Total corporate AI spending is on track to hit $2.5 trillion this year, a 44% jump from last year, and it's projected to climb to $3.3 trillion in 2027. Yet according to Pearl Meyer's Q2 2026 Market Intelligence Survey of 116 board members, CEOs, C-suite executives, and senior managers, only 34% of C-suite executives say it's consistently clear which executive or team actually makes the calls on AI. That's the lowest score of any group polled — well below the 53% of board members and 57% of senior managers below the C-suite who say ownership is clear.
That gap is the story. Companies are writing enormous checks for AI infrastructure, tools, and talent, but the people running those companies can't agree internally on who is accountable when an AI-driven decision goes right, or wrong. For a personal finance and business audience, this isn't an abstract governance footnote. It's a preview of the confusion, wasted budget, and stalled projects that ripple down into hiring decisions, vendor contracts, and ultimately shareholder returns at the companies readers work for or invest in.
A Four-Way Split With No Majority
Ninety percent of board members surveyed said the C-suite, collectively, owns AI strategy. That sounds like consensus until you ask the C-suite itself who inside that group is actually responsible. The answers split into four camps, and none of them commands a majority: 32% said the C-suite as a whole is accountable, 22% pointed to the tier of leaders one level below the C-suite, 27% said individual business-unit leaders own it, and 17% assigned it to functional heads such as HR, finance, or legal.
Put differently, if you asked four senior executives at the same company who owns the firm's AI strategy, there's a real chance you'd get four different answers. Boards are comfortable delegating the question upward into the executive suite; the executive suite hasn't finished deciding who inside it should be holding the ball.
Who Companies Say Owns AI Strategy
| Who's Named as the Owner | Share of C-Suite Respondents |
|---|---|
| The C-suite as a collective group | 32% |
| The tier one level below the C-suite | 22% |
| Individual business-unit leaders | 27% |
| Functional heads (HR, finance, legal) | 17% |
Boards and the C-Suite Are Reading From Different Scripts
The disagreement isn't confined to who owns AI — it extends to whether ownership even matters as much as boards think it does. Forty-five percent of board members named clear executive ownership and decision rights as one of their top three factors in being ready to deploy AI. Only 22% of C-suite respondents ranked it that highly. Directors are watching from a distance and see an accountability vacuum as the central risk. Executives closer to the day-to-day work are more focused on execution speed, budget, and talent — and are, perhaps, less bothered by ambiguity they've learned to route around informally.
That disconnect shows up again on team cohesion. Every single director surveyed — 100% — said they believe their senior leadership team functions as a cohesive enterprise unit. Only 66% of C-suite executives agreed; the other third said their team does not, in fact, work well together. Boards are grading the team's teamwork on a curve the team itself doesn't recognize.
Why This Isn't Just a Tech Problem
It's tempting to file AI governance under "IT issue" and move on. The survey data argues against that. In many organizations, a CIO or CTO ends up formally accountable for AI systems they don't fully control, because the budget, the vendor relationships, or the actual use cases live inside a business unit, not the technology function. That mismatch between who holds responsibility and who holds authority is a classic organizational-design failure, and it predates AI by decades — AI just raises the stakes and the dollar figures involved.
There's also a second layer of misalignment buried in the same survey: 88% of CEOs and 79% of C-suite executives said hitting their strategic goals will require significant organizational change within three years. Only 42% of directors agreed. And when asked whether employees could absorb more organizational change without feeling stretched thin, 63% of CEOs said yes, compared with just 33% of the C-suite and 40% of non-C-suite executives. The people setting the pace and the people managing the people doing the work are not looking at the same picture.
What Happens When Nobody Formally Owns AI
- Budget gets duplicated. When three business units each believe they have implicit authority over AI tooling, they often buy overlapping software rather than sharing a platform.
- Risk reviews get skipped. A use case that falls between HR, legal, and IT frequently gets deployed before anyone runs it through a formal risk or compliance check, because no single owner is required to sign off.
- Wins go unclaimed and failures go unowned. Ambiguous accountability cuts both ways — successful pilots don't scale because no one has the mandate to champion them past their originating team, and failed ones don't generate lessons learned because no one is required to conduct a post-mortem.
- Middle managers absorb the confusion. Senior managers below the C-suite reported the clearest sense of who's in charge (57%), which suggests they're often the ones translating ambiguous executive direction into concrete instructions for their teams — a role nobody formally assigned them either.
A Practical Framework for Assigning AI Ownership
Leadership consultants who work on this exact problem generally converge on a few concrete steps, and the survey results make clear why each one matters:
- Name an owner per use case, not per department. "IT owns AI" is too broad to be useful. A specific person should be named as the risk owner for each significant AI application, the way companies already assign owners to major capital projects.
- Separate the platform decision from the use-case decision. The team that selects and licenses AI infrastructure doesn't need to be the same team accountable for how a specific business unit applies it.
- Give directors a standing AI accountability line item. Since boards care more about clear ownership than executives currently do, a recurring board-level review of "who owns what" closes the gap the survey identifies.
- Audit for authority-responsibility mismatches. If someone is accountable for an AI system's outcomes but doesn't control its budget, vendor selection, or deployment timeline, that's a structural problem worth fixing before it becomes a public one.
- Re-survey your own leadership team. The cohesion gap between directors and the C-suite suggests many boards are operating on outdated assumptions about how well their executive team actually functions together.
What This Means If You Manage People Right Now
You don't need to be a Fortune 500 CEO for this to be relevant. Mid-sized companies and even small businesses are adopting AI tools for customer service, finance, and hiring faster than they're assigning clear ownership over those tools. If you manage a team, the survey's practical lesson is this: don't wait for someone above you to formally define who owns your department's AI decisions. Document, in writing, who on your team approves a new AI tool, who's responsible for checking its outputs, and who escalates when something goes wrong. That written clarity, even informally created, puts you ahead of the 66% of C-suite executives who told Pearl Meyer their own leadership team isn't fully aligned.
The trillions being spent on AI infrastructure will keep climbing regardless of whether org charts catch up. The companies that pull ahead over the next few years are unlikely to be the ones that spent the most — they'll be the ones that spent knowing exactly who was accountable for the results.