A Comprehensive AI-Powered Survey Platform for Streamlining Data Collection, Analytical Power for Smart E-Governance

Abstract

Socio-economic data collection for national policy is undergoing a paradigm shift with the emergence of AI-driven automation and analytical frameworks. Existing statistical systems, such as those managed by the Ministry of Statistics and Programme Implementation (MoSPI) through the National Sample Survey (NSS), often rely on fragmented, manual, and enumerator-driven processes that lack real-time validation and linguistic inclusivity. This survey explores the state of the art in no-code survey generation, qualitative guidelines for software research, and smart e-governance through open data and big data analytics. By analyzing recent developments in data visualization tools and the "Statistics- as-a-Service" (StaaS) framework, this paper presents a unified AI-powered architecture that integrates multi-modal delivery with real-time monitoring and automated response validation. The proposed framework leverages advanced machine learning techniques to process large datasets, identifying patterns that improve decision- making in sectors like health, education, and agriculture. This architecture offers a scalable, trusted, and intelligent approach to modernizing national statistical challenges while supporting the vision of a citizen-centric digital governance ecosystem.