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AI and the Changing Landscape of Knowledge: Rethinking KM Core Concepts and Models

Author

Listed:
  • Maayan Nakash

    (Bar-Ilan University, Department of Management)

  • Ettore Bolisani

    (University of Padova, Department of Management and Engineering)

Abstract

The rapid advancement of artificial intelligence (AI) is catalyzing a profound transformation in how individuals, organizations, and societies create, disseminate, and apply knowledge. We argue that the accelerated evolution of AI applications necessitates a critical reexamination of core concepts, definitions, and methodologies traditionally considered foundational to the field of knowledge management (KM). Established models such as the data, information, knowledge, wisdom (DIKW) hierarchy, the socialization, externalization, combination, internalization (SECI) model, and the people, process, and technology (PPT) framework have long guided KM research and practice. However, the integration of AI technologies challenges these foundational constructs, calling for their reassessment and adaptation. This chapter aims to bridge the divide between AI’s rapidly advancing capabilities and KM’s enduring conceptual principles. By examining the intersections of AI and KM, it investigates how generative AI tools, particularly large language models (LLMs), are reshaping fundamental KM elements, including key processes like knowledge acquisition, documentation, sharing, and application.

Suggested Citation

  • Maayan Nakash & Ettore Bolisani, 2026. "AI and the Changing Landscape of Knowledge: Rethinking KM Core Concepts and Models," Knowledge Management and Organizational Learning,, Springer.
    • Handle: RePEc:spr:kmochp:978-3-032-14721-9_3
    DOI: 10.1007/978-3-032-14721-9_3
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