Exploring the Role of Artificial Intelligence in Enhancing Talent Acquisition and Employee Retention Strategies

Human resources (HR) procedures have been drastically altered by artificial intelligence (AI) fast expansion, particularly in the areas of talent acquisition and employee retention. Though they are working hard to develop successful recruitment plans and keep good retention rates, organizations nonetheless struggle with issues including prejudices in decision-making and too high personnel turnover. Among other possible responses, artificial intelligence (AI) might automate administrative chores, offer predictive insights on employee happiness and attrition issues, and simplify candidate screening. In order to improve recruitment and retention rates, this article examines how artificial intelligence (AI) might be included into human resource (HR) systems utilizing predictive models and machine learning techniques. Python using TensorFlow and scikit-learn tools allowed us to create and assess a hybrid artificial intelligence framework. This framework helped to organize data on employee satisfaction and recruiting from many companies. The first tests have demonstrated that the framework precisely projects possible resignations with a 91% accuracy rate and increases recruitment efficiency by 28%. Comparisons with more conventional approaches draw attention to the more exact and affordable HR models augmented with artificial intelligence have been improved with. The significant findings imply that by lowering bias, improving decision-making, and motivating long-term employee involvement, artificial intelligence could support human resource teams. These findings reveal how artificial intelligence could modify human resource practices to attain better performance.