The Application of Machine Learning Algorithms for Optimizing Employee Performance Evaluation

This paper explores the integration of machine learning applications in employee performance evaluation, addressing the limitations of traditional methods. The purpose is to highlight how ML technologies can enhance decision-making processes and contribute to organizational growth. Key research issues include data privacy challenges, algorithmic bias, and employee resistance. Solutions involve establishing robust data frameworks, training personnel, and ensuring ethical use of data. The feasibility of these solutions is supported by real-world case studies demonstrating improved employee satisfaction and retention rates through effective ML implementation. This approach positions organizations for success in a rapidly evolving workplace.