Boards Say C-Suite Owns AI. The C-Suite Disagrees With Itself.
Ninety percent of board members surveyed by Pearl Meyer, an executive compensation advisory firm, say responsibility for leading artificial intelligence belongs with the C-suite. But ask those executives who among them actually owns AI strategy, and the answer splinters into four camps.
The survey of 108 executives and board members from 108 companies-released Wednesday-found 32% of C-suite respondents said the entire executive team shares accountability for AI. Another 22% pointed to the layer below them. Twenty-seven percent said individual business leaders own it. Seventeen percent assigned it to functional heads like HR, finance, and legal.
As companies shift from AI pilots to enterprise rollouts, this disagreement matters. If something goes wrong, nobody knows who caught it first-or should have.
The Real Problem Isn't AI
The ownership split is a symptom, not the disease itself. Pearl Meyer's data reveals deeper fractures between boards and executives on whether leadership teams actually function as units, whether strategy reaches down the organization, and what factors matter most for scaling AI.
One hundred percent of board members said their senior team is cohesive. Only 66% of C-suite executives agreed. Thirty-four percent said their team doesn't work well together.
On strategy communication, 100% of board members said senior leadership decisions translate into clear priorities. Only 78% of C-suite respondents said the same. When asked whether executives two levels below the C-suite can clearly explain the company's top strategic priorities, only 54% of C-suite executives answered yes.
"Your leaders don't know how to be a team," said Brad Jayne, a principal at Pearl Meyer and survey co-author. "C-suite teams can all perform on their own, but collaborating and working effectively as a team isn't there. AI just shines a light on something that was already there."
Boards Hear the Story. Executives Live the Reality.
Board members and executives prioritize different factors for AI readiness-and their answers reveal how each group sees the business.
Forty-five percent of board members named clear executive ownership and decision rights as a top-three factor in deploying AI. Only 22% of C-suite respondents agreed. The executives focused elsewhere: 49% pointed to data quality, infrastructure, and security as critical, compared to 18% of board members.
Peter Thies, a managing director at Pearl Meyer, said the gap makes sense. Inside companies, AI touches almost every function-tech, HR, finance, legal, individual business units. Distributed responsibility describes how AI actually works. But board members hearing about it from the CEO see nobody in charge.
Meanwhile, the C-suite worries about data quality because they understand the operational reality. Boards don't yet see why that matters.
'Just Start Using It'
How companies have positioned AI internally reveals a hands-off approach. Once basic guardrails are in place, the message from senior leaders tends to be simple: go.
"The message from leadership is often, 'Just start using it,'" Jayne said. "And they miss the rest of the story, which is, 'We're not exactly sure where to use it.'"
Forty percent of companies are still piloting AI. Thirty-one percent are experimenting or using it ad-hoc. Not because AI isn't useful, but likely because leadership teams don't agree on how to deploy it at scale or what matters most.
Seventy-one percent of executives told Pearl Meyer that success over the next 12 to 18 months depends on fixing internal processes and cross-functional coordination-not on AI itself. "Leadership systems are not evolving fast enough to support either strategy or AI," the report concludes.
The Pressure to Show Results
Companies including Block, Meta, and Oracle have announced AI efficiency gains as the reason for workforce cuts. Stock markets rewarded them. That reaction creates pressure on every other CEO to deliver the same story.
"At times I see AI being used as the reason for things that may have come about anyway," Jayne said. The more pressure builds to show real results to employees and shareholders, the more incentive exists to attribute existing changes to AI-whether the technology is actually doing the work or not.
Financial services companies face the steepest challenge. They represented 34% of survey respondents and tend to have long leadership tenures and resistant cultures. "It's difficult to move the needle," Jayne said.
Jayne described the current pace of AI rollout as slower than expected. "Maybe wheels are spinning a little bit," he said. "Are we about to shoot off down the road? I don't know. But it's a little slower to get going than I thought it would be."
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