Wind of change: how ChatGPT and big data can reshape the knowledge management paradigm?

Abstract

Purpose

The new disruption in the form of ChatGPT can be a valuable tool for organizations to enhance their knowledge management and decision-making capabilities. This article explores how ChatGPT can enhance organizations' KM capability for improved decision-making and identifies potential risks and opportunities.

Design/methodology/approach

Using existing literature and a small-scale case study, we develop a conceptual framework for implementing artificial intelligence on the internal organizational knowledge base of big data and its integration with a larger knowledge base of ChatGPT.

Findings

This viewpoint conceptualizes integrating knowledge management and ChatGPT for improved organizational decision-making. By facilitating efficient information retrieval, personalized learning, collaborative knowledge sharing, real-time decision support, and continuous improvement, ChatGPT can help organizations stay competitive and achieve business success.

Research limitations/implications

This is one of the first studies on the integration of organizational knowledge management systems with ChatGPT. This research work proposes a conceptual model on integration of knowledge management with generative AI which can be further tested in actual work settings to check it's applicability and make further modifications.

Practical implications

The study provided insights to managers and executives who, in collaboration with IT professionals, can devise a mechanism for integrating existing knowledge management systems in organizations with ChatGPT.

Originality/value

This is one of the first studies exploring the linkage between ChatGPT and knowledge management for informed decision-making.

Citation

Sumbal, M.S., Amber, Q., Tariq, A., Raziq, M.M. and Tsui, E. (2024), "Wind of change: how ChatGPT and big data can reshape the knowledge management paradigm?", Industrial Management & Data Systems, Vol. 124 No. 9, pp. 2736-2757. https://doi.org/10.1108/IMDS-06-2023-0360