Artificial Intelligence in Public Sector Information Systems: A Hybrid Systematic Literature Review And Bibliometric Analysis

DOI

10.2991/978-94-6463-926-1_9How to use a DOI?

Keywords

Artificial Intelligence; Bibliometric Analysis; Public Sector Information System; Systematic Review; VOSviewer

Abstract

This research presents a systematic literature review (SLR) and bibliometric analysis to examine how artificial intelligence (AI) determinants are conceptualised, implemented, and evaluated in public sector information systems. Following the PRISMA guidelines, 38 reviewed articles published between 2020 and 2025 were selected from Scopus and analysed using VOSviewer to map co-occurring keywords, thematic evolution, and collaboration networks. The findings reveal seven main challenges: fragmented research, geographical publication bias toward developed countries, limited access to high-quality datasets, methodological inconsistencies, ethical and regulatory ambiguities, infrastructure disparities, and trust gaps among stakeholders. Although AI offers significant potential to improve decision-making, service delivery, and operational efficiency, these challenges hinder its fair and effective adoption. To address these issues, this paper proposes a conceptual framework that integrates bibliometric and thematic insights, with an emphasis on inclusive governance, context-appropriate adaptation, and ethical compliance. The results provide actionable recommendations for policymakers, researchers, and practitioners aiming to develop explainable, inclusive, and accountable AI in the context of diverse public sectors.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Munengsih Sari Bunga
AU  - Mochamad Agung Wibowo
AU  - Sutikno Sutikno
PY  - 2025
DA  - 2025/12/31
TI  - Artificial Intelligence in Public Sector Information Systems: A Hybrid Systematic Literature Review And Bibliometric Analysis
BT  - Proceedings of the International Conference on Applied Science and Technology on Engineering Science 2025 (iCAST-ES 2025)
PB  - Atlantis Press
SP  - 65
EP  - 72
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-926-1_9
DO  - 10.2991/978-94-6463-926-1_9
ID  - Bunga2025
ER  -