A Leveraging Artificial Intelligence (AI) Powered Human Resource Management Strategy with Elevated Performance Metrics to Improve Talent Acquisition and Employee Engagement

The digital transformation period has turned Human Resource Management (HRM) into a strategic collaborative practice from its former administrative position. This research develops an elaborate strategy which utilizes Artificial Intelligence (AI) to transform Human Resource Management (HRM) capabilities in talent recruitment and employee engagement for contemporary enterprises. The proposed system improves both recruitment speed and workforce contentment through its integration of machine learning algorithms along with natural language processing (NLP) and reinforcement learning methods with traditional HR practices. The employment of NLP techniques during resume evaluation produced results that surpassed human screening with a measurement accuracy of 92.3%. XGBoost based predictive candidate-job fit analysis reached 89.6% accuracy in its assessment of organizational-demand and candidate-profile compatibility. The interpretation of employee feedback from different departments reached an 88.4% accuracy through LSTM models for sentiment analysis. The deployment of AI engagement monitoring technology resulted in a 34.4% average increase of employee engagement scores following implementation. The AI recommendation system received employee acceptance in 60.3% of cases according to its recorded data. The analyzed data shows that artificial intelligence offers organizations opportunities to optimize HR operations and decrease bias while making better data-based workforce decisions. Research findings indicate that artificial intelligence serves beyond being a supportive tool because it becomes a strategic partner for human capital management in digital environments.