In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss the critical considerations when deciding whether to hire an external AI expert or develop internal AI capabilities.

You’ll learn why it is essential to first define your organization’s specific AI needs and goals before seeking any AI expertise. You’ll discover the diverse skill sets that comprise true AI expertise, beyond just technology, and how to effectively vet potential candidates. You’ll understand how AI can magnify existing organizational challenges and why foundational strategy must precede any AI solution. You’ll gain insight into how to strategically approach AI implementation to avoid costly mistakes and ensure long-term success for your organization. Watch now to learn how to make the right choice for your organization’s AI future.

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What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode.

Christopher S. Penn – 00:00

Katie Robbert – 00:47

Katie Robbert – 01:41

What do you want to do with AI? Why are you bringing AI in? Is it because I want to kee

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss troubling new trends in leadership and how you can navigate an increasingly demanding work environment.

You’ll learn to identify the difference between tough business decisions and terrible leadership tactics. You’ll discover practical strategies to document issues and set healthy boundaries with difficult leaders. You’ll understand the critical importance of building your personal brand and professional network as your career life raft. You’ll explore how to use new tools, including AI, to enhance your skills and uncover hidden job opportunities. Watch this episode to gain actionable advice and empower yourself in today’s evolving workplace!

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What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode.

Christopher S. Penn – 00:00

It is a definite tone shift. This is from a Wall Street Journal article from May 11, titled “Everybody’s Replaceable: The New Ways Bosses Talk About Workers.” And the punchline is: shut up, stop complaining, and do more work for less pay.

Katie Robbert – 00:46

So Skims and Good American are the Kardashians. So take that with a big fat boulder of salt.

Katie Robbert – 01:19

Katie Robbert – 01:23

Katie Robbert – 01:38

Katie Robbert – 01:40

I’m not naive enough to think that there aren’t leaders out there in companies speaking this way. They absolutely are. But that’s not new. AI is not creating this problem.

Katie Robbert – 02:07

Katie Robbert – 02:09

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss the crucial difference between ‘no code AI solutions’ and ‘no work’ when using AI tools.

You’ll grasp why seeking easy no-code solutions often leads to mediocre AI outcomes. You’ll learn the vital role critical thinking plays in getting powerful results from generative AI. You’ll discover actionable techniques, like using frameworks and better questions, to guide AI. You’ll understand how investing thought upfront transforms AI from a simple tool into a strategic partner. Watch the full episode to elevate your AI strategy!

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What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode.

Christopher S. Penn – 00:00

And the thing is, when I read what they’re trying to do, they seem to have this idea that no code equals no work. That it’s somehow magically just going to do the thing. And I can understand the past tense aversion to coding because it’s a very difficult thing to do.

Christopher S. Penn – 00:49

Katie Robbert – 01:15

It’s… I think we were talking about this last week because I was asking—and I wasn’t asking from a ‘I don’t want to do the work’ standpoint, but I was asking from a ‘I’m not a coder, I don’t want to deal with code, but I’m willing to do the work’ standpoint. And you showed me a system like Google Colab that you can go into, you can tell it what you want to do, and you can watch it build the code. It can either keep it within the system or you can copy the code and put it elsewhere. And that’s true of pretty much any generative AI system.

Katie Robbert – 02:04

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss codependency on generative AI and the growing risks of over-relying on generative AI tools like ChatGPT.

You’ll discover the hidden dangers when asking AI for advice, especially concerning health, finance, or legal matters. You’ll learn why AI’s helpful answers aren’t always truthful and how outdated information can mislead you. You’ll grasp powerful prompting techniques to guide AI towards more accurate and relevant results. You’ll find strategies to use AI more critically and avoid potentially costly mistakes. Watch the full episode for essential strategies to navigate AI safely and effectively!

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Christopher S. Penn – 00:00

We have three areas where we do not just ask generative AI for information because of the way the model is trained. Those areas are finance, law and health. In those areas, they’re high risk areas. If you’re asking ChatGPT for advice without providing good data, the answers are really suspect. Katie, you also had some thoughts about how you’re seeing people using ChatGPT on LinkedIn.

