The AI talent you need will not relocate. What to do about it.

Most hiring strategies for senior AI talent begin with a quiet, unexamined assumption: that the right person, offered enough money and a big enough problem, will move to where the company is. For the leaders who matter most, that assumption is wrong, and building around it wastes quarters you do not have.

The scarcity behind this is real and worsening. AI skills are now the single hardest capability for employers to find anywhere, according to ManpowerGroup, and LinkedIn data shows AI job postings rising roughly 78 percent year on year while the available talent pool grew only about 24 percent. When the talent is this scarce, you cannot afford to shrink your own pool further by insisting that people move.

Consider the decision a senior research scientist actually faces. She has spent years building deep expertise. She earns a strong package in a city where her spouse also has a career, her children are in good schools, her commute is short, and her professional network, the people she learns from and might one day hire or join, all live within thirty minutes of her front door. Now imagine asking her to move across the world to a city she has never lived in. Even a large raise and meaningful equity rarely overcome the personal cost. For most of the talent you want, the answer is no before the question is finished.

This is not a failure of your employer brand or your recruiters. It is a structural feature of how global talent markets work, and the world's leading AI organisations have already accepted it. When the most ambitious labs wanted the best computer-vision and language researchers, they did not try to convince those researchers to relocate. They opened offices where the talent already lived. The logic was simple. If the mountain will not move, you go to the mountain.

The constraint is not a variable

The first move is to stop treating the relocation problem as something you can solve with a better offer. It is a constraint to design around, not a number to tune. Founders often respond to early rejections by escalating the package, adding equity, then adding more, and conclude that they simply have not found the magic number. The truth is that for most senior candidates there is no number, because the thing being traded away is not compensation. It is a spouse's career, a child's school year, a decade of friendships, and a professional community that cannot be packed into a shipping container. No equity refresh touches any of that.

Once you accept that the talent will not come to you, three real options remain, and naming them clearly is the start of a better strategy.

You can hire remotely, wherever individuals happen to be. This works for some roles, but for research-intensive AI it has real costs. The best work still emerges from shared context, whiteboard sessions, and the informal exchange that co-location produces. A team scattered thinly across many time zones struggles to build a common culture, and recruiting one person in each of a dozen cities means running a dozen separate campaigns against a dozen different compensation norms. It is slow and expensive, and it tends to produce a collection of individuals rather than a team.

You can lower your bar and hire the people who are willing to move. This is the most common and most damaging choice, because it quietly trades quality for convenience and you do not feel the cost until much later, when the work the team produces is competent rather than exceptional and you cannot quite say why.

Or you can go to where the talent is concentrated and build there. For senior AI talent this is usually the right answer, because the talent is not evenly spread. It clusters in a small number of dense ecosystems, and concentration is exactly what makes a focused effort efficient. It is far easier to meet ten qualified people in one city than one person in each of ten cities.

Going to the talent changes the offer

The most important effect of building where the talent lives is what it does to your value proposition. A role that requires relocation might attract a small fraction of your target pool. The same role, offered in the city where the candidate already wants to be, with the same commute, the same schools, and the same professional network intact, can attract many times more of them. You are no longer asking someone to upend their life. You are offering them an exciting new chapter without the personal cost, and that single change can move your effective addressable pool by an order of magnitude.

This is why a physical presence in a talent-dense location is not a vanity project. It is the single highest-leverage change most companies can make to their senior AI hiring. It converts a hiring strategy that fights human nature into one that works with it. The same recruiter, the same budget, and the same employer brand simply perform better when the ask is reasonable.

Concentration compounds

There is a second, slower benefit. Dense talent ecosystems are self-reinforcing. In a city where the frontier is the default conversation, knowledge flows freely, people move fluidly between the best teams, and strong talent attracts more strong talent. A credible presence there does not just give you access to the people who live in the city today. It gives you a renewable channel into the steady inflow of people who move there over time, and into the graduates that the local universities produce every year. You are not buying a one-time hiring opportunity. You are buying a position next to a pipeline.

What this means in practice

If you are serious about senior AI talent, three principles follow. First, identify where the specific talent you need is genuinely concentrated, not where it is fashionable to have an office. Density of the right skills is the asset, and the right city for vision researchers may not be the right city for systems or for applied science. Second, commit to a real presence there, even a small one, because a credible local anchor and a founding-team story will pull candidates that a remote listing never will. A serious presence signals that the work is serious. Third, treat the first hire in any new location as the most important one, because that person sets the bar, represents you to the local community, and makes every subsequent hire easier. The wrong anchor leader can quietly cap the quality of everyone who follows.

There is also a signalling effect worth naming. Establishing a real presence in a talent-dense ecosystem tells investors, candidates and competitors that you intend to compete for talent at the highest level. That signal, backed by genuine commitment, becomes part of why the best people are willing to take the call.

The companies that win the AI talent race are not the ones with the biggest budgets. They are the ones that understood early that you do not move the talent. You go to it. The rest is execution: choosing the right location, committing to it properly, and getting the first hire right. Do those three things and the hardest part of building a world-class AI team becomes merely difficult, rather than impossible.