KMS and AI: Current Research and Future Direction

The application of artificial intelligence (AI) in knowledge management systems (KMS) is revolutionizing the way organizations manage knowledge across many industries, especially when generative AI merges with current KMS. While many studies have explored AI technique application in KMS, this study aims to comprehensively investigate AI and KMS literature to identify the themes of AI in KMS research and offer significant insight into future directions. This study created a corpus combining the titles and abstracts of bibliographical records (N = 327 studies) obtained from the Web of Science and Scopus databases. An unsupervised machine learning – probabilistic topic modeling technique based on latent Dirichlet allocation (LDA) – was used to analyze the corpus. Five key topics on the emerging application and prospect of AI in KMS research, including (1) KMS strategic embedding in industrial sectors, (2) intelligent decision support and problem solving, (3) intelligent architecture for data analysis and knowledge discovery, (4) evolution of AI technologies for intelligent KMS, and (5) KMS in future organizational processes and AI integration, were identified. Such findings reveal that intelligent KMS embedding generative AI is now approaching so that organizations can enhance organizational efficiency and strategic knowledge utilization. To the best of the authors’ knowledge, this chapter is the first bibliometric analysis that examines the current studies on AI and KMS, which deepens our understanding of AI in KMS and provides new research directions of KMS in the era of AI. © 2026 selection and editorial matter, Gang Liu, Jin Chen, and Eric Tsui.