AI-native Startups Favor Senior, Elite Talent Over Entry-Level Workers
A Harvard study reveals AI-native startups are 25% smaller, employ 13% more engineers, and have 15% fewer entry-level workers and managers compared to non-AI peers. They favor senior, elite-educated, Silicon Valley-based, and male hires, suggesting AI may concentrate opportunity rather than democratize it.
Key points
- AI-native startups are defined by using AI internally to boost employee productivity and embedding it in products for customer automation.
- Researchers found AI-native startups to be 25% smaller, employing 13% more engineers, and having 15% fewer entry-level workers and managers compared to non-AI peers.
- The workers hired by AI-native startups are likely to be graduates from elite institutions, concentrated in Silicon Valley, and male.
- The study suggests that AI may be concentrating opportunity rather than democratizing it, contradicting the hopeful narrative that AI would bring more job opportunities.
A recent study by Harvard Business School and INSEAD has shed light on the hiring practices of AI-native startups. The researchers, Rembrand Koning and Hyunjin Kim, examined Y Combinator startups from 2020 to 2024 alongside a broader set of US venture-backed firms. They found that AI-native startups are 25% smaller, employ 13% more engineers, and have 15% fewer entry-level workers and managers compared to non-AI peers.
The study's findings suggest that AI-native startups favor senior, elite-educated, Silicon Valley-based, and male hires. This contradicts the hopeful narrative that AI would bring more job opportunities and democratize access to education and employment. Instead, the study suggests that AI may be concentrating opportunity, making it more difficult for marginalized groups to break into the industry.
The implications of this study are significant, as they suggest that the benefits of AI may not be evenly distributed. While AI-native startups may be creating more value per employee, they are also perpetuating existing inequalities in the industry. As the use of AI continues to grow, it is essential to address these issues and ensure that the benefits of AI are shared by all.
Sources
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