Mapping Review on AI, Employee Experience, and Work Performance: A Bibliometric Analysis

This bibliometric review examines the evolving relationship between artificial intelligence (AI), employee experience (EX), and work performance (WP) in organisational contexts from 2000 to 2025. As AI continues to transform human resource management practices, increasing scholarly attention has been directed toward understanding its impact on employee-centric outcomes and organisational effectiveness. The study analyses 373 peer-reviewed articles indexed in the Web of Science database, selected through the PRISMA screening process. Bibliometric and science mapping techniques were employed using Biblioshiny and VOSviewer to evaluate publication trends, leading authors and institutions, geographic contributions, keyword co-occurrence, and collaboration networks. The findings reveal a significant surge in research output after 2020, indicating heightened academic and practical interest in AI-driven HRM. Key themes identified include AI-enabled decision-making, employee engagement, performance enhancement, and organisational productivity. More recent studies increasingly focus on ethical considerations, transparency, employee well-being, and inclusivity in AI applications. This study offers a novel contribution by integrating AI, employee experience, and work performance into a single analytical framework, an area that has received limited systematic exploration. By mapping thematic evolution over 25 years, it highlights a clear shift toward human-centred and sustainability-oriented perspectives in AI research. Additionally, the study uncovers collaboration patterns and conceptual developments, providing valuable insights for future research directions in the field.