Hiring Top AI Talent When You’re Not a Tech Giant

Welcome to the HBR Executive Agenda for September 4, 2025.

In This Issue:

• Hiring Top AI Talent When You’re Not a Tech Giant
• Power Moves

AI talent is hard to find and even harder to afford. The New York Times recently reported that Meta offered a 24-year-old AI researcher $250 million over four years to pry him away from a startup.

While megadeals like that are rare, starting salaries for AI talent of $500,000 and up are not. That’s too pricey for many companies that need to build up their AI expertise just as urgently as the tech giants.

So how can “normal” companies compete for AI talent in this environment? I asked several experts to weigh in.

Richard Singer, CEO and co-founder of the startup Radically Human Ventures, believes that you need to provide a deep sense of purpose.

I need AI engineers and data scientists, and I don’t have $100 million to throw around. But what I find is that these guys buy into a purpose.

You need to find a way to talk to their hearts. There were five people I wanted to hire for my AI lab. I had one-hour meetings with each, and I explained our vision for nurturing human potential in the AI age. All five said yes, even though they acknowledged they could make more money elsewhere.

I can’t offer them millions of dollars. But I can offer enough to cover their needs, and if we succeed, I can share the success through stock options. And for now, I can offer purpose. And that’s appealing to many coders, who want to be part of something bigger than themselves.

Ruth Ebeling, a BCG managing director who specializes in people strategy and talent, believes flexible work policies can help level the playing field.

In any employee value proposition, there are the two big questions: Why come, and why stay? For data and AI talent there are several factors that matter deeply in both areas.

The number one ask from this group is the ability to work remotely and flexibly. Engineers are often doing deep work, and they can’t always manage that in an open-plan office with a lot of interruptions and noise. It’s not that they demand to work from home every day, but they want the ability to flex.

Many of these experts also want jobs that have a positive impact on society and humanity. Many are looking to join a company that cares, for example, about responsible AI.

And you need to provide these hires with interesting content. You need to give them fun and interesting work. You can retain them when you continually give them new problems to solve and when you offer mobility. That doesn’t mean just a step up, but an opportunity to grow in stature and compensation and to build a depth of expertise.

Nathan Marston, chief digital and technology officer at Egon Zehnder, thinks companies have to embrace the likelihood of quick turnover and use it to their advantage.

Companies need to acknowledge the fact that they may be able to retain this talent for only a year or two or three before they’ll lose out to the big tech companies.

But they should embrace that. Winning can mean bringing in the talent you need for a fixed period. You’re essentially saying to them: I can’t pay “you won the lottery” salaries because I don’t have that kind of money. But if you come and do an amazing job for me, I can increase your chances to eventually get there.

Get people when they’re young and put them through training programs. After two or three years they will become super valuable, meaning you probably can’t afford to keep them. So, you have to build your hiring strategy around that constant flow.

I also think that we underestimate the power of teams as a retention mechanism. This talent base has choices, and sometimes they’ll want to stay with people they like and respect. That means employers should try hard to build teams based around complementary skills. If you form something that feels special, you might be able to keep a team together for an extended period.

Azeem Azhar, entrepreneur and founder of Exponential View, thinks the key is to make the work interesting and meaningful.

While giants like Amazon wield immense resources, other firms can compete by offering unique advantages that appeal to top AI professionals seeking meaningful impact.

That includes access to proprietary datasets in niche domains—think medical imaging, industrial processes, or materials science. This allows talent to develop robust, specialized AI models that drive real-world innovation.

Smaller companies also offer a healthier work culture, away from the public spotlight, that can attract those valuing balance and substance over a rocket ship.

But to achieve any of this, companies will need to eliminate obstacles and change their processes to deliver on the promise of AI.

Raj Verma, CEO of Single Store, a data technology startup, says the key to attracting AI talent is giving them a chance to innovate.

Startups can’t outbid Amazon or Google for talent—and we don’t try. Big Tech’s strategy is simple: Hire the best people at insane economics that only trillion-dollar companies can afford.

For us, innovation isn’t just important; it’s survival. Innovation gives people a clear line of sight from their work to meaningful impact. That kind of ownership and fulfillment creates opportunities money can’t buy, and it’s what keeps people committed—even when big financial incentives are out there. And the only way we innovate is with the right people.

Our interns don’t work on side projects; they solve real problems from day one. Many stay because they see how fast they can grow in an environment where every contribution matters.

We once hired an intern who solved in two weeks a problem that had stumped us for a year. He made major contributions for years before leaving for Big Tech—proof of both the challenges we face and the capacity of small organizations to cultivate big talent.

It isn’t easy competing for AI talent without deep pockets, but it isn’t hopeless. You need to understand what really motivates this group and create opportunities for these experts to do truly interesting work. You maybe can’t retain them forever, but you can ride their expertise long enough to create fulfilling work that can drive innovation at your company. 

We know you’re short on time, so as we return from the summer season, we’re highlighting some of our favorite actionable insights from HBR Executive so far.

Don’t conflate uncertainty with volatility. 

While they often co-exist, treating them as the same can lead to misguided decisions, such as hesitating when you should be experimenting or overreacting when you need to build resilience.

(From: “Overcoming the Traps That Prevent Growth in Uncertain Times”)

Think about skills, not jobs. 

In an AI world, roles will constantly shift as tasks are automated and new ones take strategic priority. Knowing which skills you have in your organization—and which skills you need—allows you to adapt quickly, assembling project teams on the fly.

(From: “Assessing Your Talent Needs in the Age of AI”)

When presenting a new strategy to the board, share the solutions you’ve rejected.

Being transparent about the logic behind your final recommendation builds trust and confidence that you chose the right direction. But don’t go too deep into the details or you risk derailing the conversation.

(From: “Presenting a New Strategy to the Board—and Winning Their Buy-In”)