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

Tatiana Beliaeva (), Sami Ben Jabeur () and Adnan Maalaoui
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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)

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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.

Keywords: systematic literature review; method; AI; artificial intelligence; entrepreneurship research; IA; méthode; revue systématique de la littérature; intelligence artificielle; recherche en entrepreneuriat (search for similar items in EconPapers)
Date: 2025-07-25
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Published in AOM 2025 Annual Meeting, Academy of Management, Jul 2025, Copenhagen, Denmark. ⟨10.5465/AMPROC.2025.160bp⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05501480

DOI: 10.5465/AMPROC.2025.160bp

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