When Doug McMillon announced he was stepping down as CEO of Walmart after more than a decade at the helm, he didn’t blame the board. He didn’t cite personal reasons. He said something that should stop every senior executive in their tracks:

“With what’s happening with AI, I could start this next big set of transformations with AI, but I couldn’t finish.”

Read that again. The CEO of the largest company in the world; a leader who guided Walmart through the internet era, through supply chain collapse, through a pandemic, looked at what was coming and made a clear-eyed decision: the transformation horizon ahead didn’t match his own.

Around the same time, Coca-Cola CEO James Quincey said he could lead the company through the “pre-AI” phase, but that the next wave of “AI-driven growth” needed someone with fresh energy. Adobe CEO Shantanu Narayen, after eighteen years, framed his departure around the same idea: the next era of creativity is being “shaped by AI,” and new leadership should shape it.

Three CEOs. Three of the most recognized brands in the world. All saying a version of the same thing on their way out the door.

This isn’t a wave of high-profile executives burning out. It’s something more significant. It’s a cohort of experienced, accomplished leaders making a rational calculation that the technology disruption now underway is categorically different from anything they’ve navigated before — and deciding, honestly, that someone else should be at the wheel for the next leg of the journey.

That level of self-awareness deserves more credit than it’s getting. And it raises an urgent question for every other C-suite leader still in the chair:

What’s your honest answer to that same question?

The Data Behind the Signal

Before we get to frameworks, let’s establish the facts, because this isn’t anecdote. It’s a documented structural shift.

The numbers tell a story that goes well beyond a few high-profile departures.

CEO turnover hit record levels in 2025: a 16% spike in global departures from the prior year, more than 20% above the eight-year average. More than 1,200 U.S. CEOs left their posts in the first half of the year alone. Critically, this isn’t a story about underperformance. In the S&P 500, successions at top-performing companies jumped from 7% to 12%. Boards aren’t reacting to failure. They’re getting ahead of something.

The age data is where the AI signal becomes unmistakable: The average age of departing CEOs jumped from 55 to 63 in a single year. In July 2025, the average age of exiting CEOs hit 70.3, compared to 56.2 in the same month a year earlier. A retirement wave is underway, and AI is accelerating it. Boards aren’t just accepting these departures, in many cases they’re engineering them, actively skipping Gen X and moving directly to Millennial leaders for whom AI fluency is native, not acquired.

Here’s the wrinkle that most commentary is missing: not every experienced leader is heading for the exit. A recent survey found that 58% of Baby Boomers aged 62-plus said they are not currently considering retirement, a dramatic reversal from just a year prior, when only 11% said the same. The most common reason? They want to develop new skills. The best of this generation aren’t running from AI. They’re leaning into it. Which means the real divide isn’t generational. It’s between leaders who are engaging with the disruption honestly, and those who aren’t.

Which brings us to the real question: not whether AI is forcing a leadership reckoning—but how the leaders still in the chair should think about it.

A Disruption Unlike the Others

I’ve lived through several technology disruptions in operating roles; the internet’s first wave, the shift from print to digital, the rise of cloud and SaaS, the mobile platform shift. Each one was significant. Each one produced real winners and real casualties. None of them felt quite like this.

Here’s why this is different.

The internet disrupted business models and distribution. It reshuffled who owned the customer relationship and what information was worth paying for. But the core of what executives did — made decisions, managed people, read markets, allocated capital — remained fundamentally human. Technology changed the conditions. The decisions were still human.

I’ve watched this pattern play out firsthand. In the early days of the internet, I sat across from publishing executives who were genuinely unconcerned. “People will always want their morning newspaper. Magazines have loyal audiences that aren’t going anywhere”. The Internet platforms looked like novelties. They were not.

A few years later, while running The Hollywood Reporter, I was in meetings with studio executives exploring what digital distribution might mean for the filmed entertainment business. The response was remarkably similar. One executive turned my question about the still-nascent streaming model back on me: “Tony, theatrical box office is a $10 billion industry. Take a guess what DVD sales are. A $20 billion industry. We’re not spending much time thinking about streaming these days.” That was 2006. Today, Netflix is worth roughly two and a half times Walt Disney — the most powerful studio on the planet at the time of that conversation. The disruptor is worth more than twice the incumbent. The DVD business is a footnote.

The pattern across every major technology disruption is the same: the incumbents aren’t stupid. They’re rational, defending what’s working, discounting what’s early, and optimizing for the present. The problem is that the present has a shorter shelf life each time.

