Artificial Intelligence in Human Resource Management: Advanced Computing Systems for Talent Analytics and Decision Making

Abstract

Artificial Intelligence (AI) is transforming Human Resource Management (HRM) by integrating advanced computing systems into recruitment, talent analytics, performance evaluation, and decision-making processes. AI-driven tools provide HR professionals with data-driven insights, enabling them to identify talent, predict workforce trends, and enhance employee engagement while streamlining administrative tasks. With the rise of talent shortages and increased workplace complexities, AI offers solutions to create more adaptive, equitable, and efficient HR ecosystems. This paper explores the role of AI in HRM, focusing on its application in talent acquisition, workforce analytics, employee development, and decision-making. It highlights the underlying computational technologies, such as machine learning algorithms, natural language processing, and cloud-based analytics, that power AI systems. Case studies illustrate how organizations have used AI to improve operational efficiency and enhance workforce engagement. However, the adoption of AI in HRM also presents challenges, including data privacy concerns, algorithmic bias, and the need for continuous upskilling of HR professionals. Addressing these challenges requires a balanced approach that emphasizes ethical AI practices, robust data governance frameworks, and transparent decision-making. This study concludes by exploring the future of AI in HRM, emphasizing the integration of advanced technologies like quantum computing and federated learning to drive innovation. As AI continues to reshape HR processes, it promises to build a smarter, data-driven workforce that is equipped to thrive in a competitive global economy.

 Advanced Computing