While there’s no evidence that business leaders are outsourcing the most important decisions to AI, there are reports that many executives are relying on AI to make many — in fact, most — of their decisions. The implications for communications could be huge.

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The next monthly, long-form episode of FIR will drop on Monday, May 25.

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Disclaimer: The opinions expressed in this podcast are Shel’s and Neville’s and do not reflect the views of their employers and/or clients.

Raw Transcript

Neville: Hi everybody, and welcome to episode 512 of For Immediate Release. I’m Neville Hobson.

Shel: And I’m Shel Holtz. The inspiration for this week’s report came from a post Brian Solis wrote recently. In it, he argued that AI isn’t just changing work — it’s rewiring how executives make decisions. Once Brian put that in my head, the trend started standing out in other things I was seeing. I’ll summarize the numbers and what they mean for communicators right after this.

The numbers Brian pulled together are honestly alarming. A Confluent study of UK private sector leaders found that 62% of executives now use AI to make the majority of their decisions. That’s not some — it’s the majority. 70% say they second-guess themselves when AI disagrees with them, and 46% say they rely on AI more than their own colleagues.

On the U.S. side, SAP’s research found that 44% of C-suite executives would reverse a decision they had already planned to make based on AI input. 74% place more confidence in AI advice than in the advice they get from family and friends. Meanwhile, McKinsey reports that 92% of companies plan to increase their AI investment over the next three years, but only 1% — 1 percent — describe themselves as mature in deployment. The money to pay for AI and a sort of blind trust in its abilities are racing ahead of the internal competence to use it. Now, I want to be clear before I go on. I’m not anti-AI, Neville — you know this. Anyone who listens to the show knows I’ve been beating the drum for AI as a tool for communicators and for business in general for a long time.

AI as a thinking partner, a research assistant, a stress-tester for ideas — that’s enormously valuable. But there’s a meaningful difference between using AI to inform a decision and using AI to make the decision. And Brian puts this well: AI is becoming the new executive influencer. The problem is that it hasn’t earned that role, at least not yet.

So let’s talk about what this means for those of us in communication, because the implications are everywhere. Start with employee trust. The implicit deal between an organization and its workforce is that the people at the top got there because they have judgment and experience and pattern recognition that the rest of us don’t have — or at least they’ve been able to employ it really well and get noticed by the people who promote you into those leadership decisions.

That’s the story leadership tells, and it’s the story employees buy into. Now imagine the all-hands where the CEO announces a major restructuring, and somewhere in the Q&A, or worse, on Blind or Reddit a week later, it comes out that the decision was essentially handed to a chatbot. What happens to confidence in leadership? What happens to engagement? What happens to the social contract that says, follow me because I know where we’re going?

You can’t credibly ask people to bring their full selves to work, as they say, while you’re outsourcing your own judgment to a language model. Now extend that to external stakeholders — investors, customers, regulators, the board. They’re paying, and in a lot of cases they’re paying a lot, for executive judgment. If a strategic call goes sideways — and you know that happens — the explanation that the AI suggested it isn’t going to land well.

It’s going to sound like an abdication, because it is an abdication. And from a crisis communication standpoint, “we trusted the algorithm” is one of the worst defenses I can imagine. I don’t expect that anybody’s going to say that, but it doesn’t mean it’s not going to come out. Just ask anyone who’s worked an aviation incident, a financial services failure, or a healthcare AI misfire. Imagine the reaction when either the leader tells people, or they learn through a third party, that the afflicted stakeholder hears, “Well, that’s the decision the AI told me to make.”

And there’s a third implication that I think communicators need to surface inside our organizations: the erosion of dissent. I find this particularly interesting and disturbing.

