Where to Find AI Talent for Senior Leadership Roles

Where can you find AI talent for senior leadership roles?

Find senior AI talent among digital transformation and data science leaders first, and treat AI engineering as a minor source. In a sample of 1,000 AI Strategy leaders in our network, 77% have worked in digital transformation and 61% in data science. Only 12% have worked in AI engineering.

Most searches go wrong on that last figure. A brief written around model-building screens out most of the people who run AI strategy at director, VP and C-suite level. They came up through transformation programs and data teams, and that holds at every level: transformation experience runs from 74% among VPs to 81% in the C-suite. Product and data engineering are smaller feeders, each at 26% of our sample, against 12% for AI engineering.

The work these leaders have done looks like change management with AI at the center. One director at a large public-sector organization led an internal push to adopt AI across its global policy teams, and a three-week intervention raised AI use by 68%. Nothing in that sentence requires an engineering background. It requires someone who can get a large organization to change how it works.

LinkedIn's Economic Graph research, which covers AI talent across the whole workforce rather than senior leaders alone, points the same way: companies can grow their AI talent pipeline 8.2x globally by focusing on skills over degrees or job titles.¹ At the leadership level, the skill that matters most is having run the kind of change you are hiring for. So start where that experience sits: transformation offices, data science leadership and, further down the list, product. Where exactly you start depends on the level you are filling.

Which AI talent sources feed each leadership level?

Data science and transformation feed every level, but the C-suite draws more on startups and AI governance. In our sample, C-suite leaders are more likely than directors to have startup, AI governance and AI architecture experience. A C-suite search should reach into startups and governance work. A director search can stay closer to data science.

Startups are the clearest split. 64% of C-suite leaders in our sample have startup experience, against 38% at both director and VP. With a gap of 1.7x, a chief AI officer shortlist that skips startup operators leaves out most of the C-suite pool.

Governance follows the same pattern. 32% of C-suite leaders have worked in AI governance, against 18% of directors, a ratio of 1.8x. AI architecture shows a smaller lift: 29% at C-suite against 19% at VP. The top role draws on risk and systems design backgrounds more often than the roles beneath it.

Data science runs the other way, slightly. Directors in our sample are the most likely to have worked in it, at 64%, against 58% in the C-suite.

Some C-suite careers combine several of these. One C-suite technology leader in our network built a global software, AI and transformation consultancy to more than 70 people across four regions, running engineering, AI, product and delivery teams, and grew revenue 13-fold in nine months. That founder-operator path is the startup experience the C-suite figures point to.

So write a different source list for each level. For a director, start with data science and transformation leads. For the C-suite, add founders, startup operators and the people who have built AI governance programs. The next question is who works that list.

Should you use an AI talent agency or search firm?

Use one if your own network does not reach the people this pool is drawn from. Most senior AI leaders do not sit in AI engineering circles. They sit in transformation offices, data science groups, startups and governance teams.

The channel question is a question of reach. If your leadership team already knows the transformation and data leaders in your industry, and can name the startup operators and governance leads worth a call, a direct search can work. If your network runs mostly through engineering, it will surface the 12% and miss the rest.

The brief matters more than the channel. A recruiter handed a brief that asks for an AI engineering background will search the same narrow lane your own network would. Give any partner, internal or external, the level-specific source list above, not a technical background to match.

We cover the full trade-off, including when each route fits, in our guide on whether you need an AI headhunter or can hire directly. If you want a partner that searches across these adjacent functions, that is the work our AI executive search practice is built for.

Does location limit a senior AI search?

Less at VP level than at director level. Of the AI Strategy postings we analyzed that state a work model, 42% of VP postings are fully remote, against 28% of director postings. Across all three levels the figure is 36%.

Our data does not rank cities or regions. If you want to know which metro has the deepest bench of AI leaders, this analysis cannot tell you.

It does show that employers hiring at VP level are more often willing to look past a single metro. Hold a VP search to one city and you are working under a tighter constraint than many of the employers competing with you for the same people.

Director searches are more local. Fewer than a third of director postings that state a work model are fully remote, so a director search is more often a regional one. That is no reason to lower the bar, but it is a reason to know the local transformation and data leaders well, since the pool within commuting distance is smaller.

Decide the work model before you write the brief. A remote VP role widens the field across the US and Canada. A hybrid director role narrows it to a commuting radius, and your sourcing should start there. Location sets where you look; the requirements in the brief set who gets through.

What do employers ask for in a senior AI hire?

Employers ask for far less experience than the pool already has: a median minimum of 10 years at VP and 9 at director, in the AI Strategy postings we analyzed. Leaders in our sample bring a median 20 years of professional experience, about 7 of them in AI or data. Years rarely narrow the field. Prior functions do.

C-suite postings ask for the least: a median minimum of only 7 years, the lowest of any level. C-suite leaders in our sample bring a median 20 years, 8 of them in AI or data. The typical leader in the pool clears the posted bar by a wide margin, so a year count in the brief does little to narrow the field.

What does filter is the work a candidate has run. Name the functions the hire must have led: a transformation program, a data science organization, an AI governance framework. One VP at a professional services firm designed and implemented an AI governance and compliance framework for expanding into ML models, copilots and agentic AI, and a redesign of processes around AI lifted operational accuracy by 30%. That is a specific, checkable requirement, and "15+ years" is not.

Degree background will not sort the pool either. Of those in our sample whose field is known, 57% studied computer science or engineering and 18% studied business, finance or economics. The split barely moves between levels. A computer science or engineering requirement screens out the business, finance and economics graduates at every level, without testing what they have led.

For a step-by-step approach to scoping the role and running the process, see our guide on how to run a search for a senior AI role.

Search by prior function, then adjust for level

Senior AI leaders come from adjacent lanes far more often than from AI engineering. Transformation and data science leaders make up the core of the pool at every level. At the C-suite, add startups and AI governance. At VP, expect more room to search beyond one location.

Expect candidates to clear your posted year count easily, and expect most to come from careers outside AI engineering. In every brief, replace the year count with the functions a candidate must have run. That one change opens the search to the people who hold these jobs.