Ok CESARE, can you do this for me? Insights on how artificial intelligence fosters knowledge management

Purpose The purpose of this study is to explore how generative artificial intelligence (AI) can be integrated into knowledge management (KM) processes within manufacturing companies to enhance efficiency, knowledge accessibility and decision-making. In doing so, this study also examines the organizational enablers and challenges that shape AI implementation. Design/methodology/approach A single case study was used, conducting semi-structured interviews with key stakeholders, supplemented with document analysis and action research. Data were analysed using the Gioia approach. The case regards CESARE, an AI system developed by FPZ (an Italian manufacturing company) in collaboration with Gellify, a consulting company focused on digital transformation and AI. Findings The analysis identifies a nine-phase process model that illustrates how generative AI can be progressively embedded into KM practices, from initial exploration and small-scale testing to system integration, organizational alignment and continuous improvement. CESARE was found to reduce redundant tasks, improve knowledge flows and support informed decision-making, while its adoption was enabled by proactive data governance, user training, cross-functional collaboration and continuous monitoring. Key challenges included data privacy concerns, technical complexity and organizational resistance to change. Originality/value This research contributes to the limited empirical literature on the implementation of generative AI in KM within a specific organizational context. By providing detailed insights from a real-world case study, this paper can guide managers in adopting AI to support internal processes.