Revolutionising Talent Management through AI: A Case Study of IBM’s Cognitive HR Practices

Abstract

Artificial intelligence (AI) is increasingly reshaping human resource management from a transactional support function into a strategic, data-driven organisational capability. While prior research predominantly examines isolated AI applications such as recruitment automation or learning analytics, limited empirical work explores AI as an integrated talent management system. This study employs a qualitative single-case design to analyse IBM’s cognitive HR transformation across attraction, skills intelligence, learning and development, performance management, engagement, and retention. Findings indicate that AI-enabled skills inference enhances internal mobility and workforce agility, personalised learning systems strengthen career ownership, and predictive analytics support proactive retention and pay equity. However, sustainable outcomes depend on ethical governance, algorithmic transparency, and socio-technical alignment. The analysis further demonstrates that AI integration can connect traditionally fragmented HR processes through continuous, data-informed workforce insights. It also highlights the importance of human oversight in balancing technological efficiency with employee autonomy, fairness, and trust. These findings provide practical implications for organisations seeking to scale AI-enabled HR systems while maintaining responsible and employee-centred practices. The study advances Human Capital Theory, the Resource-Based View, and Socio-Technical Systems Theory by conceptualising AI-enabled HR as a strategic organisational capability embedded within responsible governance structures.