Confluent found that 65% of leaders say decision-making has become less collaborative since adopting AI. The Harvard Business Review just ran a piece arguing that consensus is dead in the AI era. That may be — but debate isn’t consensus. Debate is the friction that exposes bad assumptions. It’s what didn’t happen at that auto manufacturer — I think it was Volkswagen with their emissions standards. They didn’t have the psychological safety to feel safe in dissenting against the decisions being made. In this case, we’re not even looking forward at the leadership level in some cases. If AI is pushing aside the colleague who would have pushed back, whatever process your organization had for dissent just stops functioning. And when dissent dies, so does the early warning system communicators rely on to spot reputational risks before they get out of control.

So what do we do? A few things. We push for governance — and if you already have a governance model, push to revisit it. Your governance needs clear declarations of which decisions AI informs versus which ones it actually makes. We coach our executives to talk publicly about how they actually use AI, with appropriate humility, before the question gets asked for them.

We build the internal narrative that human accountability is non-negotiable, no matter how good the model gets. And we keep reminding leadership that machine confidence isn’t the same as strategic clarity. Brian’s right: AI is a test of leadership. It’s also, increasingly, a test of communication. Neville?

Neville: Well, just to set my position clear on this, too — I’ve been a drum-beater for AI as a research assistant, as a useful tool, since GPT first came out. The initial kind of hysterical enthusiasm was tempered over time, but I use the tool every single day in what I do for work, or for pleasure for that matter. So it’s something I believe strongly in. But I’ve got this, how could you say, in the back of my mind always — this thought that I don’t accept blindly anything the AI assistant tells me. If I’m researching something, for instance, I’m going to make a recommendation about something, let’s say, or I’m writing a report or even something relatively simple like an article for the blog. If I felt I wanted to say this and it’s telling me that, that’s a simple decision: I’m either going to follow it or not. Typically when that happens, I’ll ask it questions to further that angle. But this is something else, what Brian writes about. And The Register — I’ve read their piece — tempered with a bit of hysteria, it seems. I mean, this is a very alarmist piece, or argument, you could say. If it’s saying, as it is — the survey that The Register reports on — 62% of leaders of private sector companies, and according to The Register that’s owners, founders, CEOs, managing directors, the C-level leaders of various types of companies. They didn’t say sizes. But they use AI to make the majority of the decisions, which leads to some of the alarm bells ringing that you outlined. What if it gets out that the AI made a decision when something goes south? You could flip that. What happens if it gets out that an amazing decision that led to the company being massively successful was actually made by an AI?

I think it’s inevitable you’d have that sort of focus on it alongside more sane arguments, perhaps. You could argue, well, that CEO is pretty smart that he used an AI to help him do that — as opposed to the other side, which is, gee, we’ve got to fire this guy, he used an AI and it went wrong. So you’ve got to put some balance there. Also, I think you mentioned this earlier, and I agree with you, that there are two angles to every question we might ask about this. One is internal, within an organization, and the other is external. So it is an interesting point. And one thought I had in my mind, the pragmatic question: if a leader changes a decision he or she has made because the AI assistant suggests something different, who actually owns that decision in the end? In fact, whether he changes his mind or not, if the AI said, “I recommend you should do this, and here are the 10 reasons to support that idea,” that are different from what the leader was going to do, and he or she made the changed decision based on that — who actually owns that decision? Or, as I asked myself, is that really the most important question to be answered? But it’s still a natural one to arise. And yes, we could run through a long list of the implications in this scenario for the employees of the organization, other stakeholders, and the external audiences. But I have to say Brian’s arguments are well made. He sets the scene — the executives are relying heavily on AI. From there it goes more into the alarm function.

