Digital Fiscal Accountability under Indonesian Administrative Law: A Framework for AI-Driven Regional Budget Governance

Fitria Fitria; Eko Nuriyatman; Firdaus Arifin; Rahayu Repindowaty Harahap; Hanif Hardianto; Siti Fatimah; Rustian Mushawirya

Authors

Fitria Faculty of Law, Universitas Jambi, Indonesia https://orcid.org/0009-0009-4395-4561
Eko Nuriyatman Faculty of Law, Universitas Jambi, Indonesia https://orcid.org/0000-0002-6890-3121
Firdaus Arifin Faculty of Law, Universitas Pasundan Bandung, Indonesia https://orcid.org/0000-0002-4830-7605
Rahayu Repindowaty Harahap Faculty of Law, Universitas Jambi, Indonesia https://orcid.org/0000-0001-7655-5801
Hanif Hardianto Faculty of Law, Social, and Political Sciences, Universitas Terbuka, Indonesia https://orcid.org/0009-0000-3393-9493
Siti Fatimah Faculty of Social Sciences and Law, Universitas Veteran Bangun Nusantara, Indonesia https://orcid.org/0000-0003-3752-1769
Rustian Mushawirya Faculty of Law, Universitas Jambi, Indonesia https://orcid.org/0009-0008-8502-5456

Abstract

Artificial intelligence (AI) is increasingly used to support public-sector fiscal analysis. Yet, its integration into regional budgeting creates a legal problem that existing Indonesian administrative-law arrangements do not expressly resolve: how AI-generated recommendations may be used without transferring legally binding decision-making authority from public officials to algorithmic systems. This article examines the normative conditions for using AI as a decision-support instrument in regional budget governance. It develops a digital fiscal accountability framework for addressing fiscal turbulence, transparency, responsibility, and reviewability. The research uses a normative juridical method based on statutory and conceptual approaches. Primary legal materials are analyzed to identify rules and principles concerning governmental authority, administrative procedure, accountability, data protection, and digital government, while secondary literature is used to construct the conceptual relationship between administrative law and algorithmic governance. The analysis finds that AI may improve fiscal forecasting, anomaly detection, and scenario analysis, but these benefits do not make AI an autonomous administrative decision-maker. The proposed framework therefore requires human validation, traceable decision records, data-quality controls, algorithmic auditability, contestability, and a clear allocation of responsibility among officials, institutions, and technology providers. Digital fiscal accountability is proposed as a normative reconstruction that connects existing administrative-law principles with AI-specific safeguards rather than as a claim that Indonesian law already comprehensively regulates AI-driven budgeting.

References

Aldemir, Ceray, and Tuğba Uçma Uysal. 2025. “Artificial Intelligence for Financial Accountability and Governance in the Public Sector: Strategic Opportunities and Challenges.” Administrative Sciences 15(2):58. doi: 10.3390/admsci15020058.

de Almeida, Patricia Gomes Rêgo, and Carlos Denner dos Santos Júnior. 2025. “Artificial Intelligence Governance: Understanding How Public Organizations Implement It.” Government Information Quarterly 42(1):102003. doi: 10.1016/j.giq.2024.102003.

Alon-Barkat, Saar, Madalina Busuioc, Kayla Schwoerer, and Kristina S. Weißmüller. 2025. “Algorithmic Discrimination in Public Service Provision: Understanding Citizens’ Attribution of Responsibility for Human versus Algorithmic Discriminatory Outcomes.” Journal of Public Administration Research and Theory 35(4):469–88. doi: 10.1093/jopart/muaf024.

Chen, Tzuhao, Mila Gasco‐Hernandez, and J. Ramon Gil‐Garcia. 2026. “Understanding Accountability in AI Use Within the Public Sector: Insights From State Governments in the United States.” Public Administration. doi: 10.1111/padm.70051.

Coglianese, Cary, and David Lehr. 2017. “Regulating by Robot: Administrative Decision Making in the Machine-Learning Era.” The Yale Law Journal 90(4):912. doi: 10.2307/795905.

European Parliament and Council of the European Union. 2024. “Regulation (EU) 2024/1689 (Artificial Intelligence Act).” Official Journal of the European Union. Retrieved August 31, 2026 (https://eur-lex.europa.eu/eli/reg/2024/1689/oj).

Fitria, Eko Nuriyatman, Latifah Amir, and Sitta Saraya. 2025. “Administrative Law and the Efficiency of Local Government Budgeting.” As-Siyasi: Journal of Constitutional Law 5(1):147–61. doi: 10.24042/as-siyasi.v51.27598.

Gong, Yiwei, Jun Yang, and Xiaojie Shi. 2020. “Towards a Comprehensive Understanding of Digital Transformation in Government: Analysis of Flexibility and Enterprise Architecture.” Government Information Quarterly 37(3):101487. doi: 10.1016/j.giq.2020.101487.

Idil, Adelia, and Huda Alimuddin. 2024. “AI-Based Public Service Transformation: An Analysis OF Algorithmic Bias Risks AND Digital Government Accountability in ASEAN.” Asian Digital Governance Problems 1(2):78–87. doi: 10.71435/685956.

