Who Owns AI Strategy? The Growing Divide Between Boards and the C-Suite

Here is a strange little scene that is playing out inside boardrooms across the world right now.

A board chair turns to the CEO and asks, very politely, who owns the AI strategy. The CEO smiles, nods, and says the right thing. The board feels reassured. The CEO walks back to their office, calls a meeting, and asks the same question to their own team. Four different executives raise their hands. One of them is the CIO. One is HR. One is the head of a business unit. One is sitting there hoping nobody notices that nobody is actually in charge.

That, in one paragraph, is the boards and C-suite divide of 2026.

It is not a small crack. It is a structural one. And every company scaling AI is sitting on top of it.

What is the AI ownership divide, really?

The AI ownership divide is the gap between what the board believes about who owns AI in companies and what the executive team actually does about it.

A new Pearl Meyer survey, published in Fortune in April 2026, put hard numbers on this for the first time. The firm polled 108 executives and directors across 40 public companies, 58 private companies, and 12 nonprofit or government entities. The headline finding was striking. Ninety percent of board members said responsibility for leading AI sits with the C-suite and their direct reports.

Then they asked the C-suite the same question. The answer split four ways.

Thirty-two percent said the C-suite as a group owns it. Twenty-two percent passed it down one level. Twenty-seven percent said individual business unit leaders run AI. Seventeen percent said it sits with functional heads — HR, finance, legal.

In other words, the board thinks someone is driving. The C-suite is not entirely sure which one of them is holding the wheel.

This is the AI strategy ownership problem at its most honest. And it is not just about AI.

Why does the boards and C-suite divide matter now?

Because the consequences have moved from theoretical to public.

Brad Jayne, a principal at Pearl Meyer and one of the survey authors, made a sharp observation. He said AI is not creating new problems. It is exposing old ones. C-suite teams, he argued, can each perform brilliantly on their own. What they often cannot do is operate as a team. When a fast-moving external shift like AI hits, the cracks in that collaboration become impossible to hide.

The survey backs him up. One hundred percent of directors believe their senior leadership team is a cohesive enterprise unit. Only sixty-six percent of C-suite executives agree. The other thirty-four percent flatly say their team is not working well together.

So the board sees one company. The executives are running another one. And AI is the live wire connecting them.

This is what makes corporate AI governance harder than the boardroom slide deck suggests. The board hears the polished version. The executives are living the unpolished version. And nobody in either room is fully convinced the other knows what is going on.

How big is this divide globally?

Bigger than one survey.

In May 2026, BCG published its first edition of Split Decisions, surveying 625 leaders — 351 CEOs and 274 board members from companies with at least 100 million dollars in annual revenue. The findings rhyme almost uncomfortably with Pearl Meyer.

Sixty-one percent of CEOs said their boards are rushing AI transformation. More than half said AI hype is distorting boardroom judgment. Nearly forty percent said boards lack an informed view of how AI is actually reshaping growth. One in three said boards overestimate the human capabilities AI can replace.

The mirror image is just as telling. Seventy-five percent of board members rated their own AI understanding as on par with or ahead of their peers. CEOs strongly disagreed. And then there is the number that should make every compensation committee pause. CEOs estimate that thirty-five percent of their performance evaluation now depends on AI ROI. Boards estimate twenty-seven percent. That eight-point gap is not a rounding error. It is a real-life mismatch between how a CEO is being judged and what the board thinks it is judging them on.

Pearl Meyer captures the symptom. BCG captures the scale. The picture they paint together is the same — the AI leadership accountability chain is broken at the top.

What does this look like in India?

A little different, and in some ways more interesting.

A 2026 study from Zinnov, OpenAI, and Z47 surveyed over 100 CXOs across Indian enterprises. Forty-nine percent of Indian companies now classify as mature AI adopters. Forty-six percent are still scaling pilots. Five percent have not started. India also ranks number one globally in AI skill penetration. The talent is here. The compute investment is here. Twenty out of the world's top 100 AI companies have an Indian co-founder.

But here is the part that lines up with the global divide. The study identifies four archetypes of Indian enterprises — and a real chunk of them are still in what the report calls the explanation phase, spending boardroom time defending pilots rather than building enterprise-level AI.

Sound familiar? It should. Pearl Meyer reported that forty percent of global companies are still piloting AI, and thirty-one percent are using it on an ad-hoc basis. So roughly seven out of every ten companies surveyed are not yet running AI at scale. India is closer to the front of that pack than the back, but the boards and C-suite divide still shows up in the same way — a CEO who is racing, a board that is asking the wrong questions, and a leadership team that is not aligned on who actually owns the file.

For Indian directors, this also runs into a regulatory wall. Section 166 of the Companies Act expects directors to exercise reasonable care and diligence. SEBI's evolving 2026 guidelines have made it clear that fiduciary responsibility for AI outcomes rests with the board, regardless of automation level. So when the CEO says "we have got AI handled" and the board nods, both of them are now legally on the hook for what the team below them does with it.

