Skip to main navigation Skip to search Skip to main content

Advancing AI adoption in Germany's manufacturing SMEs: a TOE framework analysis

  • Lukas Weiss*
  • , Michael Möhring
  • , Keshav Dahal
  • *Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    77 Downloads (Pure)

    Abstract

    Small and medium-sized enterprises (SMEs) form the backbone of Europe’s largest economy, yet they face significant challenges in adopting artificial intelligence (AI). This study investigates factors influencing AI adoption in German manufacturing SMEs through the lens of the technology-organization-environment (TOE) framework. We identify key factors of German SMEs within the manufacturing sector across the TOE dimensions by combining a systematic literature review (n = 29) and qualitative interviews (n = 15 experts). The results show that SMEs favor cost-effective AI solutions with a clear ROI, are confronted with general data protection regulation (GDPR)-related data restrictions, and benefit significantly from public subsidies—compared to larger companies. Extending the TOE framework by integrating SME-specific contextual factors (e.g., research network and public subsidies), offering actionable insights for German SMEs to bridge the AI adoption gap. Results underscore the need for user-friendly AI tools and collaborative industry-academia initiatives to enhance SME competitiveness in manufacturing.
    Original languageEnglish
    Title of host publicationProceedings of Pacific Asia Conference on Information Systems (PACIS 2025)
    Subtitle of host publication26, Kuala Lumpur, Malaysia
    Place of PublicationAtlanta, Georgia, USA
    PublisherAssociation for Information Systems
    Number of pages17
    Publication statusPublished - 5 Jul 2025

    Keywords

    • AI adoption
    • SMEs
    • TOE framework
    • manufacturing sector

    Fingerprint

    Dive into the research topics of 'Advancing AI adoption in Germany's manufacturing SMEs: a TOE framework analysis'. Together they form a unique fingerprint.

    Cite this