Artificial Intelligence and HR Analytics: A Predictive Framework for Employee Performance and Retention

Abstract

The integration of Artificial Intelligence (AI) and Machine Learning (ML) is transforming Human Resource Management (HRM) into a data-driven and predictive function. This study proposes an AI-driven HR analytics framework to improve employee performance and retention through predictive decision-making. The framework utilizes data from HR systems, performance records, and employee feedback to identify patterns related to productivity and turnover. Machine learning algorithms such as Logistic Regression and Random Forest are used to predict employee attrition and support strategic workforce planning. The study also addresses ethical concerns including data privacy, algorithm bias, and transparency in AI-based HR systems. The findings indicate that AI-powered HR analytics can enhance employee engagement, optimize talent management, and support organizational growth through proactive and evidence-based HR decisions.