Digital transformation of human resource management: A bibliometric analysis of HR analytics, AI, and E-HR
TL;DR
The evidence reveals a path-dependent transition from administrative digitization to integrated digital HR capability and the rapid expansion of AI-related research after 2020 is accompanied by continuing theoretical fragmentation, geographically concentrated knowledge production, and limited attention to ethical governance, multi-level effects, and longitudinal value realization.
Abstract
This study maps explains the conceptual evolution of digital human resource management (digital HRM) by integrating research on electronic human resource management (e-HRM), human resource (HR) analytics, and artificial intelligence (AI). It examines how these research streams have developed, intersected, and collectively reshaped the strategic role of HRM. The study adopts a bibliometric review design using records retrieved from the Web of Science Core Collection and Scopus. Following a PRISMA-based identification, screening, and deduplication process, the final corpus comprises 1472 unique journal articles and reviews published in 576 sources between 1991 and 2026. Findings: The evidence reveals a path-dependent transition from administrative digitization to integrated digital HR capability. e-HRM and human resource information systems (HRIS) have progressively shifted from being focal innovations to providing the data and process infrastructure on which later capabilities depend. HR analytics functions as an interpretive capability that converts workforce data into decision-relevant insight, whereas AI extends this architecture through prediction, automation, and decision augmentation. The rapid expansion of AI-related research after 2020 is accompanied by continuing theoretical fragmentation, geographically concentrated knowledge production, and limited attention to ethical governance, multi-level effects, and longitudinal value realization.
