TBI Report Highlights Data Fragmentation Challenges for AI in India

A new study by the Tony Blair Institute for Global Change (TBI) highlights significant challenges facing India’s ambitions in artificial intelligence (AI) due to fragmented government data. The report, titled “From Digital Scale to Data Power: A Data Operating Model for India’s States,” emphasizes that data remains siloed across various departments and states, impeding effective decision-making and public service delivery.

The TBI report notes that Indian states generate vast amounts of administrative data daily, including beneficiary lists, health records, land registers, school enrolments, and tax filings. However, this data is often collected for specific departmental needs rather than for comprehensive policy-making. Vivek Agarwal, Country Director at TBI, stated, “Right now, in most states, the honest answer is not yet,” when asked about the trustworthiness of the data available for AI systems or human officials to act upon.

The study identifies poor-quality data as a critical issue, leading to fiscal leakage, exclusion from welfare schemes, and a decline in public trust. According to the NITI Aayog’s 2025 assessment cited in the report, poor data quality could cause a fiscal leakage of between four to seven percent of India’s annual welfare spending. Past clean-up efforts demonstrate the extent of the problem: removing 17.1 million ineligible names from the PM-KISAN farmer support scheme saved approximately ₹90 billion; eliminating 35 million bogus LPG connections saved ₹210 billion over two years; and dropping 16 million fake ration cards is projected to save around ₹100 billion annually.

The report advocates for addressing these data fragmentation issues as a foundational step before advancing AI initiatives. It outlines seven recommendations for states that revolve around a state data operating model. These recommendations include improving leadership and mandate, establishing data ownership and stewardship, creating common standards, and ensuring independent quality assurance.

Despite India’s rapid advancements in digital infrastructure—such as Aadhaar supporting over 24.5 billion electronic Know Your Customer (e-KYC) transactions and increasing formal banking inclusion from approximately 25% in 2008 to over 80% by 2023—the report argues that simply having digital tools is insufficient. Ott Velsberg, former Government Chief Data Officer of Estonia, emphasized that India’s next challenge lies in ensuring that data is trusted, connected, and effectively used to deliver better outcomes.

The TBI report also analyzes ongoing initiatives by the Indian government, including the National Data Management Office (NDMO), the AI-Readiness Framework, and various state-level programs. It cites examples from Karnataka, Odisha, and Rajasthan, which are working toward better data integration and governance.

States that successfully implement these recommendations will not only enhance their data capabilities but also improve resource allocation and public trust in government statistics. The report concludes that without addressing these foundational issues, the deployment of AI may only exacerbate existing inefficiencies rather than resolve them.