Knowledge is one of the most valuable assets in modern organizations. However, its intangible and evolving nature makes it challenging to capture and leverage. Knowledge management (KM) is the organized, systematic process that acquires, refines, organizes, and applies this knowledge to improve organizational success and secure long-term competitive advantage. As data volume and complexity continue to grow, conventional systems have proven insufficient to harness the full potential of knowledge assets. As a result, emerging technologies have become indispensable, providing agile, scalable, and intelligent solutions. However, much of the existing research often examines these technologies in isolation, considering artificial intelligence (AI) and others as standalone entities, failing to reveal the synergies that emerge from combining them. This limitation is further complicated by the nature of common research approaches: literature reviews, while offering broad theoretical insights, are typically too abstract to inform practical application; meanwhile, case studies, though grounded in real-world scenarios, often lack generalizability due to their strong context-specific focus. This study addresses these gaps by investigating how AI and complementary, emerging technologies redefine KM areas. Drawing on 1,487 documented business practices—comprising case studies, pilot projects, and simulation models—derived from literature, this research focuses on five critical KM phases: knowledge creation, acquisition, organization, transfer, and application. Conceptually, knowledge is created or acquired, then captured, organized, and preserved for the long term, transferred to those who need it, and finally applied to produce value. Finally, these practices are analyzed through association analysis via Cramér’s V to quantify the strength of relationships between AI (whether used alone or alongside other technologies), business functions and the different KM areas. Theoretically, the findings advance KM research by demonstrating which technological combinations are more effective in each KM phase. From a managerial perspective, the emerging practices examined in this study offer real-world examples of how these integrated solutions can be successfully deployed, allowing managers to draw from documented practices rather than starting from scratch.