Digital Transformation and People Analytics in Inclusive Education: A Systematic Review for Organization Development Strategies

Abstract

People analytics is the discipline of collecting and using workforce data to support evidence-based decision-making that benefits the organization and its personnel. How can we deepen our understanding of multilevel dynamics in the digital transformation of Human Resource Management (HRM)? Currently, People Analytics (PA) and Artificial Intelligence Adoption (AIA) are vital strategic tools, shaped by internal digital maturity and external factors such as the United Arab Emirates’ (UAE’s) Vision 2031. These practices influence organizational results at various levels, from individual employee engagement and digital workplace anxiety to team collaboration and overall institutional success. As a result, the connection between PA and Organizational Development (OD) is inherently multilevel. The understanding of how PA systems drive OD in multilevel studies, and how these data-driven models theoretically link technological factors to outcomes across different levels, remains incomplete. This study questions whether multilevel research in PA offers a clear theoretical basis for considering PA as an OD intervention and whether the connections between individual-level digital data and organizational-level strategic success are logically and coherently explained through theory. This paper presents a systematic review of 15 key studies from 2020 to 2026, highlighting a wide range of theoretical perspectives, from micro-level algorithmic management to macro-level sustainable competitive advantage. The results suggest significant opportunities to deepen multilevel theorizing in this area, especially in the UAE context, by linking descriptive metrics to prescriptive OD strategies. Overall, this research contributes to the field by systematically charting the theoretical discussions surrounding the multilevel aspects of PA as a tool for transformative OD.