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A Multiple Case Study of AI Potential in Small and Medium Sized Companies (SME)
University of Borås, Faculty of Textiles, Engineering and Business. Högskolan i Borås. (Industrial Engineering and Management)ORCID iD: 0000-0002-6689-3660
University of Borås, Faculty of Textiles, Engineering and Business.
University of Borås, Faculty of Textiles, Engineering and Business.
University of Borås, Faculty of Textiles, Engineering and Business.ORCID iD: 0000-0002-0905-6188
2025 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Small and medium-sized enterprises (SMEs) are central to economic development and innovation but often encounter significant obstacles in adopting advanced technologies such as artificial intelligence (AI). This study examines the potential of AI to address these challenges and enhance the competitiveness of SMEs. In a multiple case study, the research integrates a review of the relevant literature, in-depth case analyses, and semi-structured interviews to identify key barriers to AI adoption, including deficiencies in technical skills, organizational inertia, limitations in data infrastructure, and constrained resources. The study critically evaluates the transformative role of AI in improving decision-making processes, operational efficiency, and strategic adaptability in SMEs. Strategies for mitigating adoption barriers are proposed, emphasizing the importance of targeted training programs, fostering an innovation-oriented organizational culture, prioritizing robust data governance, and utilizing accessible AI tools. While the study acknowledges limitations such as the small sample size and the potential for interpretative bias, its findings contribute to the academic discourse on technology adoption in SMEs. The research provides a framework for understanding AI's role in SME contexts and offers directions for future empirical investigations into the intersection of AI and small business sustainability.

Place, publisher, year, edition, pages
2025.
Keywords [en]
AI, SME, Innovation
National Category
Business Administration
Identifiers
URN: urn:nbn:se:hb:diva-34084OAI: oai:DiVA.org:hb-34084DiVA, id: diva2:1989579
Conference
The 6th International Conference on Industrial Engineering and Industrial Management, Munich, Germany
Funder
ÅForsk (Ångpanneföreningen's Foundation for Research and Development)Available from: 2025-08-18 Created: 2025-08-18 Last updated: 2026-01-19Bibliographically approved

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Waidringer, JonasGiri, ChandadeviBeiker, SvenWittsten, Jens

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CiteExportLink to record
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Citation style
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  • apa
  • ieee
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Language
  • de-DE
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Output format
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