Agentic AI isn’t acting on the business. It’s acting on the function of decision-making itself. It’s entering the territory that senior executives have always owned: synthesis, judgment, resource allocation, workflow design, organizational structure.

That’s not a disruption to the business model. That’s a disruption to the role of the leader.

Consider what's now within reach:

CFO planning cycles that once required analyst teams for weeks can increasingly be run — at least in significant part — by AI agents.

Enterprise technology stacks that took CTOs and CIOs years to architect are being challenged by AI-native alternatives that bypass the complexity entirely.

Procurement functions that were built on human relationship and institutional knowledge are being tested against end-to-end automation.

Go-to-Market programs built over decades on personal relationships and market intuition are facing autonomous agents that evaluate, shortlist, and in some categories select vendors without a salesperson ever entering the picture.

None of this is fully realized yet. The question isn’t whether these shifts will happen. The capability is already here and moving fast. The question is whether the leaders in these roles are getting ahead of it or waiting for it to arrive. Because the executives who frame this as a threat to their function will lose that argument to the CFO who wants to cut headcount. And the executives who frame it as a transformation of their function’s value — from process management to strategic intelligence — are the ones who will define what these roles look like on the other side.

The EY analysis puts the productivity timeline plainly: the benefits of generative AI will likely arrive within three to five years, compared to multiple decades for the steam engine and roughly ten years for the computers. We are not in the early innings of a slow-moving transformation. We are in the compressed early innings of the fastest-moving general-purpose technology disruption in modern business history.

Morgan Stanley’s economists reviewed five major innovation waves; from the Industrial Revolution through the internet, and found that across every one of them, disruption ultimately complemented employment rather than eliminating it. History suggests we’ll adapt. But the historical record also suggests the transition is where leaders and organizations are made or broken.

The transition is now.

The C-Suite Reckoning: Role by Role

The disruption isn’t uniform across the C-suite. Each function is facing a specific version of this challenge. Let me be direct about each one.

* The CEO. The pressure at the top is the most visible. The McMillon and Quincey moments are proof. But the more common failure mode isn’t the CEO who steps down honestly. It’s the CEO who stays, acknowledges the disruption publicly, and then delegates it to a Chief AI Officer or a transformation task force. Real AI transformation requires the CEO to own the conviction. Not every implementation detail, but the organizational belief that this is an enterprise-wide operating shift. Every time I’ve seen that conviction delegated, the transformation stalled. That’s more than a prediction. That’s a pattern I’ve watched repeat across every major technology shift for thirty-five years.

* The CFO. Traditional financial planning — scenario modeling, FP&A, cost forecasting — is going AI-native. The CFO who built their career on Excel mastery, quarterly reviews, and headcount-based cost structures is watching the foundation move. AI can run financial models in minutes that used to take FP&A teams weeks. The CFO who leads through this will be the one who reframes their role from financial architect to “capital allocation strategist”, deciding where human judgment is irreplaceable and where AI-driven analysis should drive the work.

* The CTO/CIO. Of all the C-suite roles, this one carries the sharpest irony. The executive whose entire mandate is technology leadership now faces a transformation that threatens to outrun the very playbook they built their career on. Enterprise technology stacks assembled over decades — the integrations, the vendor relationships, the architecture decisions — are being challenged by AI-native alternatives that bypass the complexity entirely. The CTO or CIO who leads through this isn't the one who defends the existing infrastructure investment. It's the one who can hold two things simultaneously: managing what the business runs on today while architecting what it needs to run on tomorrow. That's not a technology challenge. It's a leadership one.

* The CHRO. Workforce planning in an era when the CEO of Anthropic has publicly stated that AI could eliminate 50% of white-collar work within five years is genuinely uncharted territory. The CHRO who is still running traditional headcount plans and competency frameworks is already behind. The CHRO who will lead through this is building what I’d call a “dynamic workforce architecture”, a continuous model that maps AI capability against human work, identifies where augmentation creates leverage, and redesigns roles rather than eliminating them wholesale. The future is about Human + Digital Labor.

* The Chief Growth Officer / CMO. B2B marketing as practiced for the last decade is being structurally dismantled. Buyer journeys are being executed by AI agents rather than human researchers. The content, events, and paid media programs that generated pipeline in 2020 are producing diminishing returns. The CMO who leads through this transition will stop optimizing existing channels and start designing for a world where the first buyer in the room may not be human.

* The Chief Procurement Officer. This may be the function most immediately in the crosshairs. Agentic AI is coming for sourcing, vendor evaluation, contract management, and supplier intelligence with a speed and scale that no traditional procurement team can match. The CPO who leads through this isn’t managing a cost center. They’re running an intelligence function, one where the value isn’t in the process they oversee, but in the strategic judgment they bring to decisions that AI can inform but not make.

