The accelerating advancement of artificial intelligence (AI) is significantly transforming organizational functions, with human resource management (HRM) being no exception. In particular, the strategic application of AI in employee engagement and training has emerged as a critical area of interest for both scholars and practitioners. As organizations strive to enhance workforce productivity, satisfaction, and adaptability, AI-powered tools such as chatbots, predictive analytics, learning management systems, and personalized training platforms are increasingly employed to support data-driven decision-making and foster continuous employee development. Despite the growing adoption of AI in HRM, there remains a lack of consolidated understanding of how this technological shift is being reflected in academic literature—especially in relation to employee engagement and training. To address this gap, this study presents a comprehensive bibliometric analysis aimed at mapping the intellectual landscape of research at the intersection of AI, HRM, employee engagement, and training. Using data extracted from the Scopus database covering publications from 2004-2025, this study analyzes publication trends, key authors, institutions, influential journals, and emerging thematic clusters. Visualization tools such as VOSviewer are employed to identify collaborative networks and topic evolution over time. The top research areas associated with these areas include Computer Science, Social Sciences, Medicine and Business Management contributed the most related publications. By offering an evidence-based overview of the literature, this study contributes to a deeper understanding of how AI is shaping the future of HRM and provides guidance for future research, policy formulation, and practical implementation in organizations seeking to enhance employee engagement and learning outcomes through innovative technologies.