Abstract
This research aims to propose an experience-based knowledge management (EBKMS) to facilitate knowledge activities in a community of practice (CoP). Based on the capabilities offered by conversational AI and a large language model (in general, called foundation models), the proposed EBKMS is equipped with natural language processing, understanding, and reasoning abilities to facilitate humans to communicate with their personal knowledge assistant (K-assistant) to interact with other members in their CoPs. We design the structure and operations of the EBKMS to elaborate on how they can fulfill the SECI process by integrating human and AI. The proposed framework will be developed and tested in a real-world CoP for practitioners mainly from small and medium-sized enterprises (SMEs) to update their practices and enable them to cooperate for problem-solving to enhance their resilience in facing unanticipated but urgent challenges for their sustainability. This research lays a foundation for developing conversational AI-enabled knowledge management systems to enhance human and AI collaboration.