Knowledge Management Perspective of Generative Artificial Intelligence

Abstract

In this editorial, revisiting Alavi and Leidner (2001) as a conceptual lens, we consider the organizational implications of Generative Artificial Intelligence (GenAI) from a knowledge management (KM) perspective. We examine how GenAI impact the processes of knowledge creation, storage, transfer, and application, highlighting both the opportunities and challenges this technology presents. In knowledge creation, GenAI enhances information? processing and cognitive functions, fostering individual and organizational learning. However, it also introduces risks like AI bias and reduced human socialization, potentially marginalizing junior knowledge workers. For knowledge storage and retrieval, GenAI’s ability to quickly access vast knowledge bases significantly changes employee interactions with KM systems. This raises questions about balancing human-derived tacit knowledge with AI-generated explicit knowledge. The paper also explores GenAI’s role in knowledge transfer, particularly in training and cultivating a learning culture. Challenges include an over-reliance on AI and risks in disseminating sensitive information. In terms of knowledge application, GenAI is seen as a tool to boost productivity and innovation, but issues like knowledge misapplication, intellectual property, and ethical considerations are critical. Conclusively, the paper argues for a balanced approach to integrating GenAI into KM processes. It advocates for harmonizing GenAI’s capabilities with human insights to effectively manage knowledge in contemporary organizations, ensuring both technological advances and ethical responsibility.