Bibliometric analysis reveals trends in artificial intelligence adoption in entrepreneurship, indicating interdisciplinary growth and gaps.
This study investigates the academic landscape surrounding artificial intelligence (AI) affordances and adoption in entrepreneurial practice, offering a bibliometric analysis of its evolution, intellectual structure, and emerging directions. Drawing on 114 publications indexed in Scopus from 2000 to 2024, the study employs Microsoft Excel for performance metrics and VOSviewer for science mapping. It systematically examines trends in publication volume, citation impact, co-authorship networks, institutional contributions, and methodological preferences. Findings reveal a sharp increase in scholarly output over the past five years, with 2024 showing notable acceleration. Research activity is predominantly centred in Europe and Asia, marked by robust international collaborations, yet Africa and the Middle East remain underrepresented. Quantitative methods dominate the field, though qualitative and mixed-methods approaches are gaining traction. Theoretical frameworks largely rely on adoption models such as TAM and UTAUT, while recent studies introduce broader institutional and entrepreneurial lenses. Although limited to Scopus-indexed literature, the analysis identifies significant gaps in geographic coverage, methodological variety, and theoretical expansion, offering valuable insights for future research. As a comprehensive bibliometric mapping of this domain, the study provides researchers and practitioners with a synthesised view of influential authors, journals, institutions, and thematic developments, fostering interdisciplinary engagement and guiding future research trajectories.
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Nettey et al. (2026) studied this question.
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