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Cited by 241Impact of AI and Big Data on Business and SocietyArtificial Intelligence ApplicationsTechnology Adoption and User Behaviour

The DOI matches its Crossref record; 143 of the 144 references it cites were found in a registry or an index.

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

Open access
Schwaeke, Julia, Peters, Anna, Kanbach, Dominik K., Kraus, Sascha, Jones, Paul·2025·Journal of Small Business Management
DOI 10.1080/00472778.2024.2379999
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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.

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Research works printed but not linked: 10

  1. Babucea, A. G., & Rabontu, C. I. (2022). Big data analytics in the context of business enterprises “constantin Brâncuşi” din târgu-jiu seria economie. In C.-E. Stegaroiu & C. Enea (Eds.), Economy series. Analele Universităţii. Annals of “constantin brancusi” (Vol. 1, pp. 67–74). University of Targu-Jiu.
  2. bin Ahmad, A. M., Masri, R. B., & Lee, C. A. (2019). Future challenges to the entrepreneur in relation to the changing business environment. Global Business & Management Research, 11(2), 197–205.
  3. Dedhia, S. (2021). Impact of big data & analytics (BD&A) learning intentions with moderating effect of transformational leadership as SME perspective. Turkish Online Journal of Qualitative Inquiry, 12(7), 14015–14022.
  4. 10.1108/IJSE-12-2021-0752 · DOI
  5. 10.29302/oeconomica.2020.22.2.15 · DOI
  6. Koppel, T., & Tšernikova, O. (2023). Factors affecting the SME ability to enter the AI revolution. EUAS Conference Proceedings, Tallinn, Estonia. (p. 12).
  7. Lee, S. W., & Lee, H. S. (2014). A study of an integrated model for the introduction of a big data system: TOE. The Journal of the Korea Society of Information Technology Applications, 21(4), 463–483.
  8. Mittal, N., Saif, I., & Ammanath, B. (2022). Fueling the AI transformation: Four key actions powering widespread value from AI, right now. In Deloitte’s state of AI in the enterprise (5th [Report]. Retrieved August 20, 2023, from. https://www2.deloitte.com/content/dam/Deloitte/us/Documents/deloitte-analytics/us-ai-institute-state-of-ai-fifth-edition.pdf
  9. Whitson G. M. (2024). Artificial intelligence. Salem Press Encyclopedia of Science.
  10. Worek, M., & Aaltonen, P. (2023). AI adoption challenges in manufacturing family firms: Case study. Proceedings of the ISPIM Conferences (pp. 1–10), Ljubljana, Slovenia.

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Metadata

Authors
Schwaeke, J., Peters, A., Kanbach, D. K., Kraus, S., & Jones, P.
Affiliations
  • HHL Leipzig Graduate School of Management (DE)
  • Free University of Bozen-Bolzano (IT)
  • Swansea University (GB)
Corresponding author
Jones, Paul
ORCID
Venue
Journal of Small Business Management
Publisher
Informa UK Limited
Published
2024-08-13
Volume
63
Issue
3
Pages
1297-1331
ISSN
  • 0047-2778 (ISSN-L)
  • 1540-627X
DOI
10.1080/00472778.2024.2379999
OpenAlex
W4401536151
Cited by
241
References
144
Citations by year
2026: 144 · 2025: 93 · 2024: 4
FWCI
73.31
Type
journal article
Language
en
Open access
Licence
Locations
  • Journal of Small Business Management (publishedVersion, cc-by)
  • RePEc: Research Papers in Economics (acceptedVersion)
Topics
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
  • Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
  • Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
Keywords
artificial intelligence adoption, small and medium-sized enterprises, technology-organization-environment framework, AI implementation, compatibility, infrastructure, knowledge, resources, organizational culture, competition, regulation, AI ecosystem, legal requirements

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