UNDERSTANDING DIGITAL TRANSFORMATION AND AGENTIC SYSTEM THROUGH BIBLIOMETRICS: DEVELOPING AN AGENTIC MODEL OF HUMAN–AI INTERACTION

Dinara Zhaisanova; Sholpan Jamanbalayeva; Diana Zhyilyssova; Ayaulym Baidulla

doi:10.26577/jpcsit202548

Authors

Dinara Zhaisanova Al-Farabi Kazakh National University, Almaty, Kazakhstan https://orcid.org/0000-0002-8116-6111 (unauthenticated)
Sholpan Jamanbalayeva The Institute of Philosophy, Political Science and Religious Studies of the Committee of Science of the Ministry of Science and Higher Education of the Republic of Kazakhstan, Almaty, Kazakhstan https://orcid.org/0000-0003-0310-529X (unauthenticated)
Diana Zhyilyssova Al-Farabi Kazakh National University, Almaty, Kazakhstan https://orcid.org/0000-0001-9211-5224 (unauthenticated)
Ayaulym Baidulla Al-Farabi Kazakh National University, Almaty, Kazakhstan https://orcid.org/0009-0002-3083-9715 (unauthenticated)

DOI:

https://doi.org/10.26577/jpcsit202548

Keywords:

bibliometric analysis, digital transformation, social sciences, agentic system, human-AI interaction, conceptual structure

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.

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Author Biographies

Dinara Zhaisanova, Al-Farabi Kazakh National University, Almaty, Kazakhstan

Dinara Zhaisanova is a PhD in Innovation management (2022). She is now the acting associate professor of the Department of the Artificial intelligence and Big Data. Her research interests include innovation technologies, management of technologies. ORCID iD: 0000-0002-8116-6111
Sholpan Jamanbalayeva, The Institute of Philosophy, Political Science and Religious Studies of the Committee of Science of the Ministry of Science and Higher Education of the Republic of Kazakhstan, Almaty, Kazakhstan

Sholpan Jamanbalayeva is Doctor of Sociological Sciences, Professor, Deputy General Director for Scientific Work of The Institute of Philosophy, Political Science and Religious Studies of the Committee of Science of the Ministry of Science and Higher Education of the Republic of Kazakhstan. Her research interests span across interdisciplinary domains involving digital society, sociocultural dynamics, and religion, with a specific geographic focus on Kazakhstan. ORCID iD: 0000-0003-0310-529X
Diana Zhyilyssova, Al-Farabi Kazakh National University, Almaty, Kazakhstan

Diana Zhyilussova is a docotral’s degree student at the Al-Farabi Kazakh National University in the Department of Artificial Intelligence and Big Data (Almaty, Kazakhstan, zhyilyssovadiana@gmail.com). Her academic interests focus on artificial intelligence and data-driven technologies. ORCID iD: 0000-0001-9211-5224
Ayaulym Baidulla, Al-Farabi Kazakh National University, Almaty, Kazakhstan

Ayaulym Baidulla is a docotral’s degree student at the Al-Farabi Kazakh National University in the Department of Artificial Intelligence and Big Data. Her academic interests focus on artificial intelligence and data-driven technologies. ORCID iD: 0009-0002-3083-9715