METHODOLOGY FOR ASSESSING THE ECONOMIC EFFICIENCY OF ARTIFICIAL INTELLIGENCE IMPLEMENTATION IN PUBLIC FINANCIAL CONTROL
- Authors
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Lazokat Y. Kadirova
PhD Doctoral Researcher Ministry of Economy and Finance of the Republic of Uzbekistan
Author
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Prof. Kahramon A. Usmonov
Scientific Supervisor Doctor of Economic Sciences
Author
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- Keywords:
- Artificial intelligence; public financial control; economic efficiency; state audit; digital governance; Uzbekistan–2030 Strategy; Digital Uzbekistan–2030; public sector management; AI implementation assessment; financial transparency.
- Abstract
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The digital transformation of public administration has significantly intensified the need for innovative governance instruments capable of improving transparency, accountability, and economic efficiency within public financial control systems. In the Republic of Uzbekistan, the strategic orientation toward digital modernization is legally закреплена in the Presidential Decree No. PF-60 dated October 28, 2022, “On the Development Strategy of New Uzbekistan for 2022–2026 (Uzbekistan–2030)”, as well as in the Presidential Decree No. PF-6079 dated October 5, 2020, approving the “Digital Uzbekistan–2030” Strategy. These нормативные документы emphasize the introduction of advanced digital technologies, including artificial intelligence (AI), into public financial management and control mechanisms. Furthermore, the Law of the Republic of Uzbekistan No. ZRU-669 “On State Audit” (December 23, 2020) establishes principles of transparency, efficiency, and independence in financial oversight, creating an institutional foundation for technological modernization. This study develops a methodological framework for assessing the economic efficiency of artificial intelligence implementation in public financial control, using the Ministry of Economy and Finance of the Republic of Uzbekistan as an empirical reference. The proposed evaluation model integrates financial, organizational, and managerial performance indicators, including cost reduction, labor productivity growth, improvement in risk detection accuracy, and acceleration of decision-making processes. The research applies systemic, comparative, and economic modeling approaches to measure both direct and indirect effects of AI integration. The findings demonstrate that the introduction of AI-based analytical systems may significantly enhance operational efficiency, reduce reliance on manual procedures, and support the transition from retrospective to predictive financial governance. The developed methodology provides practical instruments for policymakers and public managers to evaluate the economic viability and strategic impact of artificial intelligence in state financial control institutions.
- References
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- Published
- 2026-03-02
- Issue
- Vol. 2 No. 2 (2026)
- Section
- Articles
- License
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This work is licensed under a Creative Commons Attribution 4.0 International License.
