The widespread adoption of artificial intelligence technologies has led to comprehensive transformations within organizations. One of the most critical areas affected by this transformation is human resources. In this regard, the study examines the publication performance, research topics, and temporal evolution of the literature on artificial intelligence in human resources management. In the study, 1.999 peer-reviewed publications obtained from the Scopus database over the past ten years were analyzed using the structural topic modeling method, which is a topic modeling approach. As a finding of the analysis, 19 topics were identified. Furthermore, the findings reveal that research on artificial intelligence in human resources management has demonstrated an exponential growth trend during the period of 2016–2025. In terms of topic proportions, the most frequently studied themes were identified as “Digital Transformation in Human Resources Management,” “Ethical Recruitment,” and “Chatbot Applications,” while “Knowledge Management,” “GenAI in Assesment” and “Talent Acquisition” were represented at comparatively lower levels. The trend analysis further shows that “Ethical Recruitment,” “Green Human Resources Management,” “Adoption of Innovation,” “Digital Transformation in HRM” and “GenAI in Evaluation” have exhibited consistent growth, whereas “Internet of Things,” “Agile Team Management,” “Decision Support,” “Artificial Neural Networks,” “Project Management,” and “Robotics” have followed a declining trajectory. On the other hand, it was also identified that “Machine Learning,” as a fundamental technology, and “Chatbot Applications,” as one of the most frequently studied themes, did not display statistically significant trends. Overall, the findings indicate that research on artificial intelligence in human resources management has been shifting its focus from purely technical aspects toward dimensions such as ethics, sustainability, and social impacts; however, this transformation has so far taken place only at a limited level.