In the modern digital era, organizations are increasingly adopting Artificial Intelligence (AI) to enhance human resource practices, especially employee performance appraisal systems. Traditional appraisal methods often suffer from subjectivity, bias, and inefficiencies, which affect employee satisfaction and organizational performance. This study examines the role of AI-driven performance management systems in transforming employee appraisal methods. The research focuses on understanding how AI improves appraisal accuracy, reduces bias, and enhances decision-making processes. It also compares traditional appraisal systems with AI- based approaches and evaluates their impact on employee performance and organizational outcomes. The study adopts a descriptive research design, collecting primary data through structured questionnaires and secondary data from journals and reports. The findings reveal that AI-driven systems significantly improve transparency, efficiency, and fairness in performance evaluation. Employees show higher engagement and trust in AI-based systems compared to traditional methods. However, the study also highlights challenges such as data privacy concerns and lack of human judgment. The study concludes that organizations should adopt a hybrid appraisal approach combining AI technology with human insights to achieve optimal performance management outcomes.