New Delhi : India has enrolled over 1.4 billion people in Aadhaar and its Unified Payments Interface (UPI) now processes over 20 billion transactions a month, an estimated 49% share of all real-time payments globally. A new study by the Tony Blair Institute for Global Change (TBI), launched today reveals that the data powering India’s government systems remains in silos across departments and states, creating a gap between India’s digital scale and its ability to use data for informed decision-making better policy formulation and more effective delivery of public services.
Citing the present situation in the country with data, the report notes “Indian states generate enormous volumes of administrative data every day: beneficiary lists, health records, land registers, school enrolments, tax filings. However, these data are collected to satisfy one department’s reporting requirement, not to answer the cross-cutting questions that actually drive policy”. Fixing fragmented government data, rather than building more digital infrastructure, is India’s next challenge and the foundation for any serious AI ambition, for which the report charts out a roadmap through its seven recommendations.
The report, titled “From Digital Scale to Data Power: A Data Operating Model for India’s States,” argues that government data is not an administrative inconvenience but a delivery failure, one that leads to fiscal leakage, exclusion from welfare schemes and weaker public trust, and that will undermine India’s AI ambitions unless addressed first. According to NITI Aayog’s 2025 assessment cited in the report, poor-quality data causes fiscal leakage of an estimated four to seven percent of India’s annual welfare spending. Past clean-up exercises illustrate the scale of the problem: removing 17.1 million ineligible names from the PM-KISAN farmer support scheme saved an estimated ₹90 billion, eliminating 35 million bogus LPG connections saved ₹210 billion over two years, and dropping 16 million fake ration cards is saving roughly ₹100 billion annually.
The paper complements India’s ongoing push for data harmonisation and data-driven governance, spearheaded by the Ministry of Statistics and Programme Implementation (MoSPI). It analyses and builds on key Union government initiatives, including NMDS 2.0, SQAF, the AI-Readiness Framework, the QPR Portal and the Model Data Sharing Framework. It also draws on state-level programmes, including Karnataka’s Kutumba social registry, Odisha’s Social Protection Delivery Platform and Rajasthan’s Pehchan Portal, alongside initiatives in Andhra Pradesh, Uttar Pradesh, Tamil Nadu and Telangana.
Vivek Agarwal, Country Director, Tony Blair Institute for Global Change and co-author of the paper said, “We often talk about what AI can do for the government. This paper asks a more basic question first: is the data good enough to trust an AI system, or a human official, to act on it? Right now, in most states, the honest answer is not yet. That’s not a reason to slow down on AI, it’s a reason to be deliberate about what comes first. States that get this foundation right won’t just be AI-ready, they’ll make better decisions, serve citizens faster, and catch problems before they become crises.”
The report notes that India’s digital infrastructure has scaled further and faster than almost any country’s. Aadhaar has supported more than 24.5 billion e-KYC transactions and helped raise formal banking inclusion from roughly 25% in 2008 to over 80% by 2023, while DigiLocker has issued and verified nearly 10 billion documents for over 685 million citizens. But the report argues that none of this is the same as making that data usable across departments and levels of government, and that without fixing this first, AI deployed on top of fragmented data will simply amplify existing blind spots rather than solve them.
“India’s first digital achievement has been a scale that few countries can match: proving that identity, payments and public systems could reach hundreds of millions of people reliably and fast. The next test is different. It is about whether data can be trusted, connected and used to deliver better outcomes. As the report argues, India has not yet built this capability with the same consistency as its digital infrastructure” said Ott Velsberg, former Government Chief Data Officer of Estonia and co-author of the paper.
To address this, TBI sets out seven recommendations for states, built around what it calls a state data operating model, covering leadership and mandate, data ownership and stewardship, common standards, shared data capabilities, independent quality assurance, legal and procurement safeguards, and a State Data Balance Sheet to help leaders manage data assets and risks the way they manage finances.
States that get this right will not simply end up with better dashboards. They will be better placed to catch problems early, direct resources where they are genuinely needed, and build public trust in the numbers the government publishes. As India moves toward wider AI adoption in governance, that foundation, the report concludes, will determine whether technology strengthens delivery or simply scales up the same blind spots faster.
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