Somewhere in your business, a decision about AI is being made this week. Someone on your team is testing a tool for writing first drafts. A client asked whether you use AI, and someone gave an answer that has now become your unofficial position. A subscription renewed and nobody remembers approving it.
None of this is on anyone’s job description. Yet the work of owning AI in your business is already happening, distributed across a handful of people who never really agreed to own it.
This is the quiet reality underneath the rise of the Chief AI Officer (CAIO). Large organisations are creating the role because they have looked at their own operations and realised the same thing: someone needs to hold the AI roadmap, and right now nobody formally does. The title is new. The problem it solves is not.
The role exists whether or not the title does
Strip away the seniority and the salary, and the Chief AI Officer is responsible for a small number of unglamorous things. Deciding where AI genuinely helps and where it is a distraction. Setting a position on what the business will and will not do with client data. Choosing which tools are worth committing to and which are noise. Making sure the people using them actually understand what they’re using.
Most of that list is probably already being handled in your business. Not by one person, and not deliberately, but handled. The operations lead who quietly vetoed a tool because of where the data was stored. The senior designer who worked out a genuinely useful workflow and taught two colleagues. The founder who fields the AI question every time it comes up in a pitch.
These people are doing fragments of the Chief AI Officer job. In a large enterprise, someone has drawn a box around those fragments, given them to one person, and attached a mandate. In a smaller agency or brand, the fragments stay scattered, and the person holding the most important one often has no authority to make it stick.
The gap is not the title, it is the ownership
Reading about a new C-suite role invites a familiar reaction: another thing the big players can afford that you cannot. That framing gets the situation backwards.
You do not need to afford a Chief AI Officer. You need to notice who is already doing that work, name it, and give them room to do it on purpose rather than by accident. That is a smaller decision than it sounds.
The cost of leaving it unnamed is subtle. It is the tool nobody owns that slowly becomes load-bearing. It is the client question answered three different ways by three different people. It is the useful workflow that lives in one person’s head and leaves when they do. None of these are crises. They are the kind of small drift that only becomes visible once someone is actually looking.
Naming the owner does not mean hiring. It usually means taking someone who is already good at what they do, already curious, already half doing it, and saying: this is yours now, here is the time and the mandate to do it well. That person is rarely hard to find. They are the one people already go to when they have an AI question they don’t want to ask out loud.
What a named owner actually changes
Once the role has an owner, the questions stop arriving randomly and start arriving somewhere. The position on client data gets decided once instead of improvised each time. Tools get chosen with intent. Knowledge that was trapped in one person’s head has somewhere to live.
Sometimes the person you name has the instinct but not the map. They know the business well and they are the right owner, but the landscape of what is possible, and what is genuinely worth committing to, is unfamiliar territory. That gap is often closed faster with an outside view than through internal effort alone, not because the capability is missing, but because someone who has walked this ground before can help the right person see the shape of the decision sooner.
Where an outside view helps
This is the part of the work Tidra spends most of its time on: sitting with a business long enough to see where the AI ownership already lives, and helping the right person turn that into an actual roadmap rather than a running list of half-decisions. Not a transformation programme, not a stack of new tools. Usually a handful of clear calls about data, tools, and workflow, made once and made on purpose. For a service-led business without the bandwidth for a formal AI function, that outside perspective can do in a few sessions what would otherwise take months to surface on its own.
