The numbers come first. Total AI spending — including capital expenditures on AI infrastructure — is poised to reach $2.5 trillion in 2026, a 44% increase over last year, according to research and advisory firm Gartner. Next year, that figure is projected to climb to $3.3 trillion. At that scale of investment, the question of who owns the outcome is not academic. It is existential.
Yet only 34% of C-suite executives in Pearl Meyer's Q2 2026 Market Intelligence Survey said it is consistently clear which executive or team makes calls about AI — the lowest figure of any group polled. Board members fared better at 53%, and senior managers below the C-suite came in at 57%. The survey polled 116 board members, CEOs, C-suite executives, and senior managers, conducted in May and June 2026.
The inversion is striking. The executives closest to on-the-ground implementation are the least confident that anyone is clearly owning decisions and results. Those furthest from the daily friction of deployment are the most comfortable. That is not a governance structure — that is a liability waiting to be triggered.
The stakes are already personal for CEOs. A separate survey of 900 CEOs published in May found that 80% of U.S. CEOs believe their job is at risk if their AI projects fail to deliver, while 81% believe a fellow CEO will be ousted due to an AI failure or crisis.
Brad Jayne, a principal at Pearl Meyer and co-author of the study, put it plainly: 'Ambition for AI outcomes is currently outpacing the leadership structure needed to deliver on them. Additional investment without clear ownership will only widen that gap.'
The disconnect extends beyond accountability. When asked whether employees could absorb additional organizational change — with AI implementation as the example — 63% of CEOs said yes. Only 33% of the broader C-suite agreed, and just 40% of non-C-suite executives concurred. Meanwhile, 88% of CEOs and 79% of C-suite executives said achieving strategic goals will require significant operational changes within three years. Only 42% of board directors agreed.
Jayne called that combination 'an alarm bell.' Boards, in his reading, believe the hard work is largely done. Management teams know it has barely started.
'I worry about finger pointing,' Jayne said, warning that when spending must be justified against results, the gap between board confidence and management reality could produce turnover. 'I think we're in for a bumpy ride.'
The Pearl Meyer study also found that 78% of executives below the C-suite report their companies have the senior talent required to effectively implement and oversee AI across the whole organization — a figure that suggests middle management is either more optimistic than warranted or simply better informed than the executives above them.
Confidence that AI will deliver significant gains within 18 months holds at roughly 50% across companies at every stage of maturity, from pilot phase to enterprise-level deployment, according to Jayne. That flat confidence curve — identical whether a company has done nothing or deployed at scale — suggests expectations are not yet tethered to execution reality.
CEO Times take: Free enterprise rewards accountability, and accountability requires clear ownership. When $2.5 trillion in annual capital is deployed without a defined decision-maker, the market is not getting efficiency — it is funding organizational ambiguity at industrial scale. Boards that believe the matter is settled while management teams brace for major structural change are not governing; they are spectating. The companies that will justify this spending to shareholders are the ones that assign ownership now, before the next earnings call forces the question.
