Everyone Wants a Chief AI Officer. Most Companies Don't Need One.

Every board I talk to now opens with the same question. Do we need a Chief AI Officer (CAIO)? Half of them have already half-decided that they do, because a competitor announced one on LinkedIn last week and it looked like falling behind, and the other half are afraid they’re already too late. Most of them don’t need one. A few of them need one badly. And almost none of them have worked out which group they’re in - which is where the trouble starts.

The pressure didn’t start in the enterprise. It started, of all places, in (US) government. In April 2025 the US federal government put out a memo, telling every federal agency to designate a Chief AI Officer: name a human being, give them authority over how the agency uses AI, make them accountable for it. Government almost never moves first on anything in technology, but once “every agency must have a CAIO” was written down somewhere official the title got a stamp of legitimacy, and enterprises do what enterprises always do - they saw the signal, got nervous, and started copying it before anyone in the building asked what the thing was for - often because someone wanted a career step up. And there are many charlatans running around today, claiming they have ten years of AI experience. Well, I studied ML/AI and Neural Networks (NL) in university in Computer Science in 1996 - does this make me a 30-year AI veteran?

Let me make the case for a dedicated Chief AI Officer, before we discover you might not need one (or at least an additional one). The companies that are good at AI - the ones shipping models into the core of what they sell, companies that use AI everywhere, companies that use AI to massivley expand their offering, usually do have one person whose entire job is AI, with a budget and a mandate and nothing else pulling at their attention. AI taken seriously is not something you bolt onto an executive who already has a day job, because the moment you hand it to the person already running all of engineering, or all of product, or all of data, it becomes the thing that gets dropped the week the platform is on fire - keeping the lights on always beats running an experiment, every single time, in every company I’ve ever sat inside. Bolt AI onto a busy exec and what you’ve built is a conflict between running the business and changing it, and running wins.

A new box on the org chart does none of the work.

A VP of AI Operations - no C, no suite, no reserved parking spot - handles governance, compliance, security, policy, the vendor mess and the “are we even allowed to put customer data into this thing” questions well enough. What you need is a person accountable, by name, for AI in your company. Whether that person has a C in front of their title changes the org chart and the compensation band; it doesn’t change whether the work gets done.

And I’ve seen this movie before (I’m that old). Around 2005 every company I talked to had just decided it needed a Chief Digital Officer, and I watched a wave of them get hired into businesses that had no digital strategy at all, on the theory that the title would somehow produce the strategy. The thing you get is a new box on the org chart, a new face at the leadership table, but the same unsolved problem as yesterday, now with a salary attached to it. Digital is culture and not a position. A state of mind. Most of those CDO roles folded back into the CTO or the CMO three or four years later, once everyone stopped pretending and admitted that “digital” was just… how business worked now (And we never had a “Chief Email Officer”). AI is walking down the same hallway. Give it a year or two. Just like for some time everything had an “i” in front of it - with the iPhone being the only thing that survived (iPad I know ;-)

So when do you need a CAIO? When your product is the model itself - when your revenue depends on the models behaving, when a bad output gets you sued, when regulation and ethics and customer trust are all riding on the same horse - and when nobody in your current leadership owns it with any authority and the gap really exists. If AI is core to how you make money, and no single person can say yes or no to an AI decision and have it stick, then you have a hole in your leadership, and a Chief AI Officer is a reasonable way to fill it. That’s the company that should hire one. That's what a CAIO is for in the first place.

For most companies, though, you already employ the person. You have a CTO, or a VP of Engineering - a technical leader who understands your systems and your data and already sits exactly where AI plugs into the product. Give them the mandate, give them the budget, give them the time (rename their title, ha!), and take something off their plate while you’re at it, because you cannot just staple “and also own all of AI” onto an already-full job and expect it to happen on its own (Clearing the plate so they can own the new thing is half of what a coach is for - most of the good CTOs I know have one.). I’ve argued before that CTOs need to own AI before product management takes it from them, the way product once took “deciding what to build” away from engineering while engineering wasn’t looking, and I’ll say it again here: hand AI to a new outsider with a better title while you have a technical leader sitting right there, and you’ve just told that CTO the most important shift of their career is happening over their head.

If you’re one step ahead of most, you have a CPTO. Then make the CPTO responsible for AI - AI is mostly a product strategy issue for many companies anyway. Efficiency through AI gets you better margins, AI for more and bigger products nets you much, much more revenue and kills your competition.

There is one great thing with an AI title though: That person will get up in the morning and think about AI, and nothing else. It’s not a side gig for them, it’s the thing they want to move. It’s the thing they will be fired for if they fail.

Either way, you need an AI champion, someone who pushes - which is again a mindset and authority to do it, not a title.

Maybe I’m wrong for the handful of companies where AI is the whole business and the stakes are existential - there the dedicated title might be exactly right, and the VP-of-AI-operations answer doesn’t scale to a frontier lab that builds models as the product. But for the broad middle, the boardroom is asking the wrong question.

So decide who owns AI in your company. One name, a budget behind it, the authority to make a call and have it hold - an optimistic, pushy, AI champion. If that person already works for you - and for most of you they do - give them the mandate and skip the title. If the answer is nobody, a Chief AI Officer (CAIO) hire buys you a box on the org chart, a salary, and the same gap sitting underneath it, right up until you do the harder work of deciding who is accountable for AI and for what.

Find the owner first. Everything after that is just business cards.