AI-Powered Performance Management: Machine Learning Approaches for Employee Evaluation and Development

This study explores how AI, primarily, the axiomatic realms of machine learning algorithms, is revolutionizing performance management systems. In most traditional systems, there are issues of bias, and poor performance and even the methodologies used are dated. The above-mentioned challenges are resolved in AI-powered solutions by improving the inherent objectivity of thinking. The real-time insights provided; the capacity to provide predictions. Supervised, as well as unsupervised learning enhances the method of employee assessment and reinforcement learning helps in enhancing self-development plans. This analysis shows that Random Forest and XGBoost models yield the best performance and have higher prediction accuracy. Although data may be prejudiced and there are a lot of ethical issues, AI provides a great opportunity to optimize the employee's job performance and their satisfaction with results for the organization's management.