A Bibliometric Mapping of Artificial Intelligence Research in Digital Public Service (2020–2025)
AI ceases to be a matter of discussion as a technological innovation, but also of how governments redesign the provision of public services, deal with information, and react to the more intricate needs of society. Research in the field of AI and digital public service has been accelerating rapidly over the past few years, particularly amid the accelerated pace of digital transformation during the COVID-19 period and beyond. However, the discourse is still dispersed across different fields and research issues, and thus, it is difficult to follow the development of the field as a system. The aim of this paper is therefore to conduct a review of the development and research frontier of AI in Digital Public Service during the period between 2020 and 2025 through a bibliometric approach. The study used bibliographic data acquired via the Scopus database. Data were collected using a structured search strategy that combines Boolean operators and keywords related to artificial intelligence and digital public service. A total of 662 publications were retrieved and visualized using VOSviewer. After the use of a minimum occurrence of five, 216 keywords were chosen and grouped into six thematic clusters. The results show a definite upward trend in the number of publications after 2022, indicating greater academic interest in AI-based governance and digital transformation in the state sector. Several prevailing themes emerged, including machine learning, digital government, public administration, natural language processing, information management, and AI governance. Overall, the findings suggest that the study of AI in digital public service has moved beyond the argument about fundamental digitalization to address significant questions about governance, public value, and the responsible use of AI.
Keywords: Artificial intelligence, Digital public service, Digital government, Bibliometric analysis, Smart governance.
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