A new Pearl Meyer survey of 108 executives and board members reveals a striking disconnect: while boards overwhelmingly believe AI leadership belongs with senior executives, the C-suite itself remains deeply divided on who actually owns the strategy—and that ambiguity carries real risk.
The Ownership Split
When asked who should lead artificial intelligence initiatives, 90% of board members pointed squarely to the C-suite and its direct reports. But dig into the C-suite's own responses, and consensus evaporates:
- **32%** say the C-suite as a collective body is accountable
- **27%** assign ownership to individual business unit leaders
- **22%** believe responsibility lies one level below the C-suite
- **17%** place it with functional heads (HR, finance, legal, etc.)
As companies shift from AI pilots to enterprise-wide deployment, this fragmentation raises a critical question: *If something goes wrong, who is responsible for catching it before it becomes public?*
The Deeper Problem: Leadership Dysfunction, Not AI
According to Brad Jayne, a principal at Pearl Meyer and report co-author, AI isn't creating new organizational problems—it's illuminating old ones.
"Your leaders don't know how to be a team," Jayne said. "C-suite executives can perform individually, but collaborating effectively as a unit isn't there. AI just shines a light on something that was already there."
The survey data underscores this rift:
| Question | Board Response | C-Suite Response |
|----------|---------------|------------------|
| "Is our senior team a cohesive enterprise unit?" | 100% agree | 66% agree |
| "Do leadership decisions translate into clear priorities?" | 100% agree | 78% agree |
| "Can leaders two levels down clearly explain our top strategic priorities?" | — | 54% agree |
In other words, even executives who feel aligned at their level aren't confident that the strategy has cascaded to the teams executing the work.
Different Lenses, Different Priorities
Boards and executives also diverge on what matters most for AI readiness:
- **Boards** prioritize governance: 45% cite clear executive ownership and decision rights as a top-three factor
- **C-suite** prioritizes execution: 49% point to data quality, infrastructure, and security
Peter Thies, managing director at Pearl Meyer and report co-author, explains the disconnect: "The C-suite isn't as concerned about who owns AI because so many functions touch it. Distributed responsibility reflects how AI actually works. But from the board's vantage point, that looks like nobody is in charge."
Conversely, while the C-suite is deeply focused on data foundations, boards often underestimate their importance—a gap that could undermine even well-intentioned AI investments.
"Just Start Using It"—But Then What?
Jayne notes that once basic guardrails are set, leadership messaging often defaults to a vague mandate: *Go*.
"The message is, 'Just start using it,'" he said. "But they miss the rest of the story: 'We're not exactly sure where to use it, how to measure success, or whether it's actually making us more efficient.'"
This ambiguity leaves employees navigating AI adoption without clear direction, metrics, or support—increasing the risk of inconsistent use, compliance gaps, or public missteps.
Where the Pressure Is Highest
Industries with long leadership tenures and entrenched cultures—such as banking, insurance, and financial services (which represented 34% of survey respondents)—may struggle most to resolve these governance gaps. Cultural inertia can slow the cross-functional coordination AI deployment demands.
Meanwhile, external pressure is mounting. Companies like Block, Meta, and Oracle have cited AI-driven efficiency gains to justify workforce reductions, and markets have rewarded them. That creates a powerful incentive for other CEOs to deliver similar narratives—whether the AI is truly delivering value or not.
"At times, I see AI being used as the reason for things that may have come about anyway," Jayne observed. The more AI becomes a justification for transformation, the greater the pressure to produce measurable results that satisfy both employees and shareholders.
The Current State: Spinning Wheels, Not Full Speed Ahead
Pearl Meyer's data suggests many organizations are still finding their footing:
- **40%** are in the pilot phase
- **31%** are experimenting or using AI ad-hoc
- **71%** of executives say success in the next 12–18 months depends on fixing internal processes and cross-functional coordination—not on the AI technology itself
"Maybe the wheels are spinning a little," Jayne 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."
The Bottom Line
The survey's conclusion is stark: *Leadership systems are not evolving fast enough to support either strategy or AI.*
Boards may hear a confident "We've got this" from the top—but internally, the C-suite may be asking, "How exactly are we going to do this?" Until organizations address the underlying gaps in collaboration, communication, and accountability, AI initiatives risk becoming another initiative that sounds transformative in the boardroom but stalls in execution.
The technology is ready. The question is whether leadership is.