Researchers from Harvard Business School and INSEAD have released a working paper that challenges the optimistic narrative surrounding the AI boom. By comparing Y Combinator‑backed startups launched between 2020 and 2024 with a broader set of U.S. venture‑backed firms, the study shows AI‑native companies are markedly different in how they staff their organizations.
AI‑native startups—defined as firms that both use artificial intelligence internally to boost employee productivity and embed AI into their customer‑facing products—are about 25% smaller in headcount than comparable non‑AI ventures. Despite the smaller size, they employ 13% more engineers, indicating a heavier technical focus. The composition of their workforce also diverges sharply: entry‑level employees and mid‑level managers make up roughly 15% fewer positions, while senior staff represent 20% more of the workforce.
Hiring patterns diverge from expectations
The study’s authors, Rembrand Koning and Hyunjin Kim, note that the talent these firms do hire tends to come from a narrow demographic slice. Graduates of elite universities dominate the ranks, and the majority are based in Silicon Valley. Male employees outnumber females, reinforcing a gender imbalance already prevalent in the tech sector. Valuations of AI‑native startups remain comparable to those of their non‑AI counterparts, suggesting that the higher concentration of senior, technically skilled staff translates into greater value created per employee.
These findings run counter to the hopeful view that AI will democratize access to high‑skill jobs. Proponents have argued that AI tools could enable junior workers to “punch above their weight” and lower the technical bar for entry‑level positions. Instead, the data points to a consolidating effect, where the most credentialed workers reap the bulk of new opportunities.
The authors warn that this concentration could exacerbate existing inequality. If AI accelerates learning for those already equipped to leverage it, “differential adoption rates may translate into widening performance gaps,” they write. The implication extends beyond individual firms to the broader ecosystem of entrepreneurs and investors.
Outside the startup world, the labor market already reflects similar trends. Recent graduates now account for just 7% of new hires at major tech companies, and AI is reportedly “killing the summer internship.” Big‑tech giants such as Meta and Microsoft have cut tens of thousands of jobs as they shift spending toward AI‑driven initiatives. At the same time, demand for top‑tier talent remains fierce; Amazon Web Services announced a $1 billion investment in forward‑deployed AI engineers.
Overall, the Harvard‑INSEAD paper paints a nuanced picture of the AI boom. While AI‑native startups generate comparable valuations with fewer employees, they do so by concentrating senior, elite talent rather than opening doors for a broader pool of workers. The study suggests that without deliberate policy or corporate interventions, the AI wave may deepen, rather than narrow, existing disparities in the tech labor market.
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