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The new normal: The status quo of AI adoption in SMEs
Journal of Small Business Management, Pages: 1 - 35
Swansea University Author:
Paul Jones
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© 2024 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution License.
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DOI (Published version): 10.1080/00472778.2024.2379999
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 syst...
Published in: | Journal of Small Business Management |
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ISSN: | 0047-2778 1540-627X |
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Informa UK Limited
2024
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URI: | https://cronfa.swan.ac.uk/Record/cronfa67182 |
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v2 67182 2024-07-25 The new normal: The status quo of AI adoption in SMEs 21e2660aaa102fe36fc981880dd9e082 0000-0003-0417-9143 Paul Jones Paul Jones true false 2024-07-25 CBAE 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 Article Journal of Small Business Management 0 1 35 Informa UK Limited 0047-2778 1540-627X AI; artificial intelligence; small business; SME; technology 13 8 2024 2024-08-13 10.1080/00472778.2024.2379999 COLLEGE NANME Management School COLLEGE CODE CBAE Swansea University SU Library paid the OA fee (TA Institutional Deal) Swansea University 2024-08-29T16:11:14.8804772 2024-07-25T11:44:45.7651283 Faculty of Humanities and Social Sciences School of Management - Business Management Julia Schwaeke 1 Anna Peters 2 Dominik K. Kanbach 3 Sascha Kraus 4 Paul Jones 0000-0003-0417-9143 5 67182__31176__099d70e49a27413099a8030f5d7f41b8.pdf 67182.VoR.pdf 2024-08-29T16:08:14.8171742 Output 1968790 application/pdf Accepted Manuscript true © 2024 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution License. true eng http://creativecommons.org/ licenses/by/4.0/ |
title |
The new normal: The status quo of AI adoption in SMEs |
spellingShingle |
The new normal: The status quo of AI adoption in SMEs Paul Jones |
title_short |
The new normal: The status quo of AI adoption in SMEs |
title_full |
The new normal: The status quo of AI adoption in SMEs |
title_fullStr |
The new normal: The status quo of AI adoption in SMEs |
title_full_unstemmed |
The new normal: The status quo of AI adoption in SMEs |
title_sort |
The new normal: The status quo of AI adoption in SMEs |
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21e2660aaa102fe36fc981880dd9e082 |
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21e2660aaa102fe36fc981880dd9e082_***_Paul Jones |
author |
Paul Jones |
author2 |
Julia Schwaeke Anna Peters Dominik K. Kanbach Sascha Kraus Paul Jones |
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Journal article |
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Journal of Small Business Management |
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2024 |
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Swansea University |
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0047-2778 1540-627X |
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10.1080/00472778.2024.2379999 |
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Informa UK Limited |
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Faculty of Humanities and Social Sciences |
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School of Management - Business Management{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}School of Management - Business Management |
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description |
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. |
published_date |
2024-08-13T16:11:12Z |
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11.0241995 |