The competition for top AI talent is fierce. Not only are all the major AI tech players seeking to create and fill AI leadership roles, but startups and non-tech businesses in healthcare, financing, manufacturing and more are eager to find executives to drive their AI initiatives forward.
While compensation is of course important, it has been receiving a disproportionate amount of headlines and attention. But money isn’t everything. In my experience, there are seven key factors beyond the dollars that entice AI talent to move.
1. Value Creation
As organizations begin to better understand AI, its potential and the ability of their infrastructure to leverage it, some organizations are better positioned to create value from AI-fueled initiatives than others.
For example, we worked with one candidate who left a Tier One tech organization to work for a relatively obscure manufacturer. Why? Because they identified an opportunity to leverage automation and novel AI technologies to triple the value of this small-cap publicly traded company.
If you are an AI leader—especially one whose compensation depends on the employer’s stock price—the opportunity to create outsized value can easily outweigh base compensation.
2. Proprietary Offline Datasets
According to Epoch AI, AI companies will run out of high-quality publicly available language data as soon as 2026. With that low-hanging fruit already plucked, AI tech leaders will be drawn to companies that can offer proprietary, unpublished datasets that no one else has access to (and yes, this includes datasets that are a mess or are not yet digitized—or both).
The right set of proprietary data will enable AI leaders to build services and products that no one else in the world can. As a result, I believe that the proprietary data a company produces, acquires or has access to will play an increasingly larger role in a company’s valuation relative to its core product lines and revenue.
3. Open-Source Technology
Many of the top technology companies require their AI teams to exclusively use the in-house technology they’ve built; similarly, they play their cards close to the vest in terms of publishing research. For some AI tech leaders, organizations that embrace open-source technologies can be a significant pull.
By going with an open-source-based organization, AI researchers often have the opportunity to publish their findings, share their work and use the latest tools and techniques. Not only is this an ego boost, but building your name in the AI community is one of the best ways to secure future roles. Similarly, working with open-source technology means skills will more easily transfer to the next position, helping candidates avoid the feeling of being trapped by their skills or left behind.
4. Speed Of Delivery
In a world where AI technology is changing by the minute, taking months to ship a product is an eternity. Organizations that enable their executives to rapidly iterate are significantly more attractive than companies that traditionally take months or even years to roll out new products.
This factor is usually an advantage for smaller or early-stage companies who, quite frankly, don’t have as much to lose if a proof of concept doesn’t work out. Without having to worry about shareholders, regulators or large customer bases, these organizations give AI executives the chance to charge ahead.
5. A Seat At The Table
This is a familiar desire for AI and non-AI talent alike: Everyone wants to be in the room where it happens. But for AI talent, a seat at the table takes on added importance, as this visibility helps ensure their research and ideas come to fruition instead of being sidelined or canceled in favor of other initiatives.
This factor may have more of an impact on specific types of AI leaders, especially research- and data-science-focused leaders who are used to working with larger, more established organizations. By giving these people the ability to own the research road map and agenda, unencumbered by legacy architectures or tech, organizations can lure these leaders with the rare opportunity to bring their vision to reality free of the confines of existing decisions.
6. Work Flexibility
This is also a familiar factor. Just like the rest of us, it turns out that AI executives like the option to work from home.
While it sounds minor, it’s a feature that can make an organization more attractive compared to a larger, well-heeled competitor. We had one candidate who was offered a top position at a leading Silicon Valley tech firm, but it would require relocating his family from his home in Hawaii. Guess how that turned out.
7. Impact
Almost all of the best tech leaders were drawn to tech because they had a passion for solving problems, not just making money.
Many organizations have products, markets or missions that make them more attractive in terms of the impact the AI leader can have. Think about it this way: A massive amount of tech talent over the past two decades has been focused on advertising. But 20 years later, is improving click-through rates still something that inspires everyone to get out of bed?
Organizations leveraging AI to solve problems in fields like health, sports, entertainment, automotive, the environment and other passion fields have the ability to offer AI executives the chance to change not just a company, but an industry or even the world.
Making The Case Beyond Compensation
Make no mistake; compensation matters. Yet, every day we see AI leaders leaving higher-paying positions with top-name tech leaders to take less salary, join smaller organizations or enter non-tech industries. By understanding what truly drives talent, you can better position your organization to attract a level of AI executive that compensation alone might not secure.
