Rethinking Knowledge Management in the Era of LLMs: A Knowledge Management Model for Mitigating LLM Hallucination

Large Language Models have the potential to greatly enhance organizational knowledge management practice. However, along with this promise comes the risk of hallucination. LLM hallucination can proliferate rapidly, threatening the quality of knowledge available to employees. This paper proposes a conceptual model to guide the mitigation of hallucination-related knowledge risks in LLM-powered knowledge management systems. Building on the Knowledge Management Cycle Model, the updated framework integrates practical hallucination mitigation strategies, including Prompt Engineering, Retrieval-Augmented Generation, Automated Verification, and Human Feedback, into each stage of the cycle. While the model remains general and conceptual, it provides a foundational roadmap for organizations to adapt knowledge practices in the age of LLMs and offers clear directions for future empirical research and refinement.