The Uneven Impact of Generative AI on Entrepreneurial Performance

Nicholas G. Otis, Rowan Philip Clarke, Solene Delecourt, David Holtz and Rembrand Koning
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David Holtz: University of California, Berkeley
Rembrand Koning: Harvard Business School

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Abstract: There is a growing belief that scalable and low-cost AI assistance can improve firm decision-making and economic performance. However, running a business involves a myriad of open-ended problems, making it hard to generalize from recent studies showing that generative AI improves performance on well-defined writing tasks. In our five-month field experiment with 640 Kenyan entrepreneurs, we assessed the impact of AI-generated advice on small business revenues and profits. Participants were randomly assigned to a control group that received a standard business guide or to a treatment group that received a GPT-4 powered AI business mentor via WhatsApp. While we find no average treatment effect, this is because the causal effect of generative AI access varied with the baseline business performance of the entrepreneur: high performers benefited by just over 20% from AI advice, whereas low performers did roughly 10% worse with AI assistance. Exploratory analysis of the WhatsApp interaction logs shows that both groups sought the AI mentor’s advice, but that low performers did worse because they sought help on much more challenging business tasks. These findings highlight how the tasks selected by firms and entrepreneurs for AI assistance fundamentally shape who will benefit from generative AI.

Date: 2023-12-21
New Economics Papers: this item is included in nep-ain, nep-ent, nep-exp and nep-sbm
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Citations: View citations in EconPapers (2)

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DOI: 10.31219/osf.io/hdjpk

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