<p>The integration of Artificial Intelligence (AI) in knowledge sharing has become a critical area of research, witnessing remarkable growth over the last three decades. This study provides a comprehensive bibliometric overview of the intellectual structure and evolution of this field, aiming to identify key contributors, dominant themes, and future research directions. The analysis is based on a dataset of 1,544 publications retrieved from the Web of Science database on June, 2024. The study employs bibliometric methods, utilizing VOSviewer, Excel for co-citation, co-occurrence, and trend analysis. The main findings reveal an exponential growth in publications, particularly after 2018, with research concentrated in Computer Science and Engineering and geographically dominated by China and the United States. Thematic analysis reveals a significant transition from basic knowledge management systems to a modern emphasis on machine learning, transfer learning, and interconnected ecosystems that incorporate blockchain and the Internet of Things (IoT). Key future research directions are identified, including the need to address ethics and fairness, develop sustainable “green AI,” advance machine learning architectures, and explore the convergence of AI and blockchain. With a focus on knowledge sharing, the study reveals the dual character of AI and emphasizes the urgent need for organizations to implement comprehensive “responsible AI” strategies that include ethical audits, sustainability metrics, and well-planned pilot programs.</p>