Katie Robbert – 00:55

Every post starts with, “So I was talking with ChatGPT.” “ChatGPT was telling me this morning.” And the codependency that I’m seeing being built with these tools is alarming to me and I’m oversimplifying it, but I don’t see these tools as any better than when you were just doing an Internet search. What I mean by that is the quality of the data is not necessarily better.

Katie Robbert – 01:49

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss navigating the pressure of AI transformation and competitive parity.

You’ll learn why chasing AI trends without a clear purpose can harm your business. You’ll discover how to distinguish between merely optimizing current operations and driving real innovation. You’ll understand the importance of grounding your strategy in actual customer needs, not just competitor activity. You’ll explore how to assess new technologies like AI without getting caught up in hype. Watch the full episode to gain clarity on making smart AI decisions for your company!

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Christopher S. Penn – 00:00

We both had strong reactions to this, and I I’m happy to share mine in a little bit, but I wanted to get your take on this person’s request. How do I use AI to to catch up to where the rest of my industry is right now?

Katie Robbert – 00:49

Versus looking at your own environment, look at your own home. What you have, and saying, you know what? This is good. This suits me. And that’s the challenge I have when I hear things like that, of, do I need—I mean, I I went through this myself a couple weeks ago. We talked about it when we talked about MCPs on the podcast. It started with, am I falling behind?

Katie Robbert – 01:37

It’s not where I’m needed. And so when I see even bigger initiatives to try to keep up with the industry as a whole, my first question is, why? What is it that is going to benefit your company

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss the problem with buyer personas and how to master B2B marketing with smarter audience targeting. You’ll learn the critical differences between ideal customer profiles and buyer personas—and why using both transforms your strategy. You’ll discover how to ethically leverage AI and data to identify hidden pain points before prospects even recognize them. You’ll explore practical frameworks to align your content with every stage of the customer journey, from awareness to retention. You’ll gain actionable tactics to avoid common pitfalls and turn casual viewers into loyal buyers. Watch now to revolutionize how you connect with your audience!

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What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode.

Christopher S. Penn – 00:00

Actually, I want to dig into this, Katie, and I want your take. What’s the difference to you between an ideal customer profile and a buyer persona? A lot of people use those terms interchangeably, but they may or may not mean the same thing. What’s your take?

Katie Robbert – 00:28

The challenge I see in B2B marketing is many people create buyer personas, which is great, but there are assumptions baked in that this person already fully understands the problem and that you can solve it for them.

If you’re using your buyer persona to do a content strategy—to create content or evaluate your marketing—you’ve already skipped over awareness and consideration. You’re at the buying stage now.

When we beta-tested our ideal customer profile service, our friend Brooke Sellis from B Squared gave us her buyer persona playbook to compare against the ICP we built. That’s where we saw the disconnect—her playbook assumed everyone was already in the pipeline and knew the problem.

Our ICP analysis is meant to help marketers approach people who may not even know there’s a problem yet. You create content that resonates so when they *do* identify the problem, they enter your buyer’s journey. The ICP gets to them before that.

The challenge with buyer personas is they focus too much on someone already knowing what’s wrong and looking for a solution. In marketing, 99% of the time, they don’t know there’s a problem—or the

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss MCP (Model Context Protocol) and agentic marketing. You’ll learn how MCP connects AI tools to automate tasks—but also why technical expertise is essential to use it effectively. You’ll discover the three layers of AI adoption, from manual prompts to fully autonomous agents, and why skipping foundational steps leads to costly mistakes. You’ll see why workflow automation (like N8N) is the bridge to agentic AI, and how to avoid falling for social media hype. Finally, you’ll get practical advice on staying ahead without drowning in tech overwhelm. Watch now to demystify AI’s next big thing!

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What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode.

Christopher S. Penn – 00:00

Katie Robbert – 00:13

Problem number two is, yes, you post things typically ahead of when they become more commonplace announcements. I saw a post this morning that I shared with you about MCP and agentic marketing processes, and how it’s going to replace your SEO if you’re doing traditional SEO. For some reason, that raised all of my insecurities and anxieties. Oh my gosh, I really am falling behind because I like to tell people about getting their foundation squared away. If I’m being really honest with myself, I think I focus on that because I feel so lost when I think about AI, agentic processes, MCP, N8N, and all these other things. So I’m like, let me focus on what I know best.

