Bibliometric Mapping Of The Literature On Ai In Workforce Recruitment: Visualization Of Trends And Scientific Collaborations

This study aims to explore the research landscape of artificial intelligence (AI) in recruitment and selection within human resource management by mapping publication trends, intellectual structures, and emerging themes. Using a bibliometric analysis of 404 Scopus-indexed documents and tools such as Bibliometrix and VOSviewer, the study examines scholarly output, collaboration networks, and thematic clusters from global research. Results show a rapid increase in publications since 2018, with a peak in 2024, driven by key technologies including machine learning, natural language processing, and predictive analytics. Emerging areas such as generative AI (e.g., ChatGPT), blockchain, and virtual reality are gaining traction, while ethical concerns around fairness, transparency, and algorithmic bias are becoming increasingly prominent. The research highlights South Asia, particularly India, as a leading contributor, though the field remains globally diverse. These findings provide a comprehensive overview of the evolving AI in recruitment domain, offering theoretical insights and practical guidance for HR professionals and policymakers. The study underscores the need for multidisciplinary, ethically informed approaches to ensure AI-driven recruitment is both efficient and equitable.