The Mediating Effect of Artificial Intelligence in Recruitment and Talent Management Practices on Organizational Performance

Artificial intelligence has become a significant driver of change in human resource management, particularly in recruitment and talent management. AI-based tools are increasingly used for resume screening, candidate matching, personalized training, performance analytics, and retention management. Consequently, AI is viewed not only as a technological innovation but also as a strategic resource that can strengthen organizational effectiveness. This study examines how AI-driven recruitment and talent management practices influence organizational performance and identifies the mediating mechanisms through which this influence occurs. Special attention is given to employee engagement and perceived job security as key explanatory variables. The study is based on a secondary analytical approach using recent empirical studies, conceptual papers, and industry reports published mainly in 2024 and 2025. The analysis integrates insights from social capital theory, the resource-based view, and information processing theory. The findings show that AI-enabled recruitment and talent management positively affect organizational performance both directly and indirectly. Recruitment, performance management, and training initiatives demonstrate positive effects, while employee engagement emerges as a significant mediator. Perceived job security also plays an important mediating role. Organizations that implement advanced AI-driven talent systems report improvements in time-to-hire, cost-per-hire, retention, employee satisfaction, and overall performance. The results suggest that AI creates organizational value not only through efficiency gains but also through its influence on employee perceptions and workplace experience. Future research should apply longitudinal approaches and examine industry-specific and ethical dimensions of AI implementation in HRM.