Digital HRM as Multi-Level Architecture and Governance

Research on the digitalization of HRM is growing rapidly, yet the field remains conceptually fragmented and weakly integrated across levels of analysis. We address this problem through a systematic and thematic review of 198 peer-reviewed journal articles on digital HRM. We conceptualize digital HRM as a socio-technical configuration in which HR infrastructures and AI-enabled decision systems reshape HR strategy, HR processes, and workforce governance across strategic, functional, individual, and social levels. Our synthesis organizes the literature into three macro-themes—HR Digital Transformation (HRDT), HR-Techs/e-HRM infrastructures, and AI-based HRM—and shows that each stream privileges different value-creation assumptions while unevenly theorizing control, datafication, and accountability. Building on a level-sensitive integration, we develop an architecture-and-governance framework that explains heterogeneous outcomes by tracing how digital HRM redistributes visibility, discretion, and accountability across levels through three cross-level mechanisms—datafication, delegated judgment (automation vs. augmentation), and orchestration. We conclude with a research agenda specifying boundary conditions (e.g., governance design, data quality, HR capability maturity) linking digital HR architectures and AI-enabled HR decisions to both performance and legitimacy outcomes.