Judgment being reshaped — the judgment exercised by a leader is obviously so flaky that it can be reshaped by the AI assistant. In other words, that individual is willing to let that happen. I wonder whether this is all part of, perhaps, the speed with which people are expecting decisions to be made. Indeed, something I was doing this weekend — we’re on a holiday weekend here, by the way, so I had time to do this — that was nothing to do with work. It was a personal thing I was involved with that required analyzing a document that had a lot of financial information in it. I asked my AI assistant, in this case Claude, as part of my experiment with Claude, to summarize it and pinpoint the key aspects. It did that in about 20 seconds. And that was enough for me to know what questions I would need to ask it next, to develop it the way I want, rather than starting from scratch trying to do that. So there’s the benefit. But I think treating AI like a trusted advisor, to me, makes a lot of sense. And I’m trying to balance that thought with the alarmist approach — you know, this is a bad thing, all these terrible things are going to happen, and it will all come out. So how does that gel with treating AI like a trusted advisor? Although your point, I agree, it hasn’t earned the trust in the context of this conversation. So does it mean leaders are willing to override their own decisions or instincts based on AI input? Well, according to The Register, 62% have said they are, I suppose. If that’s true, I think we’re in trouble already, before this gets any further. So the real challenge — I think you’ll agree with this, Shel — is not the tech at all. It’s the leadership aspect, the human behavioral aspect of this, as is so often the case. When people talk about the relationship between the human and the AI and they just talk about the tech, it’s not — it’s a human issue. Cut through all the alarm bells and pluck out something which to me is extremely important, that really doesn’t get much airtime in Brian’s report at least: isn’t this really about the whole point of judgment? That someone in a leadership position in an organization is in that position partly because he or she is very good at exercising judgment in the work they do or the decisions they make. Are we saying that judgment is so fragile that an AI could just overturn all of that in an instant and lead all this? I guess my point is that I’m noting this. I listened to what you said. I haven’t read all the surveys you mentioned, or the other reports — the Harvard Business Review, for instance — I will. But I find this literally the worst-case scenario, and that’s being pitched as, you know, this is upon us, based on The Register, which, by the way, has a — let’s call it interesting — reputation over the years for some of their reporting. But this is very factual; their own report is actually quite well written. So what do we make from this then? Should we be worried? I don’t think we should, if we see this as simply something to note and look at as a communicator — let’s say the role you’ve got in ensuring that the CEO isn’t going to have his or her judgment completely overwhelmed by an AI. I just find the idea of that frankly ridiculous, in the sense of, well, not implying or even saying that this is the norm. It’s a result of surveys. There’s other research also supporting some of this, I think. But we should put it in perspective: this is, I guess, an inevitable discussion point that’s emerging at this stage in the development of AI and organizations. We’ve reported recently on this podcast how leaders are taking ownership of the AI deployments in their organizations. That doesn’t mean to say every company is doing this, because they aren’t. But we’re seeing that, and then we’re seeing other reporting we’ve commented on — that employees and other stakeholders related to an organization are unhappy with what’s happening with AI rollouts in their organization. So you’ve got all these mixed messages coming left, right and center, and now this. It doesn’t mean we should — oh my goodness — stop doing this, or have a meeting with the CEO and say, “What are you doing?” No, I don’t think so. But we need to note this nevertheless. I don’t believe this is something we should all get terribly alarmed about, to be honest, as long as we apply our own common sense to observing what’s going on and making sure we understand the CEO we’re supporting as communicators — let’s say the leadership teams — that this isn’t happening.

