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Generative Artificial Intelligence (GenAI) in entrepreneurial education and practice: emerging insights, the GAIN Framework, and research agenda

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  • Yogesh K. Dwivedi

    (King Fahd University of Petroleum & Minerals
    King Fahd University of Petroleum and Minerals (KFUPM))

Abstract

Generative AI (GenAI) is reshaping entrepreneurship by transforming the landscape of innovation, education, and ethical practices within the entrepreneurial domain. This paper provides a comprehensive review of the nascent yet impactful scholarly discourse on the role of GenAI (e.g., ChatGPT, DeepSeek, and Google Gemini) in entrepreneurship. Drawing from 39 studies, it examines four emerging themes: technology adoption, education and skill development, innovation, and performance enhancement. The analysis highlights GenAI's transformative potential to democratize entrepreneurial resources, foster creativity, and improve decision-making. However, it also identifies pressing challenges, including ethical data practices and equitable access. The paper proposes and presents the GAIN Framework along with five associated research propositions to guide future research in this domain. It concludes by emphasizing the need for a balanced integration of human ingenuity and AI capabilities, while raising critical questions about fostering ethical inclusivity and driving innovation.

Suggested Citation

  • Yogesh K. Dwivedi, 2025. "Generative Artificial Intelligence (GenAI) in entrepreneurial education and practice: emerging insights, the GAIN Framework, and research agenda," International Entrepreneurship and Management Journal, Springer, vol. 21(1), pages 1-21, December.
    • Handle: RePEc:spr:intemj:v:21:y:2025:i:1:d:10.1007_s11365-025-01089-2
    DOI: 10.1007/s11365-025-01089-2
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    References listed on IDEAS

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    Cited by:

    1. Anna Kusetogullari & Huseyin Kusetogullari & Martin Andersson & Tony Gorschek, 2025. "GenAI in Entrepreneurship: a systematic review of generative artificial intelligence in entrepreneurship research: current issues and future directions," Papers 2505.05523, arXiv.org.

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