mindset. AIs don’t get tired, and AIs can scale to every human on earth. We can all have the most incredible tutor in any field that we want. We can’t do that with people. It takes us 25+ years to grow a human into a productive member of the workforce. We do that with AI in no time flat. We can scale it basically to any number.

Amith Nagarajan: [00:44:36] The other thing to remember is the AI we have right now is the worst AI we’re ever going to have. It’s just getting better. It’s on a six-month doubling curve, roughly, in terms of power relative to cost. Coming back to your question, I’m optimistic. If you are one of the people who’s like, “I’m going to learn this stuff. I’m going to figure out how to automate a lot of the drudgery. I’m going to focus on the connection. I’m going to focus on the relationships. I’m going to focus on new ideas.” We’re explorers, right? Built deeply into our DNA is this desire to fan out and figure out what’s around the corner and what’s on the next planet or what’s behind the next business model. And we have that opportunity now. We can go and explore at an unprecedented rate. And that means more discovery. The fixed mindset—that the earth is flat, and there’s nothing past the known universe—is very limited. Every time there’s been any era of scientific progress or philosophical discovery, we quite regularly find out that, in fact, the last generation’s thinking, as novel as it was at the time, was limited, which is, by definition, what makes the world and the universe a giant and amazing mystery. To me, I’m excited. Now, not everyone’s going to share that. People lead with fear, and a lot of times they’re saying, “I don’t know if I can learn this.” I believe that we can bring everyone along.

Celisa Steele: [00:45:54] We’re not done just yet—stick around for our recap.

Jeff Cobb: [00:45:57] Learn more about the work that Amith Nagarajan does at Blue Cypress and a link to Amith’s LinkedIn profile. He’d love to connect. He’s also open to fielding e-mails.

Celisa Steele: [00:46:17] If you’re serious about AI—and you should be—be sure to check out the Sidecar site because Sidecar has dozens of free AI resources tailored to associations.

Jeff Cobb: [00:46:32] If you found this episode valuable, we’d be grateful if you’d share it with a colleague. That helps more people find the show and supports the work we do.

Celisa Steele: [00:46:40] In this episode, Amith underscored that leaders can’t delegate understanding AI. Investing even 15 minutes a day in learning about AI and using it makes a huge difference, and learning businesses that put in the time will be positioned to thrive.

Jeff Cobb: [00:46:57] Amith also pointed out the opportunity cost of inaction. Amith’s focus is on associations, and he noted that associations have incredible assets—brand, content, community—but they risk irrelevance if they don’t apply AI to reduce friction and deliver value in new ways. So, dear listener, make the time to learn and apply a bit of AI today.

Celisa Steele: [00:47:20] Thanks again for listening—see you next time on the Leading Learning Podcast.

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The post Building AI Capacity with Amith Nagarajan appeared first on Leading Learning.