Integrating Program and Performance Budgeting with Artificial Intelligence Technologies to Improve the Quality of Financial Decision-Making

Abstract

This study examines whether integrating program and performance budgeting (PPB) with artificial intelligence (AI) technologies improves the quality of financial decision-making. PPB links appropriations to programmes, objectives, outputs, outcomes, and performance indicators, whereas AI can strengthen forecasting, anomaly detection, reporting, scenario analysis, and decision support. The proposed model treats integration as an organisational, informational, and analytical capability rather than the mere acquisition of software. Five dimensions constitute the independent variable: data readiness and integration, intelligent analytics, AI-supported financial forecasting, budget-cycle automation, and programme evaluation and intelligent decision support. Financial decision-making quality is assessed through timeliness, accuracy, evidence use, allocation efficiency, expenditure rationalisation, risk detection, traceability, transparency, and responsiveness. A quantitative, cross-sectional, descriptive-analytical design was used with 64 eligible respondents and a 45-item questionnaire. The findings show a strong positive relationship between overall integration and financial decision-making quality, while the integration dimensions overlap substantially. The results support treating integration as a coherent capability bundle while retaining human oversight and accountability.