Abstract—The development of Generative Artificial Intelligence (GAI) and Large Language Models (LLMs) has transformed the field of Knowledge Management (KM) by enabling precision in transferring knowledge as well as improving decision-making processes and operational efficiency. This paper systematically reviews 58 peer-reviewed publications from 2019 to early 2024 to comprehensively understand how these technologies impact knowledge management practices across numerous industries. The roles of GAI and LLMs were examined by using the Prisma methodology. VOSviewer and Power BI were used to visualize and analyze the data. Our research identified impacts and identified related gaps, including the need for advanced anonymities of techniques, AI-related technology development, and robust ethical mechanisms. In detail, trust emerges as a key factor that impacts and encompasses technological, organizational, and interpersonal dilemmas to empower knowledge management processes. This review emphasizes the crucial importance of strategic data management and cross-disciplinary approaches in addressing and responding to existing challenges. By bridging the gaps in ethics and trust-building in the practical adoption of these technologies, organizations can utilize GAI and LLMs to create an impactful and transparent KM system while maintaining sustainable and inclusive KM practices. Further, this paper provides a detailed investigation on the transformative potential of GAI and LLMs in KM and proposes strategies for future research to address existing gaps and optimize and broaden the fields of applications.
 
Keywords—Knowledge Management (KM), knowledge sharing, Generative Artificial Intelligence (GAI), Large Language Models (LLMs)


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