No Cover Image

Journal article 56 views 1 download

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

Julia Schwaeke, Anna Peters, Dominik K. Kanbach, Sascha Kraus, Paul Jones Orcid Logo

Journal of Small Business Management, Pages: 1 - 35

Swansea University Author: Paul Jones Orcid Logo

  • 67182.VoR.pdf

    PDF | Accepted Manuscript

    © 2024 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution License.

    Download (1.88MB)

Check full text

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...

Full description

Published in: Journal of Small Business Management
ISSN: 0047-2778 1540-627X
Published: Informa UK Limited 2024
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa67182
Tags: Add Tag
No Tags, Be the first to tag this record!
first_indexed 2024-07-25T10:47:35Z
last_indexed 2024-07-25T10:47:35Z
id cronfa67182
recordtype SURis
fullrecord <?xml version="1.0" encoding="utf-8"?><rfc1807 xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"><bib-version>v2</bib-version><id>67182</id><entry>2024-07-25</entry><title>The new normal: The status quo of AI adoption in SMEs</title><swanseaauthors><author><sid>21e2660aaa102fe36fc981880dd9e082</sid><ORCID>0000-0003-0417-9143</ORCID><firstname>Paul</firstname><surname>Jones</surname><name>Paul Jones</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2024-07-25</date><deptcode>CBAE</deptcode><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.</abstract><type>Journal Article</type><journal>Journal of Small Business Management</journal><volume>0</volume><journalNumber/><paginationStart>1</paginationStart><paginationEnd>35</paginationEnd><publisher>Informa UK Limited</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint>0047-2778</issnPrint><issnElectronic>1540-627X</issnElectronic><keywords>AI; artificial intelligence; small business; SME; technology</keywords><publishedDay>13</publishedDay><publishedMonth>8</publishedMonth><publishedYear>2024</publishedYear><publishedDate>2024-08-13</publishedDate><doi>10.1080/00472778.2024.2379999</doi><url/><notes/><college>COLLEGE NANME</college><department>Management School</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>CBAE</DepartmentCode><institution>Swansea University</institution><apcterm>SU Library paid the OA fee (TA Institutional Deal)</apcterm><funders>Swansea University</funders><projectreference/><lastEdited>2024-08-29T16:11:14.8804772</lastEdited><Created>2024-07-25T11:44:45.7651283</Created><path><level id="1">Faculty of Humanities and Social Sciences</level><level id="2">School of Management - Business Management</level></path><authors><author><firstname>Julia</firstname><surname>Schwaeke</surname><order>1</order></author><author><firstname>Anna</firstname><surname>Peters</surname><order>2</order></author><author><firstname>Dominik K.</firstname><surname>Kanbach</surname><order>3</order></author><author><firstname>Sascha</firstname><surname>Kraus</surname><order>4</order></author><author><firstname>Paul</firstname><surname>Jones</surname><orcid>0000-0003-0417-9143</orcid><order>5</order></author></authors><documents><document><filename>67182__31176__099d70e49a27413099a8030f5d7f41b8.pdf</filename><originalFilename>67182.VoR.pdf</originalFilename><uploaded>2024-08-29T16:08:14.8171742</uploaded><type>Output</type><contentLength>1968790</contentLength><contentType>application/pdf</contentType><version>Accepted Manuscript</version><cronfaStatus>true</cronfaStatus><documentNotes>© 2024 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution License.</documentNotes><copyrightCorrect>true</copyrightCorrect><language>eng</language><licence>http://creativecommons.org/ licenses/by/4.0/</licence></document></documents><OutputDurs/></rfc1807>
spelling 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
author_id_str_mv 21e2660aaa102fe36fc981880dd9e082
author_id_fullname_str_mv 21e2660aaa102fe36fc981880dd9e082_***_Paul Jones
author Paul Jones
author2 Julia Schwaeke
Anna Peters
Dominik K. Kanbach
Sascha Kraus
Paul Jones
format Journal article
container_title Journal of Small Business Management
container_volume 0
container_start_page 1
publishDate 2024
institution Swansea University
issn 0047-2778
1540-627X
doi_str_mv 10.1080/00472778.2024.2379999
publisher Informa UK Limited
college_str Faculty of Humanities and Social Sciences
hierarchytype
hierarchy_top_id facultyofhumanitiesandsocialsciences
hierarchy_top_title Faculty of Humanities and Social Sciences
hierarchy_parent_id facultyofhumanitiesandsocialsciences
hierarchy_parent_title Faculty of Humanities and Social Sciences
department_str School of Management - Business Management{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}School of Management - Business Management
document_store_str 1
active_str 0
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
_version_ 1808735166023073792
score 11.0241995

Similar Items