Proceedings of the 5th International Conference on Research in Human Resource Management
Year: 2024
DOI:
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Impact of AI on Knowledge Management a Systematic Literature Review
Hamza Hayouni, ELANGUOUD Wassil, ALAOUI SOSSI Fatima Zohra
ABSTRACT:
The integration of Artificial Intelligence (AI) into Knowledge Management (KM) systems is reshaping how organizations manage intellectual capital, enhance decision-making, and foster innovation. This paper presents the results of a systematic literature review (SLR), based on 745 peer-reviewed articles retrieved from ScienceDirect between 2000 and 2024, to investigate the evolving relationship between AI and KM. The review followed a structured methodology, including a predefined search strategy, selection criteria, and data analysis procedures, to ensure a comprehensive and unbiased assessment of current trends. Articles were selected based on their relevance to key AI technologies and their applications in KM processes, including knowledge creation, retrieval, and dissemination. Our analysis revealed that AI significantly enhances KM by automating knowledge processes, improving the conversion of tacit knowledge into explicit knowledge, and fostering collaborative learning and innovation (Williams & Li, 2023). AI-powered KM systems also enable the processing of large volumes of unstructured data, providing real-time, actionable insights that enhance decision-making and organizational agility (Jones et al., 2021). Additionally, the Spiral of Knowledge model by Nonaka and Takeuchi (1995) remains highly relevant in AI-driven KM systems, as AI facilitates knowledge sharing and externalization. However, the review also highlights several challenges and limitations. The ethical implications of AI in KM, particularly issues of data privacy, algorithmic bias, and the need for explainability, are ongoing concerns (Zhang et al., 2023). Furthermore, while AI can augment decision-making, there are limitations in how it captures the nuances of human tacit knowledge and cultural context. The research is also limited by the focus on articles from ScienceDirect, which may exclude valuable insights from other databases, and by the evolving nature of AI technologies, which means that findings could quickly become outdated. In the discussion, we explore the practical implications of AI-enhanced KM systems, including their potential for improving organizational sustainability, innovation, and global collaboration (Chen & Kumar, 2024). We also address future research directions, such as the development of more transparent and ethical AI frameworks and the need for further empirical studies that examine AI’s role in KM across diverse cultural and industry contexts. By offering a comprehensive synthesis of recent literature, this study provides valuable insights into the opportunities and challenges of integrating AI into KM. The paper contributes to the understanding of AI’s transformative potential in organizational learning and innovation while acknowledging the limitations and ethical considerations that must be addressed for sustainable AI-KM integration.
keywords: Artificial Intelligence, Knowledge Management, Systematic Literature Review, AI, Spiral of Knowledge