AI-Enabled Citizen-Centric Platform For Integrating Government And Private Welfare Schemes: A Framework For Digital Inclusion And Efficient Beneficiary Mapping

Abstract

Governments and private organizations introduce numerous welfare programs targeting socio-economic development, yet fragmented information systems, bureaucratic delays, and low citizen awareness hinder their effectiveness. This study proposes a citizen-centric digital framework that integrates government and private welfare schemes into a unified platform powered by artificial intelligence (AI) and machine learning (ML). The platform leverages socio-economic profiling, rule-based eligibility filtering, automated document verification, multilingual accessibility, and AI-enabled grievance redressal to ensure transparent and inclusive service delivery. A prototype mobile application was developed and tested with pilot users, demonstrating improvements in accessibility, beneficiary mapping accuracy, and grievance resolution. Findings reveal that an integrated system enhances transparency, efficiency, and inclusivity, while enabling governments and private stakeholders to monitor welfare distribution in real time. This research contributes a scalable model for digital governance that promotes citizen empowerment, social equity, and data-driven policymaking.