I've been talking to recruiters lately, and they keep telling me the same story. A CEO calls. The board wants an AI strategy, so the company is hiring a Chief AI Officer. The recruiter asks for the job description. And what arrives is written by someone with no working knowledge of AI at all.
Not a bad draft. A hollow one.
Buzzwords stacked on buzzwords, responsibilities copied from a competitor's posting, success criteria that don't describe anything a person could actually do. The recruiters can tell. They just often can't say so, because the client is the client.
The Delegation Trap
Here's the mechanism underneath, and it's worth being precise about it. These executives don't understand AI, so they do the thing executives are trained to do with things they don't understand: delegate it. Hire a person to own all the AI things. It feels responsible. It looks decisive in a board deck.
But writing a job description is itself an act of understanding. You cannot specify work you cannot evaluate. Try this analogy on: imagine you need to hire a quantum physicist, and you don't know what quantum physics is. What do you do? You let AI write the job description, or you hand it to whoever on your team seems eager to make you happy. Either way, you now have a confident document describing a job nobody in the building can judge. The interviews are theater, because you can't distinguish a great answer from a fluent one.
The Cost Compounds Quietly
So the wrong person gets hired. Not always a bad person, sometimes a talented one who was set up to fail by a mandate that never made sense. The systems never get built, or the wrong ones do. The work product is useless, the year is spent, and here's the part that should keep CEOs up at night: by the time you've learned enough to see the problem, the person you delegated it to has quietly become one of the most expensive line items on your books. Salary, equity, the team they hired, the tools they bought, and the opportunity cost of a year you don't get back. And these are not small salaries: US Chief AI Officer bases run $280,000 to $650,000 in 2026, and year-one packages at enterprise firms clear $900,000 once bonus and equity land [1].
The most expensive problem, with your most expensive hire, is that you weren't qualified to make it.
What Recruiters Can Do
Recruiters, this is also your opening, and I mean that as an invitation rather than a dig. Two moves. First, stop treating the job description as an intake document and start treating it as the engagement. Sit with your client and refine the CAIO role, or its equivalent, until the success criteria describe real, checkable outcomes. That conversation is worth more than the placement fee. Second, get savvy on agentic AI yourselves. Not to code, but to guide. A recruiter who can tell a hiring manager "this description says platform strategy but your actual problem is workflow automation" becomes the most valuable person in the search.
What CEOs Owe the Search
And CEOs: nobody's asking you to build the systems. But delegation without understanding isn't delegation, it's abdication with a compensation package. You need enough fluency to know what you're hiring for, to interrogate the job description before it goes out, and to tell real progress from confident noise after the hire starts. That's a learnable amount of knowledge. It's weeks of real effort, not years.
The Question Worth Sitting With
Before you sign off on that CAIO search, can you explain, in plain language, what this person will have built a year from now and how you'll know if it worked?
If the answer is no, the job description isn't the next step. Your own education is.
If any of this hit a nerve, that's usually the sign there's real work to do. The kind of thing I dig into with leaders one-on-one at Dark Horse Ops. If you want to talk it through, my door is open.
Sources
[1] KORE1, "Chief AI Officer Salary Guide 2026," updated July 6, 2026.
[2] Corroborating range: Glassdoor, "Chief AI Officer Salaries," self-reported median total pay $352,629 (accessed July 2026).
A note on how this got written: I used AI to help me write this. The stories, the opinions, and the scars are all mine. I just have a very good robot assistant who helps me get them out of my head and onto the page. Which is more or less the whole point of what I do now.