In most organisations, nobody owns AI, not really. Not officially, not on an org chart, not in a way anyone could point to under pressure. For the last few years, that has been fine. Everyone touched AI a little, so no one needed to own it entirely.
That fuzziness is now expensive.
Two things changed the maths. The first is regulation. From 2 August 2026, the EU AI Act’s transparency obligations became enforceable: AI systems that interact directly with people, generate synthetic content, or use emotion recognition or biometric categorisation now require disclosure (European Commission), with providers facing fines of up to €15 million or 3 per cent of global annual turnover, whichever is higher (Cooley). A regulator does not care whether your organisation has formally assigned AI ownership. It cares who signs the compliance filing.
The second is spend. Global AI spending, including infrastructure capital expenditure, is on track to reach $2.5 trillion this year, a 44 per cent increase on last year, according to Gartner research reported by Fortune. Next year, Gartner expects that figure to climb to $3.3 trillion. That is capital being committed at a scale that normally comes with a name attached to the decision, not pocket-change experimentation.
Except it doesn’t. A Pearl Meyer survey of board members, CEOs, C-suite executives and senior managers found that just 34 per cent of C-suite executives say it is consistently clear which executive or team makes the calls on AI, the lowest confidence score of any group polled. Board members are considerably more settled, at 53 per cent. Senior managers below the C-suite, who carry out the actual AI work day to day, are more confident still, at 57 per cent. The C-suite sits in the middle of that gap, managing expectations from above and execution from below, and is the only group unsure who is actually in charge.
Meanwhile, PwC’s 29th Global CEO Survey, drawn from 4,454 CEOs across 95 countries, found that 56 per cent report no significant financial benefit from their AI investment so far, and only 12 per cent report gains on both cost and revenue (PwC). Spend accelerating, returns lagging, ownership unclear: three symptoms, one disease.
Governance Failure Wearing an Investment Story
I have watched this exact pattern play out on transformation programmes long before AI made it fashionable. A programme gets funded because the business case looks compelling on a single slide. Nobody sits down and decides who has the authority to stop it, slow it, or redirect it once it is underway. The absence of that decision does not read as a problem at the time, because everything is moving and everyone is busy. It reads as a problem eighteen months later, when the programme has drifted from its original purpose and there is no single person whose job it was to notice.
AI is running the same play at a faster clock speed. A RACI chart is not corporate theatre. It is the difference between a decision someone made on purpose and a decision that happened to everyone by default. Right now, most organisations have the second kind.
What an Actual Owner Looks Like
Contrast that with the UAE’s approach to its own AI commitment. In April 2026, Sheikh Mohammed bin Rashid Al Maktoum announced that 50 per cent of UAE government services and operations would run on agentic AI within two years, making it the first government in the world to commit to autonomous AI at that scale (Khaleej Times). Whatever view you take of the ambition, the governance structure was not an afterthought. Sheikh Mansour bin Zayed Al Nahyan was named to oversee implementation. Mohammad Al Gergawi was named to chair the taskforce running it. Before the programme scaled, someone’s name was attached to it.
It is not that most organisations lack ambition for AI. It is that they have skipped the one governance step that made every other major technology rollout survivable: deciding, on purpose, who is accountable before the spending accelerates past the point where anyone can meaningfully intervene.
Three Things That Actually Fix This
Name a single accountable owner for AI decisions at the level where spending actually happens. Not a committee. A person.
Separate who evaluates AI performance from who decides whether to scale it. Those are different jobs, and conflating them is how bad bets survive their first review.
Treat AI spending with no named owner attached to it as a governance red flag before it becomes an investment number on a board slide, not after.
None of this requires new technology. It requires the same discipline that used to be applied to every large capital commitment, before AI convinced everyone the normal rules no longer applied. They always did. The bill has simply arrived: from a regulator, from a survey, and from a CEO’s own board asking where the money went.