AI Startups Are Growing Faster With Smaller Teams, Study Finds

Artificial intelligence-powered startups are operating with significantly smaller workforces than traditional startups while achieving similar levels of funding and valuation, according to new research from Harvard Business School and INSEAD. The findings suggest AI-native companies are reshaping how modern businesses are built by relying on leaner organizational structures rather than larger teams.

The study examined nearly 50,000 venture-backed startups listed by Y Combinator and PitchBook that were launched between 2020 and 2024. Researchers Hyunjin Kim of INSEAD and Rembrand Koning of Harvard Business School found that AI-native startups employ about 25% fewer workers than conventional startups. These firms also have approximately 15% fewer entry-level employees and 15% fewer managers, resulting in flatter organizational hierarchies while maintaining comparable business value.

The researchers noted a sharp increase in AI-focused startups during the period studied. Among Y Combinator companies, the number of AI first deals recorded in 2024 was nearly eight times the average seen in 2020. AI-native firms were identified using Y Combinator’s AI self-tagging methodology.

Although AI startups generally employ fewer people, the researchers believe the expansion of AI-related business activity could still create additional demand for labor overall. Engineering talent plays a much larger role in these organizations, with AI companies employing a 13% higher share of engineers than non-AI startups.

The study found that many AI-native businesses are using artificial intelligence not only to improve internal workflows but also as the foundation of their products and services. According to the researchers, embedding AI into products has become “a primary way startups are scaling knowledge work without large teams of knowledge workers.”

Compared with conventional startups, AI-native firms place greater emphasis on engineering roles while reducing staffing in sales, finance, administration and operations. Their workforces also tend to be more experienced, with nearly 15% fewer entry-level employees and roughly 20% more senior workers. The researchers described these companies as “small teams of skilled founders building ventures that historically might have required much larger hierarchical organizations.”

Despite their reduced headcount, AI startups secure funding and valuations comparable to those of non-AI firms. As a result, they raise approximately 20% more capital per employee and achieve higher valuations per employee than traditional startups.

The research also found that many of these companies are concentrated in Silicon Valley, where employees are more likely to be male, possess advanced degrees and come from prestigious employers and educational institutions.

Researchers identified several ways AI is being applied within these startups. Around 43% use AI to fully automate tasks previously completed by workers, while another 24% develop AI tools designed to enhance the productivity of employees at client companies. An additional 15% focus on building AI infrastructure that other developers integrate into their own AI applications.

Kim and Koning said the findings may have implications beyond the startup ecosystem. “AI may not simply make existing organizations more efficient – it may change what organizations look like and do,” they wrote, adding that businesses may increasingly integrate capabilities from foundation models instead of building them through larger internal teams.

The trend may also affect job seekers entering the workforce. Eva Chan, a career expert at Resume Genius, said, “A growing share of employers are never going to post jobs. Most workers rely on early roles as stepping stones to build experience — yet those stepping stones are being engineered out of the companies everyone is chasing.”