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Contributing to entrepreneurship research with artificial intelligence methods: A systematic review

Author

Listed:
  • Tatiana Beliaeva

    (UR CONFLUENCE : Sciences et Humanités (EA 1598) - UCLy - UCLy (Lyon Catholic University), ESDES - ESDES, Lyon Business School - UCLy - UCLy - UCLy (Lyon Catholic University))

  • Sami Ben Jabeur

    (UR CONFLUENCE : Sciences et Humanités (EA 1598) - UCLy - UCLy (Lyon Catholic University), ESDES - ESDES, Lyon Business School - UCLy - UCLy - UCLy (Lyon Catholic University))

  • Adnan Maalaoui

Abstract

Entrepreneurship research is increasingly leveraging AI-based methodologies to uncover novel insights into entrepreneurial phenomena. This study documents the growing integration of AI methods within the field by identifying the topics where AI methods have been most commonly applied, assessing the contributions of AI methods to entrepreneurship research, and highlighting promising directions for future studies. A systematic review of the literature, combined with a bibliometric analysis of 216 empirical journal articles, uncovers key performance metrics and trends in AI-driven entrepreneurship research. The findings reveal five main clusters of entrepreneurial topics explored using AI methods. Additionally, a framework is proposed to categorize the contributions of AI methods based on their role in data collection and measurement, data analysis, or both. The study concludes with a proposed agenda to guide future research utilizing AI techniques.

Suggested Citation

  • Tatiana Beliaeva & Sami Ben Jabeur & Adnan Maalaoui, 2025. "Contributing to entrepreneurship research with artificial intelligence methods: A systematic review," Post-Print hal-05501480, HAL.
    • Handle: RePEc:hal:journl:hal-05501480
    DOI: 10.5465/AMPROC.2025.160bp
    as

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