The trend I see in most AI leadership briefs right now is a technology spec dressed up as a business decision. The brief asks for the deepest AI technical credentials available, the most recent research background, the strongest ML engineering pedigree, the most impressive LLM model deployment examples. The assumption is that the technical capability is the hard part, and the business application will follow.
That assumption is often wrong. And in eighteen months, a lot of businesses will be dealing with the fallout.
The wrong frame
AI leadership isn’t a technology problem that happens to have business implications. It’s a commercial and organisational problem that requires varying degrees of technical depth. The leaders who will build AI functions that create real business value aren’t necessarily the most technically capable AI people in the market. They’re the ones who can translate that capability into outcomes the business can actually use, and who can build the organisational connections and commercial credibility to deliver ROI.
Most businesses are hiring from one end of that description and hoping the other follows. The experience of the last few years in data leadership is worth looking at here. Businesses have hired technically excellent data scientists, built genuinely sophisticated platforms, and then found the insights produced weren’t being used to make any important decisions. Not because the technical work was wrong, but because nobody had been responsible for connecting it to the way the business actually operates.
AI is the same problem at higher speed and higher stakes. The technical capability is more powerful, but the gap between what the capability can do and what the business can absorb hasn’t got any smaller. If anything, it’s widened.
What the role actually requires
Three things matter when you’re hiring someone to lead an AI function, and most briefs only address one of them properly.
The first is commercial translation. The person leading AI needs to articulate what AI does for the business in terms a board, a CFO, and a CEO can act on. That means connecting capability to revenue, cost, risk, or competitive position in language that doesn’t require a technical glossary. This sounds obvious, but the pattern I see is briefs that treat commercial awareness as a “nice to have” bolted onto a technical spec, rather than the core of the role. The best data and AI leaders are the ones whose first instinct is to ask what the business needs, not what the technology can do.
The second is influence. AI doesn’t sit neatly in one function. It touches product, operations, finance, customer, and often if not always, the core commercial model. The leader who makes AI work inside a business is someone who can build relationships across the senior leadership team, negotiate priorities, and get people who didn’t want or ask for AI to cooperate with the plan. That’s not a technical skill. It’s a leadership skill, and it’s the one most often missing from briefs that focus heavily on engineering credentials.
The third is technical credibility. This one matters, but not in the way most briefs frame it. The AI leader doesn’t need to be the most technically brilliant person in the building. They need to be credible enough to earn the trust of the technical team, to make sound architectural and vendor decisions, and to know when they’re being sold something that won’t work. Technical depth is the baseline. Commercial translation and organisational influence are what determine whether the hire actually delivers.
How to brief AI correctly
The fix isn’t complicated, but it does require the brief to start from a different place. Most AI leadership briefs begin with a technical specification and add commercial requirements at the end. The brief should start with the commercial questions.
What does the business need AI to do in the next 12 to 18 months? What decisions will AI inform, and who makes those decisions today? Where does AI sit in the organisation and who does the leader report to? What’s the realistic budget, and what does the business expect in return for that investment? What does success look like in terms the board will recognise?
Once those questions have clear answers, the technical requirements follow naturally. You need someone who can deliver against that commercial mandate with the technical credibility to make smart decisions along the way. That’s a very different brief from “find the best AI technologist available,” and it produces a very different shortlist.
The businesses that get this right aren’t the ones with the biggest AI budgets. They’re the ones that treat AI leadership as an organisational and commercial appointment that happens to require technical depth, not the other way around. The brief sets the direction, and when the brief starts from the right place, the search finds the right person.