This study aims to analyze the impact of Artificial Intelligence (AI) implementation in human resource management (HRM) on both individual performance and organizational productivity. Using the Systematic Literature Review (SLR) method, the research examined 15 selected scholarly articles published between 2010 and 2025 that are relevant to the application of AI in HRM. The literature selection process followed several stages, including identification, screening, eligibility assessment, and inclusion, by utilizing academic databases such as Google Scholar, Scopus, and ResearchGate. The synthesis results reveal that AI adoption in HR functions—such as recruitment, training, performance evaluation, and employee retention—enhances efficiency, accuracy, and decision-making speed. The positive impacts of AI are evident in improving recruitment quality, optimizing talent development, predicting employee performance, and strengthening overall organizational productivity, particularly in the service sector. This study concludes that AI holds significant potential to transform HRM into a more strategic, adaptive, and data-driven system. To maximize its benefits, organizations must establish ethical governance frameworks, foster digital competency development, and ensure strong regulatory support. Future research is recommended to expand empirical investigations across various industries to strengthen the generalizability of the findings
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