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Understanding the Challenges of AI Implementation: Insights from an Empirical Study of Manufacturing Companies

In: Artificial Intelligence, Data, and Decision-Making

Author

Listed:
  • Leon Oldemeyer

    (Osnabrück University of Applied Sciences)

  • Andreas Jede

    (Osnabrück University of Applied Sciences)

  • Frank Teuteberg

    (University of Osnabrück)

Abstract

The increasing importance of artificial intelligence on manufacturing competitiveness is a prevalent topic in contemporary studies. Thereby, the potential of AI extends across companies of all sizes. However, small and medium-sized enterprises in particular see major challenges in AI implementation. As a result, our study determined the variations in the perceived barriers to AI realization among different company sizes and the obstacles that notably impede the willingness to implement AI. To achieve this, a factor analysis and structural equation modeling were carried out. Our findings highlight that the different challenges for AI implementation can be divided into four groups economic, technological, social, and political. Thereby the perception of economic challenges varies the most among distinct enterprise sizes, whereas the social challenges correlate extremely weakly. Regarding the willingness to implement AI, political challenges show the strongest negative correlation, while technological challenges, contrary to prior assumptions, lack significant influence.

Suggested Citation

  • Leon Oldemeyer & Andreas Jede & Frank Teuteberg, 2026. "Understanding the Challenges of AI Implementation: Insights from an Empirical Study of Manufacturing Companies," Lecture Notes in Information Systems and Organization, in: Christoph M. Flath & Gunther Gust & Frédéric Thiesse & Axel Winkelmann (ed.), Artificial Intelligence, Data, and Decision-Making, pages 153-168, Springer.
    • Handle: RePEc:spr:lnichp:978-3-032-08480-4_11
    DOI: 10.1007/978-3-032-08480-4_11
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