ARTIFICIAL INTELLIGENCE IN RECRUITMENT AND PERFORMANCE MANAGEMENT: ETHICAL CONSIDERATIONS AND EFFECTIVENESS

The integration of AI into human resource management has changed the very foundation of how organizations identify, evaluate, and develop talent. This review covers both the operational benefits and ethical complexities arising from AI-driven recruitment and performance management systems. Embedded in state-of-the-art empirical studies and theoretical frameworks, this paper discusses how algorithmic decision-making reshapes traditional HR practices and gives cause for concern regarding issues of bias, transparency, and human agency. The review synthesizes findings on many dimensions: effectiveness of the AI tools in predicting job performance, the emergence of algorithmic discrimination, privacy implications of continuous monitoring systems, shifting dynamics in manager-employee relations, among others. What becomes clear is that AI's promise of efficiency and objectivity recurs in a fundamental way to questions of fairness and human dignity. Organizations adopting these technologies face a balancing act between technical capability and ethical responsibility, weighing data-driven insight against irreducible complexity in the expression of human potential. As such, the paper states, successful implementation requires more than technological sophistication; it calls for reflective governance frameworks which protect human judgement while leveraging computational advantages.