A Comprehensive Study on AI Driven Public Budget Management and Resource Allocation System

Mrs. P. SWETHA¹, SK ADIL²
¹Assistant Professor, Department of Computer Science and Engineering, St. Martin’s Engineering College,
Hyderabad, India mswethacse@smec.ac.in
2Student, Department of Computer Science and Engineering, St. Martin’s Engineering College, Hyderabad, India
shaikadil2390@gmail.com

.Abstract:The Public budgeting and resource allocation are critical components of national development, directly influencing economic stability, social welfare, and regional growth. However, traditional budgeting approaches rely heavily on static data, manual analysis, and bureaucratic decision-making, which often lead to inefficiencies, bias, and unequal distribution of resources. These limitations highlight the need for an intelligent and data-driven system capable of adapting to dynamic socio-economic conditions. This project presents the design and implementation of an AI-driven public budgeting and resource allocation system that aims to enhance transparency, efficiency, and fairness in financial decision-making. The system leverages machine learning techniques and data analytics to process real-time and historical socio-economic indicators such as GDP, population, inflation, and sector demand. By applying predictive modeling and weighted scoring mechanisms, the system generates optimized budget allocation across regions and sectors. In addition to allocation, the system incorporates advanced featuressuch as resource scarcity detection and fraud/anomaly detection to identify irregularities in financial data and ensureaccountability. A user-friendly interface and interactive dashboards enable policymakers and administrators to visualize budget distribution and make informed decisions. The modular architecture supports scalability and future enhancements, including real-time data integration and automated policy recommendations. The proposed system demonstrates how artificial
intelligence can transform traditional governance processes into intelligent, automated, and data-driven frameworks, ultimately contributing to equitable and efficient resource management. Keywords: Artificial Intelligence, Public Budgeting, Resource Allocation, Machine Learning, Data Analytics, Predictive Modeling, Anomaly Detection, Smart Governance, Decision Support Systems.