But I am now in the boat where I feel like my boat is trailing behind the giant AI yacht. I’m dog-paddling to try to keep up, and I’m just not there. So help me understand a couple of things. One, what i

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss Retrieval Augmented Generation (RAG). You’ll learn what RAG is and how it can significantly improve the accuracy and relevance of AI responses by using your own data. You’ll understand the crucial differences between RAG and typical search engines or generative AI models, clarifying when RAG is truly needed. You’ll discover practical examples of when RAG becomes essential, especially for handling sensitive company information and proprietary knowledge. Tune in to learn when and how RAG can be a game-changer for your data strategy and when simpler AI tools will suffice!

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What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode.

Christopher S. Penn – 00:00

Christopher S. Penn – 00:02

Christopher S. Penn – 00:06

Christopher S. Penn – 00:07

Christopher S. Penn – 00:09

Katie Robbert – 00:17

Katie Robbert – 00:41

Katie Robbert – 00:44

Katie Robbert – 01:05

Katie Robbert – 01:07

Christopher S. Penn – 01:09

Probably one of the most well-known and easiest-to-use systems like this is Google’s free NotebookLM where you just put in a bunch of documents. It does all the work—the technical stuff of tokenization and embeddings and all that stuff. And then you can chat with your documents and say, ‘Well, what’s in this?’

In our examples, we’ve

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss the ethics of AI and ethical dilemmas surrounding digital twins and AI clones. You’ll discover the crucial ethical questions surrounding digital twins and AI clones in today’s rapidly evolving digital world. You’ll learn why getting consent is not just good manners but a fundamental ethical necessity when it comes to using someone’s data to create a digital representation. You’ll understand the potential economic and reputational harm that can arise from unauthorized digital cloning, even if it’s technically legal. Tune in to learn how to navigate the complex ethical landscape of digital twins and ensure your AI practices are responsible and respectful.

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Christopher S. Penn – 00:00

We’re not going to go into the technicals of this, of how you do this. Katie, you want to talk about more why or why not you should do this. And I’ll preface this with my absolute favorite clip from Jurassic Park.

Katie Robbert – 00:46

Christopher S. Penn – 00:47

Katie Robbert – 00:52

I think that’s a very narrow way of thinking about it because that assumes, oh, I don’t want to pay for Chris Penn’s time. If I create his digital twin, I can get all the consulting I need. I personally don’t think that’s how people are thinking about it. Hey, if I can clone a Chris Penn, I don’t have to pay him for contributed content. I can then say, Chris did this thing, or this is Chris’s voice or whatever it is, or probably more nefarious things

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss offsite optimization for generative AI.

You’ll learn how to rethink your offsite SEO strategy to effectively engage with AI models. Discover how to identify the crucial data sources that AI uses to inform its knowledge. You will understand why traditional SEO metrics are becoming less relevant in the age of AI and what truly matters for offsite success. Prepare to revolutionize your PR approach and ensure your brand is recognized by the AI systems shaping the future. Watch now to gain the offsite AI optimization advantage.

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What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode.

Christopher S. Penn – 00:00

In this week’s In Ear Insights, this is week three, part three of our optimizing your content and your marketing for AI. You know, people call it SEO for AI and a variety of tongue twisting acronyms. This week we’re talking about off site, which I feel like is probably the most accessible for folks because it’s the least technical and it is very familiar ground.

Off site AI optimization is essentially how can you be in as many places as possible as often as possible so that your name, your brand, and your content are duplicated as many places as AI crawlers grab their data from to build a training dataset library. So Katie, when we talk about going out into the world, what comes to mind for you for making that work and for being as many places as you possibly can be?

Katie Robbert – 00:58

You know, it’s funny because you just said something to the effect of it’s the most accessible or it’s the easiest. And I disagree because I feel like it’s the one that’s the least in your control. So, you know, when we talk about off site, we’re talking about getting on lists and guest posts and other people mentioning you.

And it’s not enough to just post about yourself on LinkedIn a couple of times a day. Sure, that’s part of it, but that it’s much more than that. And so, when I think about off site, I still think, okay, number one, I still have to have really good content, which is where we started this series that’s useful and appeals to my audience. So you can’t skip that step and suddenly just say, you know what?

Katie Robbert – 01:54

I’m gonna get on a bunch of who’s who lists or top 10 lists or whatever, because without that content as your fo