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Artificial intelligence implementation in manufacturing SMEs: A resource orchestration approach
Jönköping University, School of Engineering, JTH, Department of Computing, Jönköping AI Lab (JAIL).ORCID iD: 0000-0002-9603-9289
Department of Management, Universidad EAFIT, Medellín, Colombia; Entrepreneurship and Innovation, Department of Social Sciences, Technology and Arts, Luleå University of Technology, Luleå, Sweden.
Department of Computer Science, Faculty of Information Technology and Electrical Engineering, NTNU, Trondheim, Norway; SINTEF Digital, Department of Technology Management, Trondheim, Norway.
Entrepreneurship and Innovation, Department of Social Sciences, Technology and Arts, Luleå University of Technology, Luleå, Sweden; Department of Management, University of Vaasa, Vaasa, Finland.
2024 (English)In: International Journal of Information Management, ISSN 0268-4012, E-ISSN 1873-4707, Vol. 77, article id 102781Article in journal (Refereed) Published
Abstract [en]

Artificial intelligence (AI) is playing a leading role in the digital transformation of enterprises, particularly in the manufacturing industry where it has been responsible for a profound transformation in key business and production operations. Despite the accelerated growth of AI technologies, knowledge of the implementation of AI by small and medium-sized enterprises (SMEs) remains underexplored. Thus, this study seeks to examine how manufacturing SMEs orchestrate resources for AI implementation. Building on the resource orchestration (RO) theory and recent work on AI implementation, we investigate multiple case studies involving manufacturing SMEs in Sweden operating in the packaging, plastic, and metal sectors. Our findings indicate that SMEs structure a portfolio based on acquiring and accumulating AI resources. AI resources are bundled into learning and governance capabilities to leverage configurations for AI implementation. Through a dynamic process of AI resource orchestration, SMEs effectively leverage AI resources and capabilities by mobilising technologies, coordinating manufacturing processes, and empowering skilled people. This research contributes to existing practice and the academic literature on AI implementation, highlighting how SMEs orchestrate AI resources and capabilities to drive an organisation’s digital transformation whilst creating a competitive advantage.

Place, publisher, year, edition, pages
Elsevier, 2024. Vol. 77, article id 102781
Keywords [en]
AI, Artificial intelligence, Resources, Capabilities, Manufacturing, Resource orchestration, Digital transformation, Small and medium-sized enterprises (SMEs), Competitive advantage
National Category
Computer Sciences Business Administration
Identifiers
URN: urn:nbn:se:hj:diva-63931DOI: 10.1016/j.ijinfomgt.2024.102781ISI: 001222220800001Scopus ID: 2-s2.0-85189496050Local ID: HOA;intsam;944528OAI: oai:DiVA.org:hj-63931DiVA, id: diva2:1848407
Available from: 2024-04-03 Created: 2024-04-03 Last updated: 2024-09-10Bibliographically approved

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Peretz-Andersson, Einav

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