Igirisa, Rommy, Ferdinand Boba Panaha, and Yovan Iristian. 2024. “Algorithmic Transparency and Due Process in Automated Administrative Discretion: A Comparative Regulatory Analysis.” Lex Journal : Kajian Hukum Dan Keadilan 8(2):59–77. doi: 10.25139/LEX.V8I2.12746.

Janssen, Marijn, and Haiko van der Voort. 2020. “Agile and Adaptive Governance in Crisis Response: Lessons from the COVID-19 Pandemic.” International Journal of Information Management 55:102180. doi: 10.1016/j.ijinfomgt.2020.102180.

Katzenbach, Christian, and Lena Ulbricht. 2019. “Algorithmic Governance.” Internet Policy Review 8(4). doi: 10.14763/2019.4.1424.

Kuziemski, Maciej, and Gianluca Misuraca. 2020. “AI Governance in the Public Sector: Three Tales from the Frontiers of Automated Decision-Making in Democratic Settings.” Telecommunications Policy 44(6):101976. doi: 10.1016/j.telpol.2020.101976.

Madan, Rohit, and Mona Ashok. 2023. “AI Adoption and Diffusion in Public Administration: A Systematic Literature Review and Future Research Agenda.” Government Information Quarterly 40(1):101774. doi: 10.1016/j.giq.2022.101774.

Mahroof, Kamran, Vishanth Weerakkody, Zahid Hussain, and Uthayasankar Sivarajah. 2025. “Navigating Power Dynamics in the Public Sector through AI-Driven Algorithmic Decision-Making.” Government Information Quarterly 42(3):102053. doi: 10.1016/j.giq.2025.102053.

Mutai, Noah Cheruiyot, Karim Farag, Lawrence Ibeh, Kaddour Chelabi, Nguyen Manh Cuong, and Olufunke Mercy Popoola. 2025. “AI Driven Fiscal Risk Assessment in the Eurozone: A Machine Learning Approach to Public Debt Vulnerability.” FinTech 4(3):27. doi: 10.3390/fintech4030027.

Nzazi, Boaz N., Jirince K. Biaba, Ibsen G. Bazie, Tasho Tashev, Witesyavwirwa V. Kambale, Vinh Ho Tuong, Kyandoghere Kyamakya, Nathanaël M. Kasoro, and Selain K. Kasereka. 2025. “Artificial Intelligence for Public Expenditure Analysis in Low-Income Countries: Opportunities and Challenges.” Procedia Computer Science 272:261–68. doi: 10.1016/j.procs.2025.10.204.

Pasquale, Frank. 2015. The Black Box Society The Secret Algorithms That Control Money and Information. England: Harvard University Press.

Rizk, Aya, and Ida Lindgren. 2025. “Automated Decision-Making in Public Administration: Changing the Decision Space between Public Officials and Citizens.” Government Information Quarterly 42(3):102061. doi: 10.1016/j.giq.2025.102061.

Roehl, Ulrik B. U., and Morten Balle Hansen. 2024. “Automated, Administrative Decision‐making and Good Governance: Synergies, Trade‐offs, and Limits.” Public Administration Review 84(6):1184–99. doi: 10.1111/puar.13799.

Saldanha, Douglas Morgan Fullin, Cleidson Nogueira Dias, and Siegrid Guillaumon. 2022. “Transparency and Accountability in Digital Public Services: Learning from the Brazilian Cases.” Government Information Quarterly 39(2):101680. doi: 10.1016/j.giq.2022.101680.

Straub, Vincent J., Deborah Morgan, Jonathan Bright, and Helen Margetts. 2023. “Artificial Intelligence in Government: Concepts, Standards, and a Unified Framework.” Government Information Quarterly 40(4):101881. doi: 10.1016/j.giq.2023.101881.

Wang, Yingwei, and Yining Tang. 2026. “Will Embedding Algorithms into Performance Appraisals Influence the Configuration of Organizational Authority? Experimental Evidence from the Public Sector.” International Journal of Information Management 91:103109. doi: 10.1016/j.ijinfomgt.2026.103109.

Wenzelburger, Georg, Pascal D. König, Julia Felfeli, and Anja Achtziger. 2024. “Algorithms in the Public Sector. Why Context Matters.” Public Administration 102(1):40–60. doi: 10.1111/padm.12901.

Wirtz, Bernd W., Jan C. Weyerer, and Carolin Geyer. 2019. “Artificial Intelligence and the Public Sector-Applications and Challenges.” International Journal of Public Administration 42(7):596–615. doi: 10.1080/01900692.2018.1498103.

Yeung, Karen. 2018. “Algorithmic Regulation: A Critical Interrogation.” Regulation & Governance 12(4):505–23. doi: 10.1111/rego.12158.

Zuiderwijk, Anneke, Yu-Che Chen, and Fadi Salem. 2021. “Implications of the Use of Artificial Intelligence in Public Governance: A Systematic Literature Review and a Research Agenda.” Government Information Quarterly 38(3):101577. doi: 10.1016/j.giq.2021.101577.

Digital Fiscal Accountability under Indonesian Administrative Law: A Framework for AI-Driven Regional Budget Governance

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