Transformation of Talent Management Through Digital Technologies

Abstract

Talent management is being reshaped like never before by the rapid evolution of artificial intelligence (AI), big data analytics, machine learning (ML), and robotic process automation (RPA) and their integration into human resource management (HRM) processes. Based on a synthesis of the evidence from 20 peer-reviewed studies of digital technologies published between 2019 and 2026, this paper explores the impact of digital technologies on talent identification, acquisition, development and retention in modern organisations. The integration of quantitative metrics, conceptual frameworks and empirical findings across a range of industrial and geographic contexts is done through a thematic synthesis approach. Some of the key takeaways presented in the literature reviewed are that time-to-hire can be reduced by up to 75%, the voluntary turnover can be reduced by about 20–30%, and the accuracy of talent decision can be improved by 30–50%. The paper provides evidence that the adoption of digital technologies in talent management is not a linear process of technology but a systemic organisational capability transformation that needs to leverage on data infrastructure, human capital competencies, ethical governance and strategic leadership. The six main themes explored are: (a) The evolution of HR digitalisation, (b) AI driven talent acquisition, (c) People analytics and HR decision-making, (d) Digital learning and development, (e) Ethical and regulatory issues, and (f) Future directions for intelligent HR systems. The analysis shows that key challenges such as algorithmic bias, data privacy concerns and lack of analytical skills among HR practitioners persist, while key enablers include organizational culture, leadership commitment and AI capability frameworks. The results have important implications for HR scholars, practitioners and HR policy makers.