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<p>Entrepreneurship research is increasingly adopting artificial intelligence (AI)-based methods to gain new insights into entrepreneurial phenomena. We document this surge by mapping the principal topical applications of AI methods, their contributions to entrepreneurship research, and the most promising avenues for future inquiry. A systematic literature review and bibliometric analysis of 142 journal articles reveal key performance metrics and trends of AI-enabled entrepreneurship research. The results indicate a growing use of AI methods to examine a range of entrepreneurial phenomena, including the entrepreneurial process, venture capital, crowdfunding, performance, innovation, and digitalization. We further develop a framework illustrating how AI methods contribute to theory testing and theory building through their integration into data collection and measurement, data analysis, or both. Finally, we outline a roadmap to guide future research leveraging AI methods.</p>

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The adoption of artificial intelligence methods in entrepreneurship research: current state and pathways forward

  • 期刊论文

  • 发表日期：

    2026年4月10日

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  • Tatiana Beliaeva,
  • Sami Ben Jabeur,
  • Adnan Maalaoui

摘要

Entrepreneurship research is increasingly adopting artificial intelligence (AI)-based methods to gain new insights into entrepreneurial phenomena. We document this surge by mapping the principal topical applications of AI methods, their contributions to entrepreneurship research, and the most promising avenues for future inquiry. A systematic literature review and bibliometric analysis of 142 journal articles reveal key performance metrics and trends of AI-enabled entrepreneurship research. The results indicate a growing use of AI methods to examine a range of entrepreneurial phenomena, including the entrepreneurial process, venture capital, crowdfunding, performance, innovation, and digitalization. We further develop a framework illustrating how AI methods contribute to theory testing and theory building through their integration into data collection and measurement, data analysis, or both. Finally, we outline a roadmap to guide future research leveraging AI methods.