Reconceptualising AI-Enabled Knowledge Management: Implications for Organisational Learning and Strategic Decision-Making
The increasing integration of artificial intelligence (AI) into organisational environments is transforming knowledge management (KM) practices, yet scholarly understanding of how these developments support organisational learning and strategic decision-making remains fragmented. While existing research highlights the role of AI in enhancing knowledge retrieval, analytics, and decision-support capabilities, it often adopts a techno-centric perspective that underplays the influence of human, organisational, and contextual factors. This fragmentation limits the development of a coherent understanding of AI-enabled knowledge management as a unified construct. This study addresses this gap by conducting a systematic literature review (SLR) guided by PRISMA 2020 guidelines to synthesise and critically evaluate research on AI-enabled knowledge management. Peer-reviewed journal articles and conference papers published between 2010 and 2025 were retrieved from Scopus, Web of Science, EBSCOhost, and ProQuest. Following a rigorous screening and selection process, the final corpus was analysed using descriptive and thematic synthesis techniques to identify patterns, relationships, and conceptual gaps within the literature. The findings reveal five interrelated themes, namely, AI as an enabler of knowledge management processes; human-AI collaboration and the reconfiguration of knowledge work; AI-enabled organisational learning; AI-enabled knowledge management as a strategic capability; governance, ethics, and contextual contingencies. The results demonstrate that AI enhances knowledge creation, sharing, and decision-making when embedded within human-centred and learning-oriented organisational environments (Kitsios and Kamariotou, 2021; Jarrahi et al., 2023). Uncritical reliance on AI may ostensibly lead to automation bias, reduced critical engagement, and weakened knowledge quality (Storey, 2025). The study advances theory by reconceptualising AI-enabled knowledge management as a socio-technical capability mediated by human-AI interaction and shaped by governance and contextual conditions (Paschen et al., 2020; Rezaei, 2025). An integrative conceptual framework is proposed to capture these relationships and to provide a foundation for future empirical research. Practically, the findings highlight the need for organisations to balance technological innovation with human capability development and ethical governance to ensure effective and responsible AI adoption.