Do You Need a Head of AI?

Do you need a head of AI at all?

You need a dedicated AI leader when AI work has no single owner who can win executive backing for it. If one of your existing executives already decides which use cases get pursued and has the CEO's ear, you can wait. The signs that you can't wait are familiar: pilots that never reach production, AI spend scattered across teams with nobody accountable for it and board questions about AI that nobody in the room can answer.

Sponsorship is the real problem. In a Dataiku and Harris Poll survey, 70% of CEOs claimed the greatest influence on AI strategy, but only 6% are involved in nearly all the decisions that determine whether that strategy succeeds.¹ AI programs stall in that gap. Someone has to carry executive backing into the rooms the CEO isn't in, and keep carrying it after the kickoff meeting.

Employers know this. In the AI job postings we analyzed, winning executive backing is a main emphasis at director, VP and C-suite level alike. Candidates tell a different story: in a sample of 1,000 AI Strategy leaders in our network, it is only a moderate emphasis on resumes at every level. Leaders write about what they built and delivered. They say less about how they got the business to fund and adopt it.

So a head of AI exists largely to hold sponsorship, and that is the capability to test for in interviews. Ask candidates to walk you through a program they kept alive after the executive who launched it moved on. If you are not sure you need someone full time yet, weigh whether a permanent or fractional AI leader fits your stage before you open a search.

What does a head of AI do that a CTO doesn't?

A head of AI owns the redesign of roles, processes and decision rights around AI, and the choice of which use cases to pursue. A CTO or CIO runs the technology estate. Neither is usually accountable for changing how the business works because of AI, and that accountability is the core of the job.

Employers are clear about this. In the AI job postings we analyzed, redesigning roles, processes and decision rights around AI is a main emphasis at every level, and so is choosing which AI use cases to pursue. Those two duties sit at the center of the role whether the title says director or Chief.

Candidates rarely lead with either. In a sample of 1,000 AI Strategy leaders in our network, operating-model redesign is only a minor emphasis on the resumes of director and C-suite leaders, and a moderate one for VPs. The work employers most want is the work candidates least advertise. A resume screen won't find it, and a hiring team that filters on the resume will drift toward the builders.

The capability does show up when someone has it. One C-suite leader in financial services in our network got executives to adopt AI-driven decision systems across risk and growth, which raised visibility into portfolio performance by 32%. The achievement is executives changing how they decide, not a model.

Screen for this directly. Ask for a specific process that changed because of AI, who lost or gained a decision because of it and how the candidate handled the people on the losing side. The Chief AI Officer role is built around the same mandate at the top of the house.

Is a head of AI the same as a director of AI?

No. A head of AI title can sit at director, VP or C-suite level, and the level changes the job. Director-level postings lean toward hands-on delivery, while C-suite postings carry board exposure.

The AI job postings we analyzed show the split plainly. Director postings mention AI agents or agentic AI more often than C-suite postings, 38% against 29%. That is a delivery signal: the director is expected to know the current tooling and get it shipped. C-suite postings mention the board of directors more often than director postings (9% vs 3%). The senior role answers upward as well as down.

Years of experience are a poor guide to which of these you are hiring. C-suite postings ask for fewer minimum years than director postings, a median of 7 against 9, and VP postings ask for the most at 10. A years threshold will screen out good people and tell you nothing about scope.

Decide the level by scope and reporting line. If the person will report to the CEO, present to the board and own the AI agenda across business units, you are hiring at the top whatever the title says. If they will report to the CTO and own delivery of a portfolio of AI products, you are hiring a director and should expect more hands-on agent and platform work. Write the title last.

What background should an AI leader have?

Look for someone who has owned a budget and understands how models, data and systems fit together. A doctorate is optional.

In a sample of 1,000 AI Strategy leaders in our network, 82% of C-suite leaders have owned a budget, against 65% of directors; VPs sit close to the C-suite at 78%. Architecture experience is rarer across the board, but C-suite leaders have worked in AI Architecture one and a half times as often as VPs (29% vs 19%). The C-suite group includes founders and chiefs of small companies, so the comparison is about the scope a person has held, not their pedigree.

Employers mostly don't ask for a PhD. Only 9% of the AI job postings we analyzed mention a PhD or doctorate. For a leader whose job is use-case choice and operating-model change, budget ownership is the more useful filter.

Budget ownership matters because it forces the habit of proving a return. One VP at a very large company in our network ran ROI analysis on AI projects and showed a 3x return on AI technology investments within 12 months. That is the evidence a board asks for, and a head of AI should be able to produce it without help from finance.

Which AI leadership duties can stay with existing executives?

Build, buy or partner decisions, budgets and sequencing can stay with your CTO and CFO. Use-case choice and operating-model change need the dedicated owner. Security and governance stay with your risk functions, with the head of AI accountable for feeding them every use case.

The emphasis data points the same way. In the AI job postings we analyzed, build, buy and budget work gets only moderate emphasis from employers at every level, and so does understanding how models, data and systems fit together. Leaders see it differently. In a sample of 1,000 AI Strategy leaders in our network, build, buy and budget work is what their resumes lead with, at every level. A typical example: one VP at an IT services firm retired a legacy CRM for a custom AI-native platform, eliminating about $1.3 million a year in licensing and integration costs. It is valuable work, and exactly the kind your CTO and CFO already know how to run.

If you hire for a duty your executives already cover, you pay for work that is already done and still leave use-case choice without an owner. Write the role around what nobody owns today, and screen past the build-and-buy wins that dominate the resumes.

Governance needs a clear handoff. In a KPMG survey, 91% of leaders cite data security, privacy and risk as the top factor influencing AI strategy over the next six months, up from 58% in Q1.² Your head of AI does not need to run security. They do need to make sure nothing reaches production without passing through the people who do.

Hire the head of AI for the job nobody owns

A head of AI earns the salary when nobody in your company owns the decision of which AI use cases to pursue and how the business reorganizes around them. Employers make that work a main emphasis while candidates' resumes give it little space, so the hire depends on screening for it directly.

Set the level by scope and reporting line, not by the title or a years threshold. Leave build, buy and budget calls with the executives who already make them, and keep security with your risk functions. Then hire for two things: the ability to hold executive sponsorship after the launch, and a record of changing how people work. If you want help finding leaders who have done both, our AI executive search practice works on exactly these hires.