Improving public financial control processes through an artificial intelligence-based risk-oriented digital audit model

Abstract

The article examines the theoretical, methodological and institutional foundations for transforming public financial control and internal audit through artificial intelligence. Uzbekistan's 2026 internal-audit digitalisation agenda is assessed against OECD, IMF, World Bank and IIA materials and recent peer-reviewed research. The literature indicates that technical capability alone is insufficient: data quality, explainability, human oversight, algorithmic bias, privacy and auditor competence are critical. The study proposes an integrated "AI-Risk Control" model linking data integration, anomaly detection, multi-indicator risk scoring, prioritisation of control objects and auditor verification. A set of KPIs, validation criteria and phased implementation steps is developed for practical application.