Three Archetypes for Leading Through This

I’ve spent time thinking about how C-suite leaders are actually responding. Not how they’re describing it in the press release, but how the work is actually unfolding. What I see are three archetypes. Each has a different job to do.

The Transformer

This is the leader who has the runway — in terms of time horizon in the role — and the conviction to lead through the full AI transformation cycle. The imperative for the Transformer is to stop treating AI as a department initiative and start treating it as an operating system for the enterprise.

What that means in practice: every function gets reviewed through the lens of what AI can do that humans were doing, what humans must do that AI cannot yet do, and where the hybrid model creates genuine competitive advantage. That’s not a technology project. It’s a strategic redesign, and it has to be led from the top.

The Transformer also has to be willing to do something most executives avoid: change the incentive structures before the transformation demands it. AI adoption stalls when the people responsible for it are also the people most threatened by it. If the CHRO’s success metrics are still tied to headcount growth, you will not get genuine AI workforce transformation. If the CPO is measured on cost savings from vendor relationships, you won’t get a procurement function redesigned for intelligence-led sourcing.

The Transformer changes the metrics first.

The Sequencer

This is the leader who is honest — privately, at minimum — that they won’t finish the journey. They have enough runway to make real moves, but they can see the horizon. The Sequencer’s imperative is not transformation, it’s architecture.

What does a Sequencer do? They build the capability scaffold that gives the next leader a genuine running start. That means: driving AI literacy into the organization at every level. Building the data infrastructure that AI-driven operations require. Making the succession bet: identifying and developing the leaders who have both the operating experience and the AI fluency to take the baton.

The worst outcome for a Sequencer is the one I’ve seen too often in technology transitions: a leader who neither transforms nor prepares. Who manages inertia, makes incremental moves, protects existing structures, and hands the next CEO a business that is further behind than it looks. That’s not a neutral outcome. It’s an actively harmful one.

The Sequencer who does their job well is underappreciated in real time and overappreciated in hindsight. Do it anyway.

The Advisor

This is the leader who makes the call that McMillon made. Honestly, on their own terms. They step out of the operating role, but they don’t disappear. They move into the work that their experience actually makes them irreplaceable for: board roles, advisory relationships, mentoring the next generation of operators.

I’ll be transparent: this is the archetype I’m living right now. I recently stepped out of a CEO role, one where we spent two-plus years transforming a B2B demand generation business into a digital marketing services company built on a Demand-as-a-Service model. We started the AI transformation. We could see what was coming. And I made the same calculation McMillon described, at a far smaller scale. The next leg of the journey was better led by someone whose horizon matched it. That recognition is what led me to launch Uphoff Advisory and shift into board and advisory work — where thirty-five years of operating experience turns out to be exactly what organizations navigating this transition need most.

The Advisor role isn’t a retirement. It’s a repositioning.

The Honest Question

Let me end where I started.

McMillon said: ”I could start it, but I couldn’t finish it.”

That is a remarkable sentence. It requires both confidence; the conviction that you understand what needs to happen — and humility — the honesty that the journey ahead isn’t yours to complete.

Most leaders in the C-suite right now are not asking themselves that question. They’re managing the present. They’re responding to quarterly pressures, board expectations, and the urgent over the important. The AI disruption is real and they know it, but it hasn’t forced a clear-eyed personal reckoning yet.

It will.

The leaders who will navigate this best, whether as Transformers, Sequencers, or Advisors, are the ones who ask the question now, honestly, and then act on the answer with the same rigor they’d apply to any other strategic decision.

The Transformer commits the enterprise to a full operating redesign and changes the incentives to match.

The Sequencer builds the scaffold, develops the successor, and makes the architecture decisions that matter most.

The Advisor doesn't exit. They redeploy, bringing years of pattern recognition into the boardroom, into advisory relationships, and into the work of guiding operators navigating a disruption they've already lived through once.

None of these are failure modes. The only failure mode is the one that looks like leadership but is actually avoidance: staying in the chair, acknowledging the disruption in every earnings call, and changing nothing that actually matters.

The views expressed in Uphoff on Media are entirely my own. They don’t represent the opinions of any company I’ve led, any board I’ve sat on, or any investor who’s had the pleasure of debating strategy with me over the years. If something I write here sounds brilliant, I’ll take full credit. If it turns out to be wrong, I was clearly misquoted by myself.

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