Shel: Well, I don’t think this is the most important issue we’re facing with AI. I do think it’s a time to worry. Now, I will say I don’t imagine that the CEOs leading the world’s biggest companies — the Jamie Dimons, the Josh Domaros, the Tim Cooks of the world — are using AI to make important decisions. And you have to wonder, because I don’t think they asked, in the survey they did, what types of decisions these CEOs are making. Are they the game-changing decisions, the most important decisions they have to make, or are they lower-level decisions? We talk about AI taking all that drudge work off the table. Are they allowing the AI to make decisions associated with that kind of work? But I think, as people — and CEOs are people — as they get accustomed to letting AI make decisions, it might get easier and easier to turn bigger and bigger decisions over to AI as time goes by. With any luck, AI is going to get better and better and may earn that trust. But this would cause that decision-making instinct that leaders have, based on their experience and their judgment and the other things that got them to that level, to atrophy. I mean, atrophy is happening elsewhere as a result of AI among some groups of people — the ability to write your own thoughts down, to craft your own email, to conduct your own research. As far as CEOs making good decisions with support from AI, I think support from AI is going to become table stakes. I think CEOs who don’t know how to use it are going to become dinosaurs in fairly short order — not necessarily the ones who have the job now, but I don’t think you’re going to see people getting promoted into that position, or hired into it, if they don’t know how to use AI for decision support and the other things we see AI being used for very effectively at leadership levels. And leaders are using AI, according to most of the research I see. I wonder, though, if they start turning more and more decisions over to AI, what is the board or the owner going to see as the value of the CEO? If most of this work — or much of this work, the majority according to that Confluent study — is being done by AI, does that mean the enormous salaries being paid to the people at the top of the organization are going to decline? Or does it mean that the role changes altogether, or maybe even ceases to exist in favor of some other model? And by the way, I’d love to see the same question posed to people at other levels of the organization, because this probably is not something confined to the C-suite, this turning decisions over to AI. I wonder how much it’s happening in middle management. I wonder how much it’s happening among frontline workers. If it’s at the same level, then it’s a company-wide issue that needs to be addressed, because there are going to be some problems that emerge if we don’t — I mean, along the Volkswagen lines with their emissions scandal. Dieselgate, exactly. Yeah.

Neville: That was Dieselgate, as it was dubbed. I mean, it’s a good point you make. I agree. And the point you made earlier, too, is actually a critical question: what kind of decisions are we talking about here? Is it on the scale of, let’s proceed with the merger with this company rather than that one? Or is it something like, should I fit in a stopover in this city on my way to that city to meet with these people and so forth and achieve these things? Is it that? Or is it even something more prosaic? You know, what do I get my wife for her birthday next week? I’ll have my secretary do it — but the AI could tell me. I mean, that’s ridiculous, actually. But it’s significant to know what kinds of decisions we’re talking about, because I’ve not seen it referenced. It’s implying — and people are jumping, obviously, on this — that these are the kind of organization-affecting major decisions that are suddenly at risk because an AI is doing it. I find that ridiculous, to be honest. So we need to know what kind of decisions.

Shel: Yeah. I mean, in my industry, there’s a go/no-go decision on pursuing a project. I cannot imagine, in my wildest imagination, in my organization, anybody turning that decision over to an AI. But what if somewhere in the industry they do, and end up pursuing a project that ends up being more trouble than it was worth? Somebody in the organization at that leadership level, who was involved in the previous discussions, would have known for various reasons, but the AI didn’t have the experience and the insight that that individual had. That could be a financial problem for the organization.

Neville: So the role of the communicator in all of this — and this is not to say that the communicator who works closely with the leadership teams, including the CEO and others in the C-suite, is involved in every single thing they’re doing. No, that’s not realistic, because they’re not. But the communicator’s role in preserving human judgment is the right question to ask. What is it in this context? Where do communicators fit in helping leaders balance AI insights with human insight and judgment and experience? Where do they fit in doing all of that? So the two angles I notice: internal comms — communicators act as sense-makers, ensuring context, ethics and human impact remain part of decision-making. Externally, they help articulate how AI is used responsibly in the organization, which is increasingly central to trust and reputation. That addresses the point you made about when it leaks and it gets out that AI did something. I think increasingly we’re going to see that point — articulating how AI is used responsibly in an organization — because the impact can be huge if rumor builds, which it would do: “the AI is making all the decisions in this company, and why do we need the CEO and all that?” So that’s a good role for a communicator to take on, and to be seen to be the person who is the “yes, but” person and the key advisor to leadership in these things, which strengthens the communicator’s role, in my view. So there are things we can do to address this. If this is as big a problem as these articles make out, I don’t believe it’s something we should lose any sleep over right now in the context of everything else that’s going on in the organization. But nevertheless, we’ve got respected sources — Harvard Business Review, we’ve got Deloitte talking about it, and others that we pay attention to because they’re credible publications talking about this.

Shel: Well, yeah.

