Abstract
Purpose: Generative AI and more specifically ChatGPT has brought a revolution in the lives of people by providing them with required knowledge that it has learnt from an exponentially large knowledge base. In this viewpoint, we are initiating the debate and offer the first step towards Generative AI based knowledge management systems in organizations. Design/methodology/approach: This study is a viewpoint and develops a conceptual foundation using existing literature on how ChatGPT can enhance the KM capability based on Nonaka’s SECI model. It further supports the concept by collecting data from a public sector univesity in Hong Kong to strenghten our argument of ChatGPT mediated knowledge management system. Findings: We posit that all four processes, that is Socialization, Externalization, Combination and Internalization can significantly improve when integrated with ChatGPT. ChatGPT users are, in general, satisfied with the use of ChatGPT being capable of facilitating knowledge generation and flow in organizations. Research limitations/implications: The study provides a conceptual foundation to further the knowledge on how ChatGPT can be integrated within organizations to enhance the knowledge management capability of organizations. Further, it develops an understanding on how managers and executives can use ChatGPT for effective knowledge management through improving the four processes of Nonaka’s SECI model. Originality/value: This is one of the earliest studies on the linkage of knowledge management with ChatGPT and lays a foundation for ChatGPT mediated knowledge management system in organizations.
Original language | English |
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Pages (from-to) | e-copy |
Number of pages | 21 |
Journal | Kybernetes |
Early online date | 21 Feb 2024 |
DOIs | |
Publication status | E-pub ahead of print - 21 Feb 2024 |
Keywords
- ChatGPT
- ChatGPT mediated knowledge management system
- Explicit knowledge
- Generative AI
- Knowledge management
- SECI model
- Tacit knowledge
ASJC Scopus subject areas
- Software
- Control and Systems Engineering
- Theoretical Computer Science
- Information Systems
- Artificial Intelligence
- Electrical and Electronic Engineering