The Role of Explainable Artificial Intelligence (XAI) in Supporting Knowledge Management (KM) and Its Processes: An Analytical Study

Abstract

Problem: This study addresses the research gap related to exploring the role of Explainable Artificial Intelligence (XAI) in supporting knowledge management processes and investigating how this technology can be employed to enhance decision-making in contemporary environments. Significance: The importance of this study lies in its potential to highlight the role of this emerging technology in supporting knowledge management and its core processes, particularly in the domains of knowledge discovery, representation, and extraction. Hypotheses: The study assumes that Explainable Artificial Intelligence (XAI) plays a positive role in supporting knowledge management and its associated processes. Objectives: This study aimed to clarify the concept of Explainable Artificial Intelligence (XAI) and explore the relationship between XAI technologies and knowledge management (KM) and its processes, through an analytical review of the relevant scientific literature. Methods: The study adopted an inductive analytical approach by examining English-language studies published between 2020 and 2025, to identifying theoretical and practical frameworks that illustrate how XAI can support KM processes, including knowledge discovery, representation, and extraction. Results: The study concluded that (XAI) technologies have a significant positive impact on enhancing the effectiveness of knowledge management by producing interpretable outputs that support better decision-making and improve decision quality for decision-makers. The findings also indicate that (XAI) fosters transparency and trust in AI systems, thereby increasing the reliability of AI adoption in the context of knowledge management.