Neville: Brian seeded an interesting discussion point, it seems to me.

Shel: Yeah. And let’s look at a very plausible scenario. Let’s say somebody sues the organization over a decision that the CEO made, or that leadership made, that affected them badly, and they feel they deserve compensation for that. In the U.S., anybody can sue anybody for anything. And we have seen some recent lawsuits. Look at the lawsuit that we’re seeing play out right now between OpenAI and Elon Musk.

Neville: Yeah.

Shel: And look at the records, the emails that have been surfaced in discovery. Look at the trials that have been held over lawsuits brought by the parents of children who killed themselves because they got encouragement or assistance from ChatGPT, and who sued OpenAI over that. What they got in discovery was access to the kids’ entire ChatGPT history. So you have a shareholder or a customer who sues the company, and in discovery, all of these things come to light — and that’s how it gets out. So I think even decision support has to be balanced with other input that you can demonstrate in a courtroom influenced the decision that was made, so it doesn’t look like the decision was completely outsourced to the AI. I think that’s an entirely plausible scenario in a lawsuit. So yeah, it’s something we need to consider. And as you say, and as I said, there are things communicators can do about this. One is making sure people are aware of the potential for this situation. And then, as I said, influencing the governance model so that it incorporates decision-making — if it doesn’t already have decision-making and decision support in the governance document, it needs to be added. And then making sure the leaders are talking about how they’re using it, so it never comes up that they’re using it to make a decision of importance in the organization — that it’s focused on using it in very effective ways.

Neville: Yeah. I mean, I think the picture you painted — lawsuits and stuff like that — are very possible, particularly in America, where, as you said, anyone can sue anyone for anything, usually for amazing sums of money, in the billions. So maybe what needs to happen in organizations that would address this, among other things, is keeping records. So that, for instance, in an organization that has deployed or rolled out AI tools such as chatbots — let’s say maybe their own version of something based on ChatGPT, whatever it might be — it needs to be known that those record anything you interact with on an AI. Whatever level you are in the organization, there’s a record kept along with anything else: emails, internal reports, you name it, they’re monitored and tracked in most organizations. And the fact that you could add to that picture even some of these automated note-takers, like Otter and others, that are commonly used in intrusive ways in Zoom meetings — and you hear stories of private Zoom meetings —

Shel: AI transcripts of Zoom meetings in which the decisions were made.

Neville: — where the outcomes are disclosed or leak out publicly because someone used one of these tools that summarized things, including the recommendations or suggestions if they were made by anyone. If that gets into a law case by the plaintiffs, that’ll be shown out of context — you can be sure of it. So, right.

Shel: Yeah. And that’s why a lot of organizations are saying to their employees, you can’t record these kinds of meetings.

Neville: Right. But someone will, and it’ll happen. So you need to head that off the path, as it were, and have your own structure in place and your communication surrounding it. So, for instance, you have to have very clear narratives around decision ownership, for example, that would help you in crisis situations. That’s the internal focus. Externally, you’ve got to communicate the kind of structure you have for human accountability — not “the algorithm said we should do this.” We can laugh about it, as I am at the moment, but imagine the reality of something like that happening. So I think these are all things that are plausible, I do believe, particularly in the U.S., I have to say — but hey, could be anywhere. It isn’t complicated to work out a plan of how you would prepare for things like this. But I’d rather look at it not as preparing for worst cases, although you need to. It’s just a switch — flip it over a bit and look at the benefits of all of this. And again, not solely the communicator: the individual leader has to be willing to go along with this, has to be willing to share some of the thinking he or she is doing and the discussions with the assistant, whether it’s an AI or anyone else, to realize that you can’t do this without full transparency, at least to your advisors, including the communicator.

Shel: Yeah, absolutely. And we will be back with a follow-up episode when the inevitable headline surfaces of a company that gets in trouble because it’s revealed that the CEO abdicated a decision to AI. Until then — actually until next week — that’ll be a 30 for For Immediate Release.

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