Most organisations I talk to already use AI. Licences have been bought, a few pilots are running, and someone in legal has written a policy. What they rarely have is a person who owns the whole thing.
IT owns the licences. The business owns the use cases. Legal owns the risk. Finance owns the budget line. Each of them is doing their job. And the decisions that sit between them don't get made, because none of them is placed to make them.
That gap is what the Chief AI Officer is for. The title is new enough to mean different things in different places, so it's worth being concrete. A CAIO is not a title. It's a set of decisions with one name attached.
Where the role came from
The role went mainstream in the public sector first. In March 2024 the US Office of Management and Budget told every federal agency to designate a Chief AI Officer, responsible for coordinating AI use, managing its risks and promoting its uptake. Large companies followed.
In Europe the push came from a different direction. The EU AI Act puts obligations on organisations that use AI, not only on the companies that build it. Since February 2025, Article 4 has required them to make sure their staff have a sufficient level of AI literacy. Someone has to own that. In most organisations nobody does yet.
The five decisions
When I describe the role to a leadership team, I describe it as five decisions. If one person holds all five, you have a CAIO, whatever the title says. If they are spread across four departments, you don't.
What we use AI for, and what we stop. A portfolio of use cases with owners, ranked by value and by how ready the data and the people are. The hard part is the second half. Pilots are cheap to start and expensive to end, and most organisations have more of them than anyone approved.
Which tools and models we buy. Vendor and model choices, made once and written down, rather than separately by every team with a credit card. Including the choice to buy nothing yet.
What the rules are. Governance in proportion to the risk. A policy people can follow, an approval route that takes days rather than months, and a clear view of which EU AI Act obligations actually apply to you. Most won't. The ones that do matter a lot.
Where the money goes. AI spend is spread across licences, consulting, cloud and staff time, and often booked in four places. Somebody needs to see the total and decide whether it pays back.
Who can do what. Skills, roles and hiring. Who gets trained, who builds, and who is accountable for a use case once it is live.
None of these is a technical decision on its own. Each has a technical part, which is why the person holding them needs to know the technology well enough not to be sold to.
What the CAIO doesn't own
The role goes wrong in two predictable ways.
The first is the CAIO who becomes the AI team. Every request routes to them, every build waits for them, and the organisation learns that AI is something a specialist does on your behalf. That's the opposite of the goal. The point is AI in the daily work of people who are not AI specialists.
The second is the CAIO who owns AI the way a compliance function owns risk. All policy, no delivery. Approvals pile up, the useful work moves to personal accounts, and the governance ends up describing a world that doesn't exist.
The CAIO owns the decisions. The work belongs to the teams. The data belongs to whoever already owns it. Training and building are capabilities the organisation needs to grow, not services the CAIO provides.
I keep that line in my own work. When a client needs teams trained or tools built, that goes to Applied Futures, the company I co-founded for exactly that, and the decision seat stays separate.
It doesn't have to be a new person
In plenty of organisations the right answer is to give the five decisions to someone who is already there. A CTO or CIO with the time and the interest. A COO who already runs the operating model. A digital director.
The test is whether you can name the one person who will be asked, at the next board meeting, what the organisation's position on AI is. And whether that person can answer with decisions rather than a list of tools. If so, you have your CAIO. If the honest answer is "it depends who you ask", you don't.
When the five decisions don't fit anyone's existing role, and the organisation isn't ready for a permanent hire, a fractional seat is one way to cover the gap. I've written about when fractional is the right shape and when it isn't, and about what the first ninety days look like.
One thing to do this quarter
Write the five decisions on a page and put a name next to each.
Where the same name appears five times, you're in good shape. Where five different names appear, you've found the reason your AI pilots don't add up to anything. And where there is no name, you've found your first decision.