How Executives Actually Talk About AI

AI is everywhere. But what does it mean for your business? Gartner is the world authority on AI with more than 200,000 client conversations and more than 6,000 written insights on AI in 2025 alone. Leaders across the C-suite just like you are partnering with Gartner to turn AI ambition into impact. Go to Gartner.com/AI to learn more. Welcome to Gartner ThinkCast. I'm Karen Stokes-Lockhart. Today, we're diving into what executives talk about when they talk about AI. Pulled from one of his recent standout conference sessions, Gartner VP analyst Nate Suda will cover how executive discussions about AI are evolving and why that evolution matters. He'll break down three distinct but overlapping conversations. ROI, workforce, and operating philosophy. And what they reveal about how AI is redefining not just technology strategy, but the very structure and design of the enterprise itself. You'll learn what it really means to become an AI-shaped organization. Now here's Nate Suda. Alright, we got an interesting one here. What executives talk about when they talk about AI? What do executives talk about when they talk about AI? What are we talking about? Again, I promise we won't get into unquestioned questions or maybe we will. But in all seriousness, what we are seeing is that the way that C-suite talk about AI is changing. CEOs have much bigger expectations of AI. It was a bit like two years ago when we were talking about AI. The CEO was way back there trying to pull them along and get on the train. Now, all of a sudden, for many organizations, they are way out in front. We are going to be talking about that and we are going to talk about what that means for CIOs. We have three sections. We are going to talk about new conversations on value. The way we see the value conversation evolving in the C-suite, we will talk about the AI-shaped organization and the near-term structures and mid-term implications. Let's start going with new conversations on value. I have to warn you, the way I tend to present, we are going to jump straight in. We are seeing three C-suite conversations on AI. I am going to tell it in terms of a story, in terms of what was happening in 2024 and 2025 and now going into 2026. In 2024, the C-suite conversation was all about ROI. That conversation is continuing. That happened last year, it is never going to stop. That is going to continue. As C-suite is talking about ROI, they said, wait a minute. This is going to impact the workforce and we need the workforce on board to get that ROI. In 2025, a new conversation, immersion, that was about the workforce. That is continuing. We will hear more about that this year. What we are noticing is that now, at the very tail end of last year and going now into 2026, we are seeing a new conversation in the C-suite emerge. This is an emerging one. It is a different one. We are calling this the operating philosophy conversation. The organizing question around each of these conversations is a little bit different. With ROI, it is straightforward. What is the ROI? With the workforce, what about the people? With the operating philosophy, that is different. That is how will we win? That is a very different conversation. We see that the person or the role who is at the center of these conversations, not exclusively, but primarily is different. With ROI, it is very much around the CFO and the CIO. With the workforce, it is very much around the CHRO, Chief HR Officer and the CIO. It is the CEO who is at the focus of that operating philosophy conversation. What I think is very interesting is that when the CEO asks that question, how will we win? If the others members of the C-suite are in that ROI conversation, that is where their heads are. What they hear is how do I deliver an AI initiative that is going to give me 20% financial return. This is a very different question or objective than the question that the CEO is asking. They are asking something very different. They are not talking about financial health, which is the focus of the ROI conversation. They are talking about competitive strategy. I think that is a strange way to describe the workforce conversation. When we hear this conversation in the C-suite, the questions that emerge, the next level of questions, or what about tacit knowledge, what about experience, what about skills, what about attrition of knowledge in the organization, what about pipeline of leaders and development and our workforce. Are we making our organization brittle or stronger, more brittle or stronger? It is actually a question of organizational resilience. All three of these have their place. They are all important. They all have the same objective, which is organizational longevity. They are very, very different questions. They have very, very different objectives. That means very, very different things for CIOs. Another way to talk about this is this slide, which some of my colleagues call the underwater camel slide. I lived in Scotland for 10 years, so I like to call this the Loch Ness Monster Slider, the Nessie slide. What this is trying to show you is that we have had disciplines of management, philosophies and company excellence over the years. We had a TQM in Lean. Lean was very specific about how do we improve the efficiency of manufacturing or operations. But in the 2000s, we were all six sigmaing everything, whether or not we were near a factor or not. I guarantee all of us in the 2010s were in an agile organization, even though it maybe had nothing to do with software development. Adjai was about the efficiency of software development, very practical, but it very quickly became this is how we operate as an organization. We saw some things similar with that with digital transformation, but what we're seeing with AI is something very similar emerge. AI is kind of moving in management speak from a very discrete set of technologies and practices and processes to how we operate as an organization, how we do things around here. So the ROI conversation is interesting. The big question is where do I invest to create financial return now? We have to ask this question. What's interesting about this conversation is it's very tangible. It's intentionally narrow. It's very specific. It's very concrete. It's very disciplined. And this