Artificial intelligence in human resource management: Publication growth, citation inequality, and international collaboration

Type of the article: Research ArticleAbstractThis study aims to examine publication dynamics, citation inequality, author and country participation, international scientific collaboration, cited-reference relationships, and author-keyword structures in Scopus-indexed research on artificial intelligence in human resource management (HRM) published between 2000 and 2025. Following EID-level screening of 1,596 records, 659 publications were identified as thematically relevant to the topic of AI-HRM. The selected corpus accumulated 25,072 citations, averaging 38.05 citations per publication. Citation impact was highly concentrated, with a Gini coefficient of 0.7396 and 60.16% of citations attributable to the most-cited 10% of publications. Annual output increased from 16 publications in 2019 to 267 in 2025, corresponding to a compound annual growth rate of 59.86%. In addition, descriptive growth-model comparisons showed that the exponential model provided the strongest fit to the annual publication series (R² = 0.9945). International co-authorship was identified in 211 publications (32.02%). Country collaboration, cited-reference co-citation, and author-keyword networks were examined to characterize the intellectual and conceptual structure of the field. The study provides a traceable and reproducible bibliometric assessment of the documented indicators of publication growth, citation inequality, international collaboration, and thematic relationships within the selected AI-HRM corpus.AcknowledgmentsThe research was supported through grant funding of the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (grant IRN AP23490443), “Human capital management, improving the quality of labor resources in the context of the development of the digital economy.”