Artificial Intelligence in Human Resource Management - Aris Setia Noor; Firdiansyah Lukman; Pandef Rudianto (PT. Anagata Sembagi Education, 2026)
Artificial intelligence (AI) is transforming human resource management (HRM) from an administrative function into a data-driven strategic capability. This article synthesizes twenty-five peer-reviewed sources published between 2021 and 2026 to examine how AI technologies, including machine learning, natural language processing, and generative AI, are reshaping recruitment, training, performance management, compensation, and retention. Using a structured literature review method with a PRISMA-informed research flow, this study identifies patterns across empirical, conceptual, and bibliometric studies on AI-HRM integration. The findings show that AI enhances the speed and consistency of recruitment screening, personalizes learning and development pathways, and produces predictive insights that support retention and workforce planning. At the same time, the literature consistently raises concerns about algorithmic bias, data privacy, and the erosion of human judgment in high-stakes decisions such as hiring and termination. The novelty of this review lies in integrating strategic, ethical, and technological perspectives into one conceptual framework linking AI capability, HR functional application, organizational outcome, and governance safeguard, an integration most prior single-function reviews omit. The article concludes that sustainable AI-HRM adoption requires augmentation rather than replacement of human decision-makers, supported by transparent governance, continuous auditing, and HR professionals equipped with data literacy to interpret and contest algorithmic recommendations responsibly.