AI helps entrepreneurs produce more, and more polished, ideas, but those ideas tend to be less novel.

Because AI models answer alike, founders who lean on them risk converging on the same crowded markets.

Domain expertise and using AI as a questioner rather than an author help preserve originality.

Picture two entrepreneurs who have never seen each other, with one based in Ho Chi Minh City and the other in Melbourne. On the same evening, each starts a chatbot and asks it for a business idea related to sustainable packaging. Just a few seconds later, they both get well-structured and confident responses. The problem is that the responses are nearly identical.

This is the paradox facing generative AI in the field of entrepreneurship: Although the tool enables each founder to work faster and with greater productivity, it may be causing founders as a group to become less unique. In entrepreneurship, being distinctive is not just an advantage; it is often the objective.

We should be fair to the machine. In a controlled laboratory experiment involving 124 entrepreneurs, Cristofaro and colleagues (2025) found that working with AI increased the number of opportunities participants identified and led to a deeper evaluation of those opportunities. Likewise, Terwiesch and colleagues (2026) found that, on average, ideas produced by large language models had higher purchase intent than human-generated ideas and were seven times more likely to end up in the top 10%.

In terms of volume, speed, and refinement, AI has the advantage. Yet if entrepreneurship amounted to nothing more than coming up with more plausible ideas, then the problem would be settled.

The hidden cost: novelty

The same studies tell another story: In Cristofaro's experiment, AI also decreased both the novelty of the opportunities that entrepreneurs noticed and the innovativeness of the ways........

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