REVOLUTIONIZING HR: AI-DRIVEN TRANSFORMATION IN TALENT ACQUISITION, DEVELOPMENT, AND MANAGEMENT
Artificial intelligence; bias reduction; human resource virtual assistants; human-centred HR; recruitment automation; talent management
Introduction: Organizations in the knowledge-based industry depend on intellectual capacity, where key talent plays a major role in their success and business sustainability. Human resource (HR) management, in its traditional form involves labour-intensive processes and practices that are prone to unconscious bias, inadequate retention measures and diversity issues creating significant challenges in talent management. Purpose: The study brings to the fore a multi-stakeholder outlook that makes the adoption of artificial intelligence (AI) very lucrative. This study aims to highlight the capabilities of AI that address its limitations and retain a human-centric approach. Scope: The study encompasses the whole gamut of talent management lifecycle, starting from recruitment automation initiatives to onboarding, career planning and development, employee engagement, performance management, and succession planning in large global organizations. Methodology: The authors carried out an extensive review of the literature and analysis of use cases encompassing the use of AI and its implementation strategies, outcomes, and best practices, spanning the myriad talent acquisition and management functions. Findings: About 40% of large organizations have plans to invest in AI-enabled skills management solutions by 2028. AI-driven talent analyticshaveenabledbettercandidateassessment,hiringbiaseshave significantly reduced, and retention rates have increased an 82%. Significant workload savings, enhanced prediction capabilities, and improved accuracy across talent management processes are some of the other benefits of AI-enabled talent management solutions. AI usage has enhanced HR professionals efficiency, leadership has improved their decision-making capabilities, and employees have experienced increased opportunities for personal and professional development. Individual chapters 2026 The authors.
Artificial Intelligence for Digital Talent Acquisition and Management: Analytical Approaches, Practices, Models for Digitalization;pp.95-112
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https://www.scopus.com/pages/publications/105034486368?origin=resultslist
Niranjan L.R., aSchool of Business and Management, Christ University, Karnataka, Bangalore, India; Rajan S., Faculty of Management and Commerce, Ramaiah University of Applied Sciences, Karnataka, Bangalore, India