Artificial Intelligence in Human Resource Management: Transforming Talent Acquisition, Employee Engagement, and Performance Management

Abstract

Artificial intelligence has moved from a peripheral experiment to a structural feature of human resource management. This chapter examines how AI is reshaping three interlocking pillars of the HR function: talent acquisition, employee engagement, and performance management. Drawing on recent industry research and scholarly literature, the chapter traces the shift from rule-based automation toward predictive and, increasingly, agentic systems capable of sourcing candidates, forecasting workforce needs, synthesising performance signals, and personalising the employee experience at scale. It also confronts the tension between efficiency gains and the ethical, legal, and human costs of algorithmic decision-making, including bias, opacity, surveillance, and the erosion of managerial judgment. The chapter closes with a discussion of governance frameworks and a forward-looking assessment of human-AI collaboration, arguing that the organizations most likely to benefit from AI in HRM are those that treat it as an augmentation of human judgment rather than a replacement for it.