is good. In some organizations, this means that actually this is causing some organizations to pull back on investments, sometimes justifiably, on AI because they can't see how this is going to turn into a concrete ROI in the future. So there's a different there's a different test here. Now when we look at the workforce conversation, this is it's not about reassurance, but it's recognizing that work and skills are evolving. How do we retain institutional knowledge and stay resilient as an organization? As we implement AI, is this going to change? It's going to impact negatively, as usually the question, our ability to operate, particularly in terms of skills and knowledge and people. But when we get into the operating philosophy conversation, it's different. The question is, it has a very different perspective. It says, the world around me is changing. How do we succeed and deliver mission objectives, particularly if we're in public sector, in an AI-shaped economy? It's beginning to think of AI less of something that we have internally that we can use and more like an extrinsic factor that is impacting the organization. The world around me is changing. How is this going to change? What our company is and what we have to do. It's thinking about it as an extrinsic factor that creates a competitive necessity that means that we have to act. And it changes a practical examination of the firm's management DNA. How do we do things around here? This is increasingly how we see CEOs talk about AI. And this is very, very different than how do we get a 20% financial return. Now, what this means, very practically, is that there are new tests of AI success. With the ROI conversation, the test is, can the financial outcome be evidenced? And this is a high bar. And this is a test that's not going to go away. It continues. We've got to pass this test. But if we only pass this test, we're not going to succeed. There's another test that we have to pass. And that is, is the organization becoming stronger or more brittle? And then finally, the last one is, are there signs that the organization is structurally changing? AI is changing the boundaries between departments, teams, functions within the organization? Are there signs that this is changing the shape, the functional organization of the workforce? And that's what we see when we talk a lot to CEOs. And what this sometimes manifests itself, and I was talking to some of you earlier, the past couple of days they say well. you know, my executive teams are making some pretty wild promises about AI. And this is what we think is behind it. Now, what this means very practically. So these are three tests for success. But what this very practically means is that now in 2026, if your focus of AI value is answering that first question, can the financial outcome be evidenced? If that's the question or your primary question or your only question that you're trying to answer, then you're already behind. Now, those are the new conversations on value. What does this AI-shaped organization look like? What are we seeing? Looking to stay ahead of the competition, attend a Gartner conference. Our conference has provided attendees with invaluable insights and ideas. And the content is always relevant in tailored to key issues being faced by leaders in every core business area. Be it finance, HR, sales, IT, supply chain, or marketing. During a set of Gartner conference to learn about emerging trends and gain new perspectives that you won't be able to find anywhere else. There's a few terms that we're going to use, the operating philosophy competitive strategy and operational transformation. Change requires a belief, a goal, and a process in each one of these terms aligns to those. These are similar concepts, but the operating philosophy sets the belief system. What the organization can become? Which, of course, leads to competitive strategy, which is, how do we win? When finally, operational transformation institutionalizes that operating discipline. How do we become? And we're going to talk about for a little bit is this first one. What the firm can become? We're seeing something that we call belief ahead of measurement. Now, this is not particular to AI. This is leadership at the frontier. This happens with every C-suite in every organization. But it's worth highlighting here to show the difference between that operating philosophy conversation and the ROI conversation. CEOs, they are betting on AI. A lot of them are. They're betting on AI, but they're not betting on it in the abstract. They're saying, you know what? I see pockets of evidence. I see pockets of success in my own organization. I see pockets of success in colleagues at other organizations. I'm hearing about that. And maybe I'm seeing it in other trusted sources. And it's incomplete, but I'm seeing enough evidence that I can triangulate between these. And as I triangulate between these, this is creating a belief of what this can be for our organization. And that belief creates a thesis that if this human plus systems, they can reliably expand what roles can handle, then the operating model, the strategy, and capital allocation needs to change. A head of the ability for us to manage this. Because remember, this is an extrinsic force that requires a competitive necessity. Now, that belief requires a goal. What does that goal look like? What we're seeing is that this leads to some archetypes of the organizations. The question is, what are we going to use AI to optimize for? What does that look like in the organization? We're beginning to see some of these emerge. So we're seeing CEOs starting to organize for competitive and mission outcomes. And the first one that we're seeing is higher-less growth. This is the principle that we can keep our head count flat, but we can continue to grow. Now, what is that going to look like? We're not exactly sure. Is this going to work? Maybe, maybe not. Probably. There's a couple of jackals. We can see the disconnect already. How is this going to work? Is this going to be that we can keep our head count flat and we're going to grow like this? Or do we have to grow, but maybe grow the head count a little bit less? What does that look like? This is still-- we're trying to figure this out. But this is the belief ahead of measurement. This