AGENTIC AI IN TALENT DISCOVERY

Abstract

Agentic Artificial Intelligence is defined as AI systems that act autonomously with goal-directed behaviour, is revolutionizing talent discovery in the contemporary Human Resource (HR) landscape. This paper explores the evolving role of agentic AI in identifying, engaging, and evaluating potential candidates for organizations, particularly in the context of global capability canters (GCCs). Through a rigorous literature review, we examine AI’s contributions to bias mitigation, efficiency improvement, and strategic workforce planning. The methodology synthesizes qualitative and quantitative research from both academic and industry sources, providing an integrated perspective on technological influence. The findings highlight that agentic AI systems enable better predictive analytics, enhanced candidate experience, and data-driven hiring decisions. However, challenges persist in areas such as ethical alignment, explainability, and regulatory compliance. Our review emphasizes the importance of responsible AI design and collaborative ecosystems involving human and machine agents. Future research should focus on explainable AI, privacy considerations, and cross-border compliance in talent acquisition.