AI- DRIVEN PERFORMANCE MANAGEMENT SYSTEMS AND EMPLOYEE ENGAGEMENT

The growing integration of Artificial Intelligence (AI) in human resource management has significantly transformed traditional performance management systems, making them more data-driven, continuous, and personalized. This study examines the role of AI-driven performance management systems in enhancing employee engagement within modern organizations. The primary objective is to analyze how AI-based tools such as real-time feedback mechanisms, predictive analytics, and automated performance tracking influence employee motivation, satisfaction, and overall engagement levels. A quantitative research design was adopted, with data collected from 150 employees across various service sector organizations using structured questionnaires. Descriptive and inferential statistical techniques were employed to analyze the relationship between AI-enabled performance practices and employee engagement. The findings indicate a strong positive correlation between the use of AI in performance management and higher levels of employee engagement, particularly due to increased transparency, timely feedback, and personalized development plans. However, concerns related to data privacy and over-reliance on technology were also identified as potential challenges. The study concludes that while AI-driven systems significantly improve engagement and organizational efficiency, a balanced approach combining human judgment and technological capabilities is essential for sustainable outcomes.