A review of human resource management in the age of artificial intelligence and automation

The combination of artificial intelligence (AI) and automation in human resource management (HRM) is transforming HR activities, boosting decision-making, and increasing efficiency across the employee lifetime. AI-driven applications in HRM span talent acquisition, training, employee satisfaction, retention, and termination, using descriptive, predictive, and prescriptive algorithms to automate processes, such as resume screening, candidate matching, and personalized training programs. However, the revolution is limited by ethical problems, algorithmic prejudice, and the possible displacement of human positions, all of which raise questions about fairness and transparency. This review adopts the PRISMA methodology to systematically analyze the literature on the role of AI in HRM, evaluating a range of studies on the efficiency and challenges of AI applications in the HR process. Data processing involves extracting empirical studies, focusing on AI methods and applications tested in HRM contexts. The results show that AI methods consistently perform well in talent acquisition, retention, and satisfaction prediction. These AI methods have been recognized for their reliability and versatility in addressing critical HRM functions. In conclusion, while AI in HRM has immense potential for efficiency and precision, businesses must address ethical considerations and ensure the integration of human-centered techniques to maximize advantages while limiting hazards.