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The recent surge in the adoption of artificial intelligence (AI) by small and medium-sized enterprises (SMEs) has garnered significant research attention. However, the existing literature reveals a fragmented landscape that hinders our understanding of how SMEs use AI. We address this through a systematic literature review wherein we analyze 106 peer-reviewed articles on AI adoption in SMEs and categorize states and trends into eight clusters: (1) compatibility, (2) infrastructure, (3) knowledge, (4) resources, (5) culture, (6) competition, (7) regulation, and (8) ecosystem: according to the technology–organization–environment model. Our research provides valuable insights and identifies significant gaps in existing literature, notably overlooking trends identification as a pivotal driver and neglecting legal requirements. Our study clarifies AI implementation within SMEs, offering a holistic and theoretically grounded perspective to empower researchers and practitioners to facilitate more effective adoption and application of AI within the SME sector.
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Schwaeke et al. (Tue,) studied this question.
synapsesocial.com/papers/68e5c751b6db64358755da47 — DOI: https://doi.org/10.1080/00472778.2024.2379999
Julia Schwaeke
HHL Leipzig Graduate School of Management
Anna Peters
Stetson University
Dominik K. Kanbach
HHL Leipzig Graduate School of Management
Journal of Small Business Management
Swansea University
University of Johannesburg
Free University of Bozen-Bolzano
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