Entrepreneurship and artificial intelligence: a bibliometric analysis

María Dolores Redondo-Rodríguez (), Eloísa Díaz-Garrido (), Diana C. Pérez-Bustamante Yábar () and María Ángeles Ramón-Jerónimo ()
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María Dolores Redondo-Rodríguez: Rey Juan Carlos University
Eloísa Díaz-Garrido: Rey Juan Carlos University
Diana C. Pérez-Bustamante Yábar: Rey Juan Carlos University
María Ángeles Ramón-Jerónimo: Pablo de Olavide University

The Journal of Technology Transfer, 2025, vol. 50, issue 4, No 17, 1840-1872

Abstract: Abstract Despite being a new field, Artificial Intelligence (AI) has rapidly become a prolific topic due to the major upsurge in interest shown by researchers worldwide. However, several key aspects of AI remain unexplored. The aim of this paper is to identify and analyse the existing research on the intersection between AI and entrepreneurship. Specifically, we pose two important questions: (1) What research has been conducted so far on AI and entrepreneurship? (2) What have the key themes and concepts been in this field of research from its inception to the present day, and how have they evolved over time? In order to provide an answer to these questions, a descriptive bibliometric analysis of AI and entrepreneurship is proposed through the development of the cognitive structure of this research field. A total of 270 articles from the Web of Science, published between 1987 and 2024, have been analysed by SciMAT. The findings of the study validate the diverse thematic spectrum surrounding the intersection of AI and entrepreneurship: the application of AI methodologies within entrepreneurial research, the emergence of AI-centric business ventures, and the application of AI in entrepreneurship, particularly in critical functions such as decision-making. The key terms have evolved over time, starting with neural networks in the initial period, business models in the second period, and concluding in the latest period with key concepts such as crowdfunding, entrepreneurs, Covid, and e-health. This research offers major contributions to entrepreneurs, and provides significant guidance for future research in this area of study.

Keywords: Artificial intelligence; Entrepreneurship; Bibliometric analysis; SciMAT (search for similar items in EconPapers)
JEL-codes: O3 O30 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10961-024-10165-8

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