AI in KM: A Framework and Practitioner Insights

This paper presents a framework for integrating artificial intelligence (AI) into knowledge management (KM) using the Jennex–Olfman KM Success Model as a foundation. Through a literature review and a thematic analysis of 400 practitioner comments from the global SIKM Leaders community, the study examines how AI is being applied in KM and the implications for practice. Findings highlight that AI expands KM across diverse sectors, enhances efficiency through automation and workflow integration, and supports human judgment in knowledge tasks. At the same time, risks concerning bias, accuracy, transparency, governance, and infrastructure remain central challenges. Mapping these insights to the KM Success Model shows that AI strengthens system and knowledge quality while requiring leadership and governance to safeguard service quality. The analysis extends the model by emphasizing explainability, transparency, and human oversight as critical for AI-enabled KM. Overall, the study concludes that AI offers significant potential to advance KM success, but its value depends on careful alignment with organizational strategy, investment in infrastructure, and sustained commitment to ethical and responsible implementation.