Abstract
This chapter presents a bibliometric analysis of 255 publications indexed in the Scopus database between 2016 and 2025 to examine how artificial intelligence (AI) is influencing diversity and inclusion in human resource management (HRM). Using the search terms “Artificial Intelligence,” “Women,” and “Bias,” the study maps publication trends, document types, subject areas, authorship patterns, and country-wise contributions to assess the evolution of scholarship at the intersection of AI and gender equity. The findings reveal a steady growth in research, with healthcare emerging as the dominant domain, while a growing body of literature increasingly addresses HRM-related concerns such as recruitment, retention, promotions, pay equity, workload allocation, and performance evaluation. The analysis highlights the dual role of AI: while algorithmic systems may reproduce historical biases embedded in data, they also offer mechanisms to mitigate discrimination through anonymized recruitment, fairness-oriented evaluation metrics, and data-driven pay audits.