Boards Say C-Suite Owns AI. The C-Suite Disagrees on Who.
Board members have a clear answer to who should lead artificial intelligence strategy: the C-suite. Executives at the top of companies, however, point in four different directions.
A Pearl Meyer survey of 108 executives and board members found 90% of directors said the C-suite and their direct reports own responsibility for AI. Inside that same C-suite, only 32% agreed that the group as a whole is accountable for AI strategy.
The remaining executives split their answers: 22% pointed to the level below the C-suite, 27% to individual business leaders, and 17% to functional heads like HR, finance, and legal.
This gap matters. As companies move from testing AI toward company-wide rollouts, unclear ownership creates real risk. If something goes wrong-a biased hiring tool, a data breach, a public mistake-the question of who catches it first becomes urgent.
The Symptom of an Older Problem
Brad Jayne, a principal at Pearl Meyer and one of the survey's authors, said AI isn't creating new governance problems. It's exposing ones that already existed.
"Your leaders don't know how to be a team," Jayne said. "C-suite teams, they can all perform on their own, but collaborating and actually figuring out how to work effectively as a team isn't there."
The survey found wider disconnects between what boards believe and what executives experience. Board members said 100% of their senior teams are cohesive enterprise units. Only 66% of C-suite executives agreed. The other 34% said their teams don't work well together.
The gap widened further down the organization. All board members said decisions from senior leadership translate into clear priorities. Only 78% of C-suite executives agreed. When asked whether leaders two levels below the C-suite can clearly explain the company's top strategic priorities, only 54% of C-suite executives said yes.
That means nearly half of executives confident in strategy at their own level doubt it has reached the people actually implementing AI across the business.
Boards Hear the Story, Not the Reality
Peter Thies, a managing director at Pearl Meyer, said boards and executives see the business differently. Boards hear a narrative from the CEO about AI strategy. Executives live the operational reality.
When Pearl Meyer asked what factors matter most for AI readiness, the two groups named almost entirely different answers. Board members focused on ownership-45% said clear executive ownership and decision rights were top-three factors. Only 22% of C-suite respondents agreed.
C-suite executives zeroed in on infrastructure. Forty-nine percent pointed to data quality, infrastructure, and security as top factors. Only 18% of board members mentioned these.
"The C-suite's not that concerned about who owns AI, because a lot of people actually have something to do with it," Thies said. AI touches nearly every function: technology, HR, finance, legal, and individual business units. Distributed responsibility looks like a governance gap to boards looking in from outside. To executives living it daily, it looks like how AI actually works.
'Just Start Using It'
Companies have deployed AI with minimal structure. Once basic guardrails are in place, Jayne said, the message from leadership is simple: go.
"The message from leadership is often, 'Just start using it,'" he said. "And they miss the rest of the story, which is, 'We're not exactly sure where to use it.'"
The data supports this. 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 aren't aligned on how to deploy it at scale.
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.
Pressure to Show Results
Companies including Block, Meta, and Oracle have announced AI efficiency gains as the reason for workforce cuts. The stock market rewarded them.
That creates pressure on every other CEO to deliver the same story, whether the AI is actually producing results or not. "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 performance gains tied to AI, the more companies risk deploying it without proper alignment on strategy or accountability. Industries with long leadership tenure-finance, banking, insurance-will likely struggle most with these discrepancies.
"Leadership systems are not evolving fast enough to support either strategy or AI," the Pearl Meyer report concludes.
For executives tasked with building AI strategy, the survey points to a single bottleneck: the team at the top needs to agree on who owns what, and that agreement needs to cascade clearly downward before rolling out AI at scale. AI for Executives & Strategy resources can help leadership teams align on governance and accountability structures before problems emerge.
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