AI-Enabled Talent Management: Transforming Recruitment, Performance and Employee Engagement

Abstract

Artificial intelligence (AI) is rapidly transforming the way organizations recruit, assess, engage and retain employees by transforming the way they do these in the organization. Although existing literature has deeply explored various AI-based tools and applications in the field of human resource management, there is a strong need for a theoretical understanding of how AI alters the basic principles of talent management as a practice. Addressing the need, in this chapter, a theoretical and integrative approach has been applied, applying various established theories in the realms of organization, human resource and behaviours as a way of reinterpreting talent management in the AI era. Counter to conventional thinking that regards AI as a mere technological advancement, in this analysis, AI-based talent management has been identified as a social, technical and strategic phenomenon that alters the way organizations recruit members, manage their performance and encourage them to work. This analysis has applied classical concepts such as Person–Job Fit Theory, Signalling Theory, Human Capital Theory, Goal Setting Theory, Expectancy Theory, Agency Theory, Job Demands–Resources Theory, Social Exchange Theory, Self-Determination Theory, Resource-Based View and Institutional Theory. This chapter develops these new viewpoints and constructs a conceptual framework for AI-enabled talent management. The framework describes how talent outcomes are impacted by AI capabilities via hiring, performance and engagement processes.