Artificial Intelligence and Employee Performance: A Human Resource Management Perspective

Abstract

Artificial Intelligence (AI) is transforming Human Resource Management (HRM) practices, offering opportunities to enhance employee performance through data-driven decision-making, automated feedback, and streamlined HR processes. This article examines the impact of AI on employee performance from an HRM perspective, drawing on a literature-based research method that synthesizes findings from recent academic studies. The review focuses on three key areas: AI-based HRM practices, employee performance and productivity, and the challenges of AI adoption. The review analyses AI applications in recruitment, performance evaluation, training and development, and workforce decision-making, while also addressing the ethical and organizational challenges associated with AI adoption. The findings indicate that AI can significantly improve employee productivity, motivation, and job performance when integrated effectively into HRM practices. Specifically, AI-enabled performance feedback, particularly when constructive and learning-oriented, enhances employee development and reduces interpersonal concerns. However, the review also identifies critical challenges, including algorithmic bias, privacy and data security risks, lack of transparency, and employee resistance. These factors can undermine the effectiveness and fairness of AI-based HR decisions. The study emphasizes that AI should augment rather than replace human judgment, with human oversight remaining essential for ethical and equitable outcomes. Organizational support, employee training, clear policies, and trust-building are identified as key conditions for successful AI implementation. Overall, the evidence suggests that AI has substantial potential to enhance HRM and employee performance, but its benefits depend on responsible adoption, transparency, and the preservation of human control in decision-making processes. 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