is what we're seeing CEOs organize for. And if you read earnings calls, which is where a lot of this evidence is coming from, you will see this kind of language again and again and again. I'll show you some examples later on. So this is the first archetype that we're seeing. Now, the next archetype that we're seeing, well, we're not exactly sure yet. We're seeing one. We expect that more will emerge over the course of this year. We've got some speculations on what they might be, but this is what we're actually seeing. We're seeing that that's a higher-less growth emerge now. We expect others to emerge, but selecting this is going to become a core CEO decision. It's a core CEO strategy decision. And if we talk about higher-less growth, higher-less growth is an interesting one. And there's another feature of these conversations that very often they happen at the same time without the individuals realizing that there are very different conversations happening. I'm sure you've experienced this in your own management teams, right? Because if we're talking about higher-less growth, if I'm looking at this from the ROI lens, I have the hypothesis that I can have lower labor costs, but I need evidence. So I'm looking for the business case. Now, some in your management team are going to be looking at higher-less growth from this perspective. In fact, probably this gentleman right here who laughed when I said, "Is this real or is it not?" But if I'm looking at it from the workforce lens, I'm seeing something very, very different. I'm seeing actually a risk to institutional knowledge and burnout. This is a very different perspective that I have. And if I'm the CEO and I've got that operating philosophy lens, I see a structural imperative for long-term competitiveness. Maybe if I look at the ROI lens from the perspective of the operating philosophy, maybe it doesn't work exactly yet, but we have to figure out a way to make it work. That's the perspective. And we'll see how that plays out. Now, what's interesting is that when these are not kept clearly distinct, they create a lot of conflict and a lot of confusion. We see this in a lot of boards where it's not clear that we're operating at different levels. There are different assumptions going on, and particularly in this topic. And these three conversations, they exist because of three different anxieties, cash, capability, and competitiveness, all essential for the organization, but depending on where you're looking, you're seeing something different in that higher-less growth. Now, I said that I was going to show some hypotheticals of what could those outcomes look like. So, higher-less growth is at the top. We just talked about that one. Trust advantage. This is an interesting one. Will we, as an organization, use trust and trust in AI, trust because of AI, or trust in our AI systems? Will we use that as a way to compete, as to provide competitive, distinctive differentiation? Or will we use AI for risk and shock absorption, particularly with the workforce and with roles and with skills? There's others here, speed as advantage, price leadership, quality, market shaping, or mission change. These ones that are at the bottom here, the five at the bottom, these are kind of classic, Michael Porter, five forces kinds of strategies. What's interesting about the ones at the top is that these ones are very distinctive or could be very distinctively because of AI. And the fact that new competitive positioning will emerge is not that crazy to think about. The classic competitive positioning is I compete on quality, price, or niche. I've got the best product, I've got the cheapest product, or I provide a product that nobody else provides. That's kind of classic competitive positioning. But in digital, of course, another one emerged. And that was customer experience. Of course, customer experience didn't not exist before that, but it kind of became its own thing with digital. We think something else is going to emerge, or maybe some other things will emerge with AI. So there'll be new competitive positioning, not just price, not just quality, not just niche. So there's going to be other ways to win. Now, I'll give you some examples of where we're seeing this language. So the CEO of Air Lequeed in their earnings calls, they say, "We're deploying AI for structural transformation." This is not ROI, this is something much bigger. The CFO of the bank, New York, Melon says, "What you're going to hear from us is using AI to run the company better." And in context, this doesn't mean just we're going to improve processes. This is quite a significant step change. That's the intention here. In this article from the Wall Street Journal, we're seeing some interesting language, a very strong bias against the reflective response. So we're beginning to hear belief language here. These are words of belief, not necessarily evidence, going back to that belief ahead of measurement. And then this last one, those words are explicitly. Part of that thinking is the belief that AI will. There's a belief happening here, which is driving a new way of seeing the firm. Okay, so what are the near-term features and the mid-term implications? In the near-term, these are some of the things that we're seeing. We've got some defining features. There's three. Human plus as the basic unit of work. The second is a structural recomposition of work. And then capability per person, not just capacity or complexity. Talk about each one of these in turn. So human plus is the basic unit of work. So every major management doctrine, it starts with redefining what counts as the basic unit of design or organization. With lean, we talked about value streams, not isolated tasks. With agile, we talked about cross-functional teams, not individual contributors. And with AI, we're talking about human plus, not the un-aided person. So we're talking about a change. It's very similar to analogous in many ways to these of the past. And so then the question that we have to ask ourselves is, not how can this person perform their tasks more efficiently? That's capacity. But what should this role be responsible for? Remember that diagram of the software engineer expanding out into adjacent roles? That's what we're seeing here. The example that I like to give is the