Digital Transformation in Government Auditing Using Artificial Intelligence: A Proposed Framework for Enhancing Transparency and Sustainability in Supreme Audit Institutions
DOI:
https://doi.org/10.37375/esj.v9i2.4387Abstract
Abstract
This study examines digital transformation in government auditing by applying artificial intelligence (AI) as a strategic approach to enhancing the role of Supreme Audit Institutions (SAIs) and their capacity to promote transparency, accountability, and sustainability. The study is motivated by rapid changes in the international audit environment, where AI and data analytics have become increasingly important priorities for international and regional audit organizations. At the same time, many SAIs continue to rely, to varying degrees, on traditional auditing methods.
The study aims to analyze the main areas in which AI can be applied in government auditing, including big data analytics, machine learning, natural language processing, and robotic process automation. It also reviews relevant academic literature and previous studies, examines selected international and Arab audit experiences, and develops the Balanced Five-Dimensional Smart Audit Framework. The framework consists of three structural dimensions: technological, institutional/governance, and human/knowledge, complemented by two cross-cutting dimensions: ethics and risk management, and institutional and digital sustainability.
The study adopts a descriptive-analytical approach based on the analysis of eight relevant academic and institutional studies and documents, a review of reports issued by INTOSAI, IDI, and OECD, and an analysis of three audit experiences in Greece, Jordan, and Egypt. The findings indicate that successful smart audit transformation depends not only on technology but also on integrating digital readiness, institutional governance, human capabilities, ethical safeguards, and risk management, while preserving auditors’ professional judgment.
The study also proposes a practical roadmap for gradual transformation, beginning with readiness assessment and pilot projects, followed by institutional expansion and capacity building, and ultimately continuous data-driven auditing
References
المراجع العربية
1. المنظمة العربية للأجهزة العليا للرقابة المالية والمحاسبة (أربوساي). (2025). الذكاء الاصطناعي والتحول الرقمي في الأجهزة العليا للرقابة: نحو نموذج متكامل "الرقابة الذكية المتوازنة". مجلة الرقابة المالية، العدد الخاص.
2. المنظمة العربية للأجهزة العليا للرقابة المالية والمحاسبة (أربوساي). (2025). دور الذكاء الاصطناعي في تطوير أساليب المراجعة في الأجهزة العليا للرقابة. مجلة الرقابة المالية.
3. الهيئة الوطنية لشؤون الإعلام (مصر). (2025). المنظمة العربية للأجهزة العليا للرقابة المالية والمحاسبة (أربوساي).
4. منظمة الإنتوساي - الفرع المصري (الهيئة العامة للرقابة والمحاسبة). (2025). رؤية مصر لرئاسة الإنتوساي: تكامل المراجعة والتنمية.
المراجع الأجنبية:
1. Alonso-Morales, N., Saez-Martín, A., Plata-Díaz, A. M., & Lopez-Hernandez, A. M. (2026). Perception of the benefits of artificial intelligence in public auditing and its impact on technology acceptance: empirical evidence from European regional audit institutions. Journal of Financial Reporting and Accounting, advance online publication. https://doi.org/10.1108/JFRA-09-2025-0719
2. Al Amimi, H. S. (2020). The Future of Public Sector Auditing: Living in Times of Change. International Journal of Government Auditing, 47(2), 4–5.
3. Beckstrom, J. R. (2021). Auditing Machine Learning Algorithms: A White Paper for Public Auditors. INTOSAI Journal.
4. Ceki, B., & Moloi, T. (2025). Technology adoption and digital transformation by supreme audit institutions: a content analysis study. International Journal of Government Auditing / Taylor & Francis.
5. INTOSAI. (2025). INCOSAI XXV Theme II Discussion Paper: The Use of Artificial Intelligence Techniques in Auditing.
6. INTOSAI Development Initiative (IDI). (2023). Understanding the Use of Artificial Intelligence in Public Sector Auditing.
7. INTOSAI Journal. (2025a). Harnessing Real-Time Analytics for Public Accountability: The Digital Evolution of Supreme Audit Institutions.
8. INTOSAI Journal. (2025b). Global Summit 2024: Supreme Audit Institutions' Contribution to Sustainability and Digitalisation.
9. INTOSAI Journal. (2025c). Supreme Audit Institutions and Applying the Value Creation Concept for Taxpayers in a Digital Era.
10. INTOSAI Journal. (2026). The Use of Artificial Intelligence (AI) in the Execution of Audits.
11. OECD. (2024). Governing with Artificial Intelligence: Are Governments Ready? OECD AI Papers, No. 20. https://doi.org/10.1787/26324bc2-en
12. Heyaca, M. E., & Pallotta, A. (2026). The State of Artificial Intelligence in Public Audit: Evidence from Selected Countries and the European Union. OECD Artificial Intelligence Papers, No. 58. https://doi.org/10.1787/f4a6c658-en
13. Kassar, M., & Jizi, M. (2025). Artificial intelligence and robotic process automation in auditing and accounting: a systematic literature review. Journal of Applied Accounting Research, advance online publication. https://doi.org/10.1108/JAAR-05-2024-0175
14. Leocádio, D., Malheiro, L., & Reis, J. (2025). Exploration of audit technologies in public security agencies: Empirical research from Portugal. Journal of Risk and Financial Management, 18(2), 51. https://doi.org/10.3390/jrfm18020051
15. Papapanagiotou, A., & Zachou, C. (2024). AI and Machine Learning in Public Sector Auditing: Perspectives from the Hellenic Court of Audit — A Jurisdictional SAI. ASOSAI Journal.
16. DiMaggio, P. J., & Powell, W. W. (1983). The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields. American Sociological Review, 48(2), 147–160.
17. Jensen, M. C., & Meckling, W. H. (1976). Theory of the firm: Managerial behavior, agency costs and ownership structure. Journal of Financial Economics, 3(4), 305–360.
18. Moore, M. H. (1995). Creating public value: Strategic management in government. Harvard University Press.
19. Tornatzky, L. G., & Fleischer, M. (1990). The processes of technological innovation. Lexington Books