What are boards and CEOs actually disagreeing about?

The disagreement is not just about ownership. It runs across three things.

One. What matters most for AI readiness. Pearl Meyer asked respondents to name the top factors for being AI-ready. Forty-five percent of board members named clear executive ownership. Only twenty-two percent of C-suite executives agreed. Meanwhile, forty-nine percent of the C-suite pointed to data quality, infrastructure, and security as the top factor. Only eighteen percent of boards saw it the same way. Boards are worried about who is in charge. The C-suite is worried about whether the plumbing works.

Two. Whether the strategy is actually reaching the ground floor. One hundred percent of board members in the Pearl Meyer survey said leadership decisions translate into clear priorities for the rest of the company. Only seventy-eight percent of the C-suite agreed. And when asked whether leaders two levels below the C-suite could clearly explain the company's top strategic priorities, only fifty-four percent of executives said yes. Almost half admit the strategy is not landing where the work happens.

Three. The pace. This is where BCG's data is loudest. Boards want speed. CEOs want sense. Forty percent of board members who consider themselves less AI-savvy than their peers say their organization is moving too slowly. That fear-of-missing-out is now driving real boardroom pressure. Meanwhile, CEOs feel the pressure of their own performance review depending on AI ROI numbers that may not show up for years.

This is who owns AI in companies translated into actual workplace tension. Speed versus sense. Ownership versus distribution. Optimism versus operating reality.

Why is "just start using it" not a strategy?

Because it is the default — and the default is failing.

Jayne summed it up bluntly in the Pearl Meyer report. The message from most senior leaders, he said, is essentially a single command. Go. Start using it. Try it. Figure it out as you go.

The rest of the sentence, which usually does not get said out loud, is that nobody is exactly sure where to use it, whether employees are using it well, whether productivity is actually improving, or which workflows are quietly being broken by enthusiastic experimentation.

This casual approach is fine when AI is a side project. It becomes a serious problem when AI is making decisions, signing contracts, generating customer-facing content, and influencing hiring or lending decisions. That is the world we are now in.

And it is the reason boards keep asking the ownership question. Not because they are obsessed with org charts, but because they sense — correctly — that "everybody owns it" is a polite phrase for "nobody owns it."

What should boards and CEOs actually do?

Five practical moves, in order.

One. Name the owner. One name, one face, one accountability line. Not a committee. A single executive — usually the CEO, sometimes the COO, occasionally a Chief AI Officer — who carries the file. Distributed responsibility is the right way to run AI. Distributed accountability is not.

Two. Make AI a standing board agenda item. Like cyber. Like audit. Not a special one-time presentation. A recurring, scheduled review that the board owns and the CEO reports on. This is the cleanest path to fixing AI leadership accountability without turning the board into an IT committee.

Three. Educate the board, but not only through the CEO. BCG suggested CEOs should personally educate their boards. That is necessary, but not sufficient. If the CEO is the only source of the board's AI knowledge, the board cannot independently evaluate the CEO's AI strategy. Bring in external faculty. Independent advisors. Real operators. Eighty percent of both CEOs and board members in the BCG survey agreed that future directors should have demonstrable AI fluency. That is the bar.

Four. Audit the cascade. If only fifty-four percent of the C-suite believes the strategy is reaching two levels below them, that is the real failure point. Boards should ask CEOs to bring in the layer below the C-suite — not for show, but to actually test whether the strategy lands.

Five. Re-anchor performance metrics. If thirty-five percent of CEO compensation is hinged on AI ROI, the metric needs to exist on paper, not in a hallway conversation. Compensation committees that do not have a written AI performance framework are flying blind.

The real question is not who owns AI

It is whether the boardroom and the executive corridor are reading the same script.

Right now, they are not. Pearl Meyer says it. BCG says it. The India data says it. Seventy-one percent of executives in the Pearl Meyer survey said success over the next twelve to eighteen months will depend on fixing internal processes and cross-functional coordination, not on the AI itself.

That is the line that should be printed on every boardroom agenda this quarter. The AI is not the problem. The way leaders are choosing to govern around it is.

The companies that close this boards and C-suite divide in 2026 will not be the ones with the loudest AI press release. They will be the ones whose board chair, CEO, and head of strategy can finish each other's sentences on AI strategy ownership — and back it up with a name, a metric, and a calendar.

Everyone else will keep nodding politely in the boardroom and panicking quietly in the corridor.

As AI reshapes leadership accountability, the biggest risk is no longer technology — it is misalignment between the boardroom and the executive corridor. The organizations that win in 2026 will be the ones where directors and leadership teams are aligned on AI strategy, governance, and accountability.

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