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Revisiting the SECI Model: The Impact of Generative AI on Organizational Knowledge Creation

In: Managing Human and Artificial Knowledge

Author

Listed:
  • Kathrin Kirchner

    (Technical University of Denmark, DTU Engineering Technology)

  • Enrico Scarso

    (University of Padova, DTG - Department of Management and Engineering)

Abstract

This chapter intends to open a debate about how generative AI (GenAI) influences organizational knowledge creation and if this involves revisiting existing theoretical models, specifically the SECI model of the organizational knowledge creation process. To this aim, based on the extant literature, two different perspectives on the role of GenAI within the organizational knowledge creation process are analyzed. The first one considers GenAI as a new and powerful tool that supports SECI conversion processes. The second, instead, regards GenAI as a new actor in the process, and hence requires a rethinking of the SECI model. Therefore, the chapter proposes a new model, based on the idea of the SECI model, that considers GenAI as a new player and the artificial knowledge created by it as a new type of knowledge. The new model is called AKI, where AKI is artificial knowledge integration into the organizational knowledge creation process. The chapter compares the SECI model with the new one by discussing their advantages and limitations when used to analyze the impact of GenAI on organizational knowledge creation. The conclusions call for the need to deepen the debate and support it with empirical evidence.

Suggested Citation

  • Kathrin Kirchner & Enrico Scarso, 2026. "Revisiting the SECI Model: The Impact of Generative AI on Organizational Knowledge Creation," Knowledge Management and Organizational Learning, in: Ettore Bolisani & Maayan Nakash & Constantin Bratianu & Ruxandra Bejinaru (ed.), Managing Human and Artificial Knowledge, pages 105-125, Springer.
    • Handle: RePEc:spr:kmochp:978-3-032-14721-9_6
    DOI: 10.1007/978-3-032-14721-9_6
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