A robust platform: Mospi's latest initiative will strengthen governance

Mospi's proposed AI-powered Common Data Platform could unify official statistics, improve policymaking and lay the foundation for an India-specific statistical LLM

The Ministry of Statistics and Programme Implementation (Mospi) is planning to build a first-of-its-kind common data platform (CDP) and eventually a dedicated large-language model (LLM), powered by artificial intelligence (AI), for official statistics by integrating nearly 300 official datasets from across ministries and the National Accounts Division into a single trusted platform. The plan must be welcomed because it will improve access to India’s core statistical data under one unified digital umbrella. This platform will replace fragmented portable document formats (PDFs) and spreadsheets with AI-enabled, multilingual and searchable data, making it useful for policymakers, researchers and businesses. The initiative complements recent reforms such as Mospi’s AI-readable eSankhyiki portal and its road map for harmonising administrative datasets. A harmonised data ecosystem can connect information that currently resides in departmental silos, enabling interoperability, improving data discovery, and supporting advanced analytics. More importantly, it can strengthen evidence-based and citizen-centric policymaking by allowing governments to monitor programmes in near real time, identify implementation gaps, reduce duplication, and generate more reliable insights from linked administrative datasets. Easily available data will also help businesses in terms of planning and executing various strategies and investments. 

The proposed CDP architecture mirrors emerging international practice. Countries such as the United Kingdom, the Netherlands, Finland, Canada and Singapore are using a combination of LLMs to retrieve information from verified official databases over a dedicated statistical-language model. However, the success of the proposed LLM will depend on the quality of the underlying data as they retrieve and synthesise information from existing datasets. If datasets remain fragmented, inconsistent or poorly documented, AI will merely reproduce existing shortcomings at greater speed and scale. Administrative data continues to be maintained in incompatible formats, often without common metadata, standardised classifications or unique identifiers, limiting interoperability across departments. These technical gaps are compounded by shortages of skilled data-management professionals, inconsistent conceptual definitions, and an institutional cautious approach to data sharing across agencies because of governance and compliance concerns. 

The government’s implementation road map rightly recognises that data harmonisation must precede AI deployment. Priority should, therefore, be given to data cleansing, structural standardisation and consolidation into a centralised and trusted repository. Equally important is the establishment of data-strategy units (DSUs) in all departments to ensure coordination, accountability, and sustained oversight of data-governance processes. Alongside this, mandatory metadata standards, unified classifications, and common identifiers must be enforced through formal government directives to ensure uniformity in data collection and usage practices across the system. Investment in the capacity-building and  training of data staff will be critical for enabling this transition. At the same time, secure data-sharing frameworks based on role-based access controls, audit trails, and privacy-by-design principles must be institutionalised to build trust and enable safe data exchange. 

Ultimately, the CDP should be viewed not merely as a technological upgrade but as a structural shift in India’s statistical governance. Mospi, to its credit, has updated various data series and made them more robust in recent months. If the latest initiative is supported by strong institutional mechanisms, sustained capacity building, and enforceable standards, it will have the potential to transform India’s fragmented statistical architecture into a unified, intelligent, and AI-ready system.