What Role Do Artificial Intelligence and Machine Learning Play in Enhancing Human Resource Decision-Making Processes by Method from 2015 to 2025 Using Bibliometric Method

Abstract-This research examines the impact of artificial intelligence (AI) and machine learning (ML) on improving human resource (HR) decision-making procedures, with an emphasis on the years from 2015 to 2025. Employing a bibliometric approach, the study uncovers trends, obstacles, and prospects related to artificial intelligence and machine learning usage in human resource management. The results depicted in Figure 1 (“Document by Year”) indicate a marked rise in research activity after 2020, emphasizing an increasing interest in the incorporation of AI and ML in HR practices. Figure 2 (“Document by Area”) illustrates that computer science (45%) and business studies (30%) lead in research contributions, highlighting the technical and strategic aspects of these technologies. The geographic analysis shown in Figure 5 (“Document by Country”) reveals that 40% of the studies come from the United States, while European and Asian nations account for 30% and 20%, respectively. Institutional contributions, shown in Figure 7 (“Document by Affiliation”), indicate that 60% of research originates from academic institutions, while corporate research centers account for 25%. Figures 3 and 4 underscore the variety of sources and funding, showing a balance between academic integrity and practical uses, with government funding representing 50%. The research highlights the revolutionary impact of Artificial intelligence and Machine learning in human resource management, especially concerning talent acquisition, employee engagement, and workforce management. Nevertheless, ethical issues, biases in algorithms, and privacy threats present significant challenges. By combining technological advancements with ethical guidance, as illustrated by the trends shown in the figures, organizations can develop adaptable, inclusive, and effective HR systems that meet the changing needs of the workforce.