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The Uneven Impact of Generative AI on Entrepreneurial Performance

Author

Listed:
  • Otis, Nicholas G.
  • Clarke, Rowan Philip
  • Delecourt, Solene
  • Holtz, David

    (University of California, Berkeley)

  • Koning, Rembrand

    (Harvard Business School)

Abstract

Scalable and low-cost AI assistance has the potential to improve firm decision-making and economic performance. However, running a business involves a myriad of open-ended problems, making it difficult to know whether recent AI advances can help business owners make better decisions in real-world markets. In a field experiment with Kenyan entrepreneurs, we assessed the impact of AI advice on small business revenues and profits by randomizing access to a GPT-4-powered AI business assistant via WhatsApp. While we are unable to reject the null hypothesis that there is no average treatment effect, we find the treatment effect for entrepreneurs who were high performing at baseline to be 0.27 standard deviations greater than for low performers. Sub-sample analyses show high performers benefited by just over 15% from the AI assistant, whereas low performers did about 8% worse. This increase in performance inequality does not stem from differences in the questions posed to or advice received from the AI, but from how entrepreneurs selected from and implemented the AI advice they received. More broadly, our findings demonstrate that generative AI is already capable of impacting—though in uneven and unexpected ways—real, open-ended, and unstructured business decisions.

Suggested Citation

  • Otis, Nicholas G. & Clarke, Rowan Philip & Delecourt, Solene & Holtz, David & Koning, Rembrand, 2023. "The Uneven Impact of Generative AI on Entrepreneurial Performance," OSF Preprints hdjpk_v1, Center for Open Science.
    • Handle: RePEc:osf:osfxxx:hdjpk_v1
    DOI: 10.31219/osf.io/hdjpk_v1
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