Advances in artificial intelligence (AI) have transformed various aspects of human resource management (HRM), especially in decision making, operational efficiency, and data analysis. The application of AI in HRM offers opportunities to increase organizational effectiveness, but also raises challenges related to transparency, algorithmic bias, and ethics in workforce management. Therefore, this research was conducted to explore the impact of AI in HRM and how organizations can optimize its use. This research uses a literature review method, by examining various scientific sources related to the implementation of AI in HRM. The study was conducted on articles from academic journals, industry reports, and related publications that discuss the role of AI in the recruitment process, performance evaluation, employee training, and strategic decision making. The research results show that AI can improve HRM efficiency through automation of administrative tasks, predictive analytics, and personalization of the employee experience. However, the main challenges found include algorithmic bias, lack of transparency in AI systems, and legal and regulatory uncertainty. In conclusion, AI has great potential in supporting more effective and data-driven HRM, but its use must be accompanied by policies that ensure transparency, accountability and a balance between automation and the role of humans in decision making. Therefore, a careful approach is needed in adopting AI to ensure maximum benefits without compromising aspects of ethics and fairness.
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