Artificial Intelligence in Human Resources: A Systematic Review
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Abstract
This Artificial Intelligence (AI) has emerged as a fundamental driver of digital transformation in organizations, particularly in the field of human resource management (HRM). This study aims to examine the main AI techniques applied in HR functions, identifying their most common uses, benefits, implementation challenges, and the key factors influencing their adoption. The research follows a systematic literature review methodology, guided by the PRISMA 2020 framework to ensure transparency, rigor, and reproducibility. The central objective is to understand how AI contributes to strategic talent management and which organizational, technological, and ethical factors shape its successful adoption. The hypothesis suggests that effective integration depends not only on technological availability but also on digital skills development, ethical governance, and cultural readiness within organizations. The findings show that AI is predominantly used in recruitment, performance evaluation, and attrition prediction, where tools like machine learning and natural language processing improve speed, consistency, and predictive accuracy. Benefits include increased efficiency, support for decision-making, and the potential to mitigate human bias. However, several challenges persist, such as data quality limitations, algorithmic bias, employee resistance, and insufficient regulatory frameworks. Adoption is more likely when organizations invest in digital infrastructure, promote transparent practices, and provide training for HR professionals
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