Artificial Intelligence in Public Sector Governance: A Bibliometric Analysis of Global Research Trends
DOI:
https://doi.org/10.33701/jtp.v18i1.6473Keywords:
Artificial Intelligence, AI Governance, Public Sector Governance, Public Administration, Digital Transformation, Algorithmic Accountability, Bibliometric AnalysisAbstract
Abstract
Artificial intelligence (AI) has moved from a technical innovation agenda to a governance issue that affects public decision-making, service delivery, organizational capacity, accountability, and citizen rights. Yet the literature is fragmented across information systems, public administration, computer science, law, and policy studies. This study maps the intellectual structure and thematic evolution of global research on AI in public sector governance through a bibliometric analysis of 263 English-language journal articles indexed in Scopus between 2021 and 2025. Bibliometrix/Biblioshiny and VOSviewer were used to examine publication dynamics, keyword frequency, co-occurrence, thematic positioning, and conceptual relationships. The results indicate a rapidly expanding and increasingly differentiated field. AI is the dominant conceptual anchor, while public sector, public policy, public administration, ethical technology, governance, and decision making form the principal connecting themes. The thematic map indicates that digital transformation, decision making, and public sector operate as motor themes; public policy and ethical technology represent an advanced governance-oriented stream; and algorithmic accountability, automation, and decision-support systems remain emerging or weakly integrated. The article argues that the field is shifting from an adoption-centred literature toward an institutional governance literature. It identifies four analytical tensions that require future research: capability versus control, efficiency versus equity, automation versus discretion, and innovation versus democratic legitimacy. The study contributes a research agenda that positions AI as a socio-technical and institutional transformation rather than a stand-alone computational tool.
Keywords: Artificial Intelligence; AI Governance; Public Sector Governance; Public Administration; Digital Transformation; Algorithmic Accountability; Bibliometric Analysis
Abstrak
Kecerdasan buatan (Artificial Intelligence/AI) telah bergeser dari agenda inovasi teknis menjadi isu tata kelola yang memengaruhi pengambilan keputusan publik, penyelenggaraan layanan, kapasitas organisasi, akuntabilitas, dan hak warga negara. Namun, literatur yang berkembang masih tersebar pada bidang sistem informasi, administrasi publik, ilmu komputer, hukum, dan studi kebijakan. Penelitian ini memetakan struktur intelektual dan evolusi tematik riset global mengenai AI dalam tata kelola sektor publik melalui analisis bibliometrik terhadap 263 artikel jurnal berbahasa Inggris yang terindeks Scopus pada periode 2021-2025. Bibliometrix/Biblioshiny dan VOSviewer digunakan untuk menganalisis dinamika publikasi, frekuensi kata kunci, ko-occurence, posisi tematik, dan hubungan konseptual. Hasil penelitian menunjukkan bidang yang berkembang cepat dan semakin terdiferensiasi. AI menjadi jangkar konseptual utama, sedangkan sektor publik, kebijakan publik, administrasi publik, teknologi etis, tata kelola, dan pengambilan keputusan menjadi tema penghubung utama. Peta tematik menunjukkan digital transformation, decision making, dan public sector sebagai motor themes; public policy dan ethical technology sebagai arus tata kelola yang semakin maju; sementara algorithmic accountability, automation, dan decision-support systems masih merupakan tema yang berkembang atau belum terintegrasi kuat. Artikel ini berpendapat bahwa bidang ini bergerak dari literatur yang berpusat pada adopsi menuju literatur tata kelola institusional. Empat ketegangan analitis diidentifikasi untuk agenda penelitian mendatang: kapasitas versus kontrol, efisiensi versus keadilan, otomatisasi versus diskresi, serta inovasi versus legitimasi demokratis.
Kata kunci: Kecerdasan Buatan; Tata Kelola AI; Tata Kelola Sektor Publik; Administrasi Publik; Transformasi Digital; Akuntabilitas Algoritmik; Analisis Bibliometrik
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References
1. Ananny, M., & Crawford, K. (2018). Seeing without knowing: Limitations of the transparency ideal and its application to algorithmic accountability. New Media & Society, 20(3), 973-989.
2. Aria, M., & Cuccurullo, C. (2017). Bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959-975.
3. Athaya, N. (2026). , Penerapan Artificial Intelligence ( AI ) dalam Sistem Administrasi Publik : Peluang , Tantangan , dan Etika Pelayanan Publik di Indonesia transformasi mendasar dalam tata kelola pemerintahan di berbagai negara . Konsep digital. 7(November 2025).
4. Bannister, F., & Connolly, R. (2014). ICT, public values and transformative government: A framework and programme for research. Government Information Quarterly, 31(1), 119-128.
5. Binns, R. (2018). Fairness in machine learning: Lessons from political philosophy. Proceedings of the 1st Conference on Fairness, Accountability and Transparency, 149-159.
6. Bullock, J. B. (2019). Artificial intelligence, discretion, and bureaucracy. American Review of Public Administration, 49(7), 751-761.
7. Cordella, A., & Bonina, C. M. (2012). A public value perspective for ICT enabled public sector reforms: A theoretical reflection. Government Information Quarterly, 29(4), 512-520.
8. Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285-296.
9. Dunleavy, P., Margetts, H., Bastow, S., & Tinkler, J. (2006). New public management is dead-long live digital-era governance. Journal of Public Administration Research and Theory, 16(3), 467-494.
10. Eubanks, V. (2018). Automating inequality: How high-tech tools profile, police, and punish the poor. St. Martin's Press.
11. Floridi, L., Cowls, J., Beltrametti, M., et al. (2018). AI4People-An ethical framework for a good AI society. Minds and Machines, 28, 689-707.
12. Fountain, J. E. (2001). Building the virtual state: Information technology and institutional change. Brookings Institution Press.
13. Faris, A., Harahap, R., & Harahap, A. M. (2023). Peran digitalisasi dalam meningkatkan partisipasi publik pada pengambilan keputusan tata negara. 9(2), 769–776.
14. Gil-Garcia, J. R., Dawes, S. S., & Pardo, T. A. (2018). Digital government and public management research: Finding the crossroads. Public Management Review, 20(5), 633-646.
15. Haug, N., Dan, S., & Mergel, I. (2024). Digitally induced change in the public sector: A systematic review and research agenda. Public Management Review, 26(7), 1963-1987.
16. Janssen, M., Brous, P., Estevez, E., Barbosa, L. S., & Janowski, T. (2020). Data governance: Organizing data for trustworthy artificial intelligence. Government Information Quarterly, 37(3), 101493.
17. Janowski, T. (2015). Digital government evolution: From transformation to contextualization. Government Information Quarterly, 32(3), 221-236.
18. Kroll, J. A., Huey, J., Barocas, S., et al. (2017). Accountable algorithms. University of Pennsylvania Law Review, 165, 633-705.
19. Kuziemski, M., & Misuraca, G. (2020). AI governance in the public sector: Three tales from the frontline. Data & Policy, 2, e10.
20. Lepri, B., Oliver, N., Letouze, E., Pentland, A., & Vinck, P. (2018). Fair, transparent, and accountable algorithmic decision-making processes. Philosophy & Technology, 31, 611-627.
21. Mergel, I., Edelmann, N., & Haug, N. (2019). Defining digital transformation: Results from expert interviews. Government Information Quarterly, 36(4), 101385.
22. Meijer, A., & Wessels, M. (2019). Predictive policing: Review of benefits and drawbacks. International Journal of Public Administration, 42(12), 1031-1039.
23. NIST. (2023). Artificial Intelligence Risk Management Framework (AI RMF 1.0). National Institute of Standards and Technology.
24. OECD. (2019). Recommendation of the Council on Artificial Intelligence. OECD Legal Instruments.
25. Page, M. J., McKenzie, J. E., Bossuyt, P. M., et al. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71.
26. Raji, I. D., Smart, A., White, R. N., et al. (2020). Closing the AI accountability gap: Defining an end-to-end framework for internal algorithmic auditing. Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, 33-44.
27. Reisman, D., Schultz, J., Crawford, K., & Whittaker, M. (2018). Algorithmic impact assessments: A practical framework for public agency accountability. AI Now Institute.
28. Selbst, A. D., Boyd, D., Friedler, S. A., Venkatasubramanian, S., & Vertesi, J. (2019). Fairness and abstraction in sociotechnical systems. Proceedings of the Conference on Fairness, Accountability, and Transparency, 59-68.
29. Sun, T. Q., & Medaglia, R. (2019). Mapping the challenges of artificial intelligence in the public sector: Evidence from public healthcare. Government Information Quarterly, 36(2), 368-383.
30. Tangi, L., Janssen, M., Benedetti, M., & Noci, G. (2021). Digital government transformation: A structural equation modelling analysis of driving and impeding factors. International Journal of Information Management, 60, 102356.
31. UNESCO. (2021). Recommendation on the ethics of artificial intelligence. UNESCO.
32. United Nations. (2024). United Nations e-government survey 2024: Accelerating digital transformation for sustainable development. United Nations Department of Economic and Social Affairs.
33. van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523-538.
34. Veale, M., & Brass, I. (2019). Administration by algorithm? Public management meets public sector machine learning. In K. Yeung & M. Lodge (Eds.), Algorithmic regulation (pp. 121-149). Oxford University Press.
35. Vial, G. (2019). Understanding digital transformation: A review and a research agenda. Journal of Strategic Information Systems, 28(2), 118-144.
36. Wirtz, B. W., Weyerer, J. C., & Geyer, C. (2019). Artificial intelligence and the public sector-Applications and challenges. International Journal of Public Administration, 42(7), 596-615.
37. World Bank. (2022). GovTech maturity index 2022 update: Trends in public sector digital transformation. World Bank.
38. Wutsqah, U., & Erwiant, A. (2025). Teknologi Artifical Intteligence ( AI ) Dalam Upaya Menciptakan Tata Kelola Pemerintahan Yang Inklusif. 5(1), 78–86.
39. Yeung, K. (2018). Algorithmic regulation: A critical interrogation. Regulation & Governance, 12(4), 505-523.
40. Zupic, I., & Cater, T. (2015). Bibliometric methods in management and organization. Organizational Research Methods, 18(3), 429-472.
