What AI changes for the C-Suite
- Marion Heil
- vor 2 Tagen
- 6 Min. Lesezeit
A reader asked me an interesting question under one of my recent leadership articles. How do CEO expectations evolve as AI and data-driven decision-making become more central to value creation?
My answer at the time was that AI raises the bar on the analytical side while leaving the human and relational dimensions of the role largely untouched. And it got me thinking and I promised a dedicated piece on it. Here it is, and it turned out to apply well beyond the CEO chair, and well beyond PE.
One small departure from how I usually write these. I do not normally build an article around other people's studies. Most of what I share comes from what I see directly in board rooms and CEO transitions, and from the conversations I have along the way with the clients and candidates I work with. But this time I wanted to pressure test my own answer against what the people who study this for a living, the strategy firms, the search firms, the AI researchers, are actually finding.
Some of it confirmed my answer from back then. Some of it sharpened it in a way I had not fully considered.
Take a CEO I worked with recently. Every morning he opens his laptop to three AI-generated dashboards from his leadership team, a churn model flagging accounts at risk, and a board deck the CFO built overnight with an AI drafting tool. All of it is more current and more detailed than anything he had eighteen months ago. And he told me, half joking, that he has never felt less certain about what to do with his day.
That tension says a lot about where the role is heading, for CEOs and for the CXOs around them.
That tension says a lot about where the role is heading, for CEOs and for the CXOs around them.
The analytical floor is rising fast
As AI absorbs more execution, the center of gravity moves upward. Execution becomes abundant. Judgment becomes the constraint.
Bain's research on the operating model for the AI era puts it well. As AI absorbs more execution, the center of gravity moves upward, from doing the work to framing the decision. Execution becomes abundant. Judgment becomes the constraint. Wharton's Ethan Mollick found something similar in practice. In his studies with Boston Consulting Group, AI performed at roughly the eighth percentile of BCG's own elite consultants. It raised the floor for average performers a lot. It did nothing to touch what separates the best from the merely good.
For a CEO or a CXO, that is the whole story in one sentence. AI will make your analysis faster, cheaper, and more complete than any prior generation had available. It will not tell you which of three plausible strategies to bet the company on with limited runway left, or which of your direct reports to trust with a call that cannot wait for more data.
And it is not only a CEO problem
The shift Bain describes, execution becoming abundant while judgment becomes the constraint, and the risk Russell Reynolds flags, judgment eroding under too much reliance on AI, were not researched as CEO-specific findings. They hold just as much for a CFO deciding how much weight to give an AI-generated forecast, a CHRO leaning on AI-driven succession scoring, a CTO signing off on an AI-recommended architecture. Any member of the C-suite whose job involves making calls under incomplete information is exposed to the same dynamic.
This cannot be handed to someone else
CEOs now see themselves, not a CTO or a digital lead, as the primary decision maker on AI strategy.
Boston Consulting Group's 2026 AI Radar found that 72 percent of CEOs now see themselves, not a CTO or a digital lead, as the primary decision maker on AI strategy. The ones getting real value from it, their so-called trailblazers, spend eight or more hours a week building their own fluency with the tools. That is an uncomfortable fact for anyone tempted to treat AI as someone else's problem, a CTO's or a head of data's. The evidence says the opposite.
Egon Zehnder's recent work with CHROs, CFOs, and technology leaders found fewer than 10 percent say they have fully scaled their AI use cases, and that the biggest barriers are human, not technical. They also frame board oversight of AI as a leadership test in its own right, asking whether the top team can tell real strategic value apart from what they call AI theater. Spencer Stuart's latest Board Index shows the accountability catching up with that scrutiny. CEO turnover at S&P 500 companies rose nearly 30 percent in 2025, with boards devoting noticeably more time to AI oversight alongside succession.
AI readiness is a leadership competency, not a technical one.
Korn Ferry's succession research backs this up from a different angle. Their argument is that AI readiness is a leadership competency, not a technical one, and that most succession plans are still built around criteria, like past performance and tenure, that say very little about who can actually lead through AI-driven disruption. The whole search industry is reorganizing around this and is launching AI-enabled assessment platforms, as this changes what "ready" means in an assessment when working on CEO succession and transitions.
The catch: judgment has to be earned, not assumed
Here is the complication I did not fully appreciate when I first answered that question. Russell Reynolds published a report in May 2026 called The Emerging Leadership Development Gap of the AI Era, and it belongs right alongside the optimism from Bain and BCG. Fifty-seven percent of leaders in their research already worry that over-reliance on AI is undermining critical thinking and judgment itself. Their Chief Science Officer calls the risk "judgment without experience". When a leader acts on an AI-generated insight without the depth to interrogate it, poor decisions do not slow down. They scale faster. The danger is not that AI replaces expertise. It is that its fluent imitation of expertise gets mistaken for the real thing.
What good looks like
The practitioners closest to real AI deployments keep landing on the same detail. Adoption tends to fail not because the tool is wrong but because nobody senior visibly uses it first. When a CEO writes board updates with AI and says so, the leadership team follows. When targets do not move to reflect the time AI is supposed to free up, the gains get quietly absorbed and nothing changes. The behavioral work of AI adoption, not the technical work, is where most of the value is won or lost.
Why this lands even harder in PE
This piece grew out of a discussion on a PE-focused article, and it is worth closing the loop on that.
Everything above holds for any CEO or CXO. In PE-backed companies, however, it is sharper still.
Everything above holds for any CEO or CXO. In PE-backed companies, however, it is sharper still.
McKinsey's 2026 Global Private Equity Report even has a name for it now, CEO alpha, the portion of portfolio company returns that comes down to the CEO. Sponsors are pushing portfolio companies to be AI-fluent well before exit, because it strengthens the story they tell buyers, and the firms leading on digital and AI adoption are already showing stronger shareholder returns than those lagging behind. Hold periods are short, often three to seven years, so there is less time for a judgment call to mature or quietly correct itself. The bench is thinner too. A listed company can spread the adoption burden across a CTO, a Chief Data Officer, layers of functional depth. A typical portfolio company C-suite has three or four people carrying that same weight directly, with nowhere for it to diffuse. And the sponsor sits closer and watches more continuously than a public company board does. The pressure on judgment is universal. In PE, it just has fewer places to hide.
My conclusion
It is raising the bar on the analytical side, and at the same time putting real pressure on the judgment.
So here is how I would update and sharpen my answer. AI is not simply raising the bar on the analytical side while leaving judgment untouched. It is raising the bar on the analytical side, and at the same time putting real pressure on the judgment it was supposed to leave alone. The leaders who hold their edge will not be the ones who defer most to the tools, and not the ones who resist them either. They will be the ones still doing the slower, harder work of building judgment through direct experience, so that when the model hands them a confident answer, they still know enough to ask whether it is the right one.
ABOUT THE AUTHOR
Marion Heil is founder and managing partner of Board+CEO Advisors, a Vienna-based executive search and board advisory boutique. She advises listed companies, family businesses and investors on C-suite, leaders and supervisory board appointments across DACH and CEE.
