Welcome to the HBR Executive Agenda on September 4th, 2025.
In this issue:
Hire top AI talent when you’re not a tech giant power move
AI talent is hard to find and even more difficult to afford. The New York Times recently reported that Meta provided $2.5 million over four years, $250 million, to keep him away from startups.
Such Megadeals are rare, but not the departure pay of AI talents over $500,000. That’s too expensive for many companies that need to build AI expertise as urgently as the tech giants.
So, how can a “regular” company compete for AI talent in this environment? I asked a few experts to weigh me.
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Richard Singer is the CEO and co-founder of a radically human venture for startups, and believes it needs to provide a deep sense of purpose.
You need AI engineers and data scientists. There’s no 100 million dollars to throw away. But what I found was that these people are bumping into purpose.
You need to find a way to speak with their minds. There were five people who wanted to hire for my AI lab. I held an hour-long meeting with each of us, explaining our vision to foster human potential in the age of AI. All five said yes, despite admitting they could make more money elsewhere.
We can’t provide millions of dollars. But I can provide enough to cover their needs and if we succeed, we can share success through stock options. And for now, I can provide a purpose. And it appeals to many coders who want to be part of something bigger than you.
Ruth Evering, managing director at BCG, specializing in people’s strategy and talent, believes that flexible work policies will help level the playing field.
There are two major questions about employee value propositions. Why do they come, why do they stay? There are several deep and important factors in data and AI talent in both areas.
The number one question I’d like to ask from this group is that you can work remotely and flexible. Engineers often do deep work and cannot always manage it in an open plan office with lots of interruptions and noise. It’s not that they require them to work from home every day, but they want the ability to succumb.
Many of these experts also want jobs that have a positive impact on society and humanity. Many people are trying to join companies that care about responsible AI, for example.
And you need to provide interesting content to these recruits. You need to give them fun and interesting work. New problems to be solved can be kept when providing mobility. It means not only a step forward, but also an opportunity to grow height and compensation and build depth of expertise.
Nathan Marston, Chief Digital and Technology Officer at Egon Zehnder, believes that businesses need to embrace the possibility of quick turnover and use it to their advantage.
Companies need to acknowledge the fact that they could only maintain this talent for a year or two or three years before losing to a major tech company.
But they should accept it. Winning means bringing the talent you need for a fixed period. You essentially tell them: I don’t have such money, so I can’t pay the salary “You won the lottery”. But if you come and do a great job for me, I can increase your chances.
Get people when they are young and put them through training programs. In a few years, they will become incredibly valuable. This means that you probably can’t afford to keep them. Therefore, it is necessary to build a recruitment strategy around that constant flow.
I also think that the team’s strength is underestimated as a retention mechanism. This talent base has options and sometimes they want to be with people they like or respect. This means that employers need to try to build their teams based on complementary skills. If you form something special, you may be able to keep your team together for a long time.
Entrepreneur and founder of exponential views, Azeem Azhar believes the key is to make work interesting.
Giants like Amazon behave huge resources, but other companies can compete by offering unique benefits that appeal to top AI professionals seeking meaningful impact.
This includes access to your own dataset in your niche domain. This should be considered medical imaging, industrial processes, or materials science. This allows talent to develop robust, specialized AI models that drive real-world innovation.
SMEs can also move away from the public spotlight, provide a healthier workplace culture and attract the important balance and substance of rocket ships.
However, to achieve this, businesses will need to eliminate obstacles and change their processes to fulfill their AI promises.
Raj Verma, CEO of Single Store, a data technology startup, says the key to attracting AI talent is giving them the opportunity to innovate.
Startups can’t outperform Amazon or Google because of their talent. Big Tech’s strategy is simple. It’s about hiring the best people in insane economics that only sign companies can buy.
Innovation is not important to us. It’s survival. Innovation gives people a clear view, from their work to their meaningful impact. Such ownership and fulfillment create opportunities for money to not be able to buy. That’s what keeps people committed even when there’s a big financial incentive there. And the only way we can innovate is with the right people.
Our interns are not working on side projects. They solve the real problem from day one. Many people stay because they can see how fast they can grow in an environment where every contribution is important.
We once hired an intern who solved the problems that baffled us for a year in two weeks. He made a great contribution over the years before leaving big skills to prevent both the challenges we face and the ability of small organizations to develop great talent.
Competing for AI talent without deep pockets is not easy, but it’s not hopeless. You need to really motivate this group and understand what creates opportunities for these professionals to do truly interesting work. You may not be able to hold them forever, but you can ride expertise long enough to create fulfilling jobs that can drive innovation in your company.
As you know you have shorter times, when you come back from the summer season, we highlight some of our favorite practical insights from HBR executives so far.
Don’t confuse uncertainty with volatility.
They often coexist, but treating them as the same can lead to misguided decisions, such as reluctance to when it is necessary to build resilience.
(from: “Overcoming traps that hinder growth during uncertain times”)
Think about your skills, not your work.
In the AI world, roles change constantly as tasks are automated and new things take strategic priorities. Knowing which skills you have and what skills you need in your organization will allow you to quickly adapt and build your project team on the spot.
(from: “Evaluating the needs of talent in the age of AI”)
When presenting a new strategy to the board, share the rejected solutions.
Being transparent about the logic behind the final recommendations builds confidence and confidence that you have chosen the right direction. But don’t go into the details too deeply. Otherwise, you risk derailing the conversation.
(from: “Submit a new strategy to the board and win buy-in”)
