Abstract
This study conducts a comprehensive bibliometric analysis of research on digital transformation within the social sciences from 1997 to 2024 and integrated these findings to develop an Agentic Model of Human–AI Interaction. Drawing on 389 articles indexed in the Web of Science database, the analysis examines publication dynamics, influential authors and institutions, citation structures, and thematic research clusters using RStudio-based bibliometric tools. Results reveal that digital transformation has evolved into a central driver of societal, economic, and cultural change, with research output peaking in 2021–2022. Prominent themes include artificial intelligence, innovation processes, digital media technologies, and the societal implications of emerging technologies. Beyond mapping the knowledge landscape, the study proposes a conceptual agentic system model that explains how AI agents process, interpret, and operationalize human queries through structured stages of planning, retrieval, reasoning, and response generation. This integration of bibliometric insights with system conceptualization contributes to a deeper understanding of the evolving human–AI relationship and highlights key gaps and future research opportunities in the study of agentic systems within digital transformation.