The new normal: The status quo of AI adoption in SMEs

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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Publication Details

Journal
Journal of Small Business Management
Published
2024-08-13
DOI
https://doi.org/10.1080/00472778.2024.2379999
Citations
123
Primary Topic
Innovation and Knowledge Management
Type
article
Field-Weighted Citation Impact
68.22
Controls
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article

The new normal: The status quo of AI adoption in SMEs

Dominik K. Kanbach, Sascha Kraus, Anna Peters, Paul Jones et al.
123 citations
Journal of Small Business Management
Innovation and Knowledge Management
68.22
article

The new normal: The status quo of AI adoption in SMEs

Dominik K. Kanbach, Sascha Kraus, Anna Peters, Paul Jones, Julia Schwaeke
article en
123 citations

Abstract

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.

Journal of Small Business ManagementVol. 63(3)
Free University of Bozen-Bolzano (IT), University of Johannesburg (ZA), HHL Leipzig Graduate School of Management (DE), Woxsen School of Business (IN), Swansea University (GB)
Gender equality
Openalex Percentile: Top 0%
Innovation and Knowledge Management
68.22
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