Optimizing Digital Talent Management with AI: Analytical Approaches and Innovations

Introduction: The application of artificial intelligence (AI) in talent management is reforming recruitment, workforce development, and employee engagement. Traditional human resource (HR) practices are being displaced by AI technologies that accelerate processes, eliminate discriminatory hiring, and facilitate improved decision-making. Purpose: This chapter explains how AI employs data predictions, machine learning (ML), and chatbots to enable automated recruitment. This, in turn, allows rapid screening of candidates’ skills, matching of jobs, and more diverse hiring. AI also enables tracking the progress of workers, real-time performance measurement, and personalized learning plans, thus ensuring employee satisfaction and preventing staff turnover. Scope: The study examines AI applications in HR, including predictive analytics, ML, and chatbots for hiring, performance tracking, and employee retention strategies. It also discusses ethical challenges such as algorithmic bias and data privacy. Methodology: A qualitative analysis of AI-driven HR tools and case studies from companies implementing AI in talent management is conducted to assess its impact on efficiency and fairness. Findings: AI accelerates hiring, improves diversity, enhances performance tracking, and personalizes learning plans, reducing turnover. However, risks like biased algorithms and data security concerns necessitate ethical AI implementation with human oversight. Proper AI integration can create a data-driven, inclusive, and competitive talent management system, balancing technological advancements with human expertise.