AI-Driven Public Finance Models for Scaling Inclusive Education in India: A Design-Science Framework for a Developing Economy

Abstract

India has made substantial progress in expanding school access, yet the financing of inclusive education remains constrained by regional inequalities, uneven infrastructure, teacher deployment gaps, fragmented data systems, and weak links between public expenditure and learning outcomes. This article proposes an AI-driven public finance model for scaling inclusive education in India. Using a design-science and policy-analysis approach, the study synthesizes recent evidence from Indian education policy, UDISE+ school statistics, Samagra Shiksha, the National Education Policy 2020, and international research on AI in public financial management, education finance, and algorithmic governance. The proposed model integrates seven functions: education data integration, predictive budget forecasting, equity-weighted resource allocation, HR analytics for teacher deployment, real-time expenditure monitoring, outcome-based evaluation, and responsible AI governance. The framework is designed to support inclusive education for children with disabilities, girls, rural learners, socio-economically disadvantaged groups, and students in under-resourced districts. The article argues that AI should be treated not as a replacement for public decision-making but as a decision-support infrastructure that improves fiscal targeting, transparency, and accountability. The study contributes a context-specific conceptual model for India and offers policy recommendations for ministries, state governments, district education offices, and development partners seeking to align digital public infrastructure with SDG 4 and inclusive growth.