AI-native startups are hiring fewer entry-level workers, Harvard study finds

• In a new study, researchers at Harvard Business School analyzed AI-native startups.
• These are startups that leverage AI to automate work and in the products they build.
• They have fewer workers, more technical talent, and a flatter management structure.

AI, it seems, is for the experts.

In a new working paper, researchers at Harvard Business School and the nonprofit business school, INSEAD, found that AI-native startups are building smaller, flatter teams with fewer entry-level workers than their non-AI peers.

The study, titled "AI-Native Firms," examined Y Combinator startups from 2020 to 2024 and a broader set of US venture-backed startups whose first financing closed during the same period.

The paper defines a new category of "AI-native startups" characterized by two shifts in productivity. The first is the process channel: They use AI inside the company to make employees more productive, such as helping them code, sell, design, or coordinate work faster. The second is the product channel: They embed AI directly into what the company sells, so customers can use the product to perform work that once required human teams.

AI-native startups are 25% smaller, with about 13% more engineers, and their shares of entry-level workers and managers are each roughly 15% lower than non-AI-native startups.

The findings test a broadly accepted premise of the AI boom: AI is reshaping the bottom rungs of the career ladder. Entry-level workers are using it to take on bigger responsibilities sooner and automate routine tasks. This comes as vibecoding has also made it easier for non-engineers to turn ideas into prototypes, blurring the threshold and need for technical talent.

However, the paper found that the AI is creating a greater demand for expert-level talent. The share of senior workers at AI-native startups is 20% higher, and these companies tend to attract a specific type of worker.

"AI-tagged firms employ smaller teams of more talented and technical workers. These workers are especially likely to be graduates from elite institutions, concentrated in Silicon Valley, and male," the authors wrote.

That suggests AI-native startups may not be democratizing access to opportunities so much as concentrating opportunity among already-credentialed, highly technical workers.

The authors' bigger concern is how that will affect demographic gaps.

"If AI tools accelerate learning for those who use them, differential adoption rates may translate into widening performance gaps — both for individual workers within firms and for the entrepreneurs who found them," the researchers wrote.