contact center and inside sales. Contact center and inside sales, these are parts of the organization that are speaking to your customers every single day, all day long. But if we save time in the contact center, even if we save them all the time in the world, they're not going to be able to do upsell. Why? Because they don't have the skills, they don't have the experience, they don't have the knowledge, they don't have the systems, they don't have the processes, they don't have anything that they need to do the upsell. But what we're seeing from organizations, many examples where they're saying, well, you know what? For the contact center, we're going to give them a hyper personalized prompt so that when they are resolving the problem with the customer, they can start that conversation and say, hey, do you know what? We see that you're interacting with these products and services, we see that there's some others that you personally would be interested in. Would you like to have that conversation? That's just a very simple example. But that allows them to start the conversation of upsell. And sometimes we're seeing a lot more than that. Now, what that means when that happens, is that the work over here begins to move from inside sales into the contact center. And then as the work is moving, so the work stays the same, but it's moving, we step back, executive step back and they say, wait a minute, the work that was being done here, a lot of us being done here now, do I need this function? The question of what happens to the people is an entirely separate conversation and that's how we see it play out. But do I need this function? Because a lot of the functions that exist in our organization exist because and in support of the technology that we have. So we see that question of what should this role be responsible for changing? We see the structural decomposition of work, or deliberate, just like I was just talking about, a deliberate decomposition of work and structure. How work is divided across roles, teams and functions? The work stays the same. Some cases the work is going to be new. Some cases the work is going to be more. But in many cases, the work is going to stay the same. If we're an automotive company, 10 years now we're still going to be making cars, we're still going to be closing the books. A lot of the work is going to stay the same. But where the work lives, who does the work, is going to change. This is Mike Ulster. He's the CIO and CTO of Mantec. He's a professional services firm. And what he and Mantec have realized is that they have a lot of examples of AI with a call blue money. This is productivity. This is efficiency. These are good benefits. But it takes structural transformation, like what I was just talking about, to turn that into green money, to hard savings. And that comes through critical business changes, process re-engineering, redesigning teams, redesigning staffing. And this one, I quite like this one, is the capability per person, not the capacity or the complexity. There's this quote from Sam Altman, where he said this a couple of years ago, where he said, "I and my tech CEO, friends and I, we have this bedding kind of thread going on on WhatsApp." And he says, "We're bedding when is going to be the first one person billion dollar company." Now, when I first read this a couple years ago, I thought, "Well, what Sam is talking about is efficiency. Individual people can become so much more efficient that they can do much, much greater amounts and they can build this one person billion dollar company." Now, that might have been what Sam was talking about. But as I read this quote now, what I think what he was foreshadowing was something very, very different. Just like that software engineer is expanding into the adjacent roles, but individuals can do more, not just more capacity, but more capability. And we're seeing this in a lot of different roles. Now, what does this mean for midterm implications? Again, we've got three. The first is that talent asymmetry becomes a principle for workforce restructuring. The second is that functional boundaries change. And the third is that spans of control and layers are reset. Now, the first one, talent asymmetry becomes a principle for workforce restructuring. Some people, and we've seen this for some time with AI, benefit more than others with AI. Some people benefit, substantially. Some people actually get slower if we're going to use that word. I don't like that word, but it's an easy way to describe it. There's a negative impact because of AI. Now, this has an organizational design implication. It's not necessarily a fairness implication. It will change how we organize the workforce. And what we see is that from low experience to high experience staff, the human skill and ability will increase. But when you layer AI on top of that, we see something, we don't see that same straight line. We see this kind of a curve. We see significant impact for the lowest skilled workers in the organization. They come up very, very quickly. They learn from AI. Those, at the very highest experience, they become much more creative. They also have a very high impact. What happens in the middle? It's a bit softer. When I speak to some sweet teams, they say, "Well, maybe it's like that. Maybe it's a little bit below the line. We're not sure." But what we see organizations looking at is either end of the experience spectrum. That's where AI is having the biggest impact. And this is going to have an impact on how the ideal role for the workforce in different functions. This is likely to change in the future. Thanks for listening to this latest episode of ThinkCast. That was Gartner VP analyst Nate Suda. To learn more about this topic and to register for a Gartner conference near you, follow the links in the description. ThinkCast will be back where we listen to podcasts a week from today. In the meantime, please rate, review, subscribe, and share with a colleague. So neither of you will miss it. ThinkCast is a production of Gartner. This podcast may not be reproduced or distributed in any form without Gartner's permission. It consists of the opinions of Gartner's research organization, which should not be construed as statements of fact. 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