Budget 2026–27 and IndiaAI: What to watch for if AI is to strengthen state capacity
By Arshi Aadil, Lead Social Protection and Policy, MSC
In a public hospital, the hardest part is often not the treatment itself, but the administrative hurdles around it in the form of paperwork, eligibility checks, approvals, delays, and repeated visits. For citizens, this is what the state feels like in practice: not policy intent, but the ability to deliver services reliably and correct errors quickly. AI can help administrations spot bottlenecks early, route grievances faster, and reduce avoidable delays so delivery improves without reducing accountability. This is not about automating entitlements; it is about strengthening the administrative systems around them. This is why the AI debate in India needs to be anchored in state capacity, not just innovation.
Union Budget 2026–27 is an opportunity to make that shift concrete. India has already signalled intent through the IndiaAI Mission, approved by the Union Cabinet with an outlay of ₹10,372 crore over five years, spanning shared compute, datasets, skilling, applications, and safe and trusted AI. The Budget will now be judged on whether it strengthens this mission in ways that improve real public services and whether it funds the guardrails that prevent predictable harms.
First, watch for continuity in IndiaAI funding and if it is designed for sustained use.
AI systems require reliable shared computing capacity and secure environments for public applications. The clearest signal will be whether allocations support this as an ongoing public capability, not a one-time asset so public-interest deployments can move beyond pilots without duplicating tools across departments. Experience from World Bank supported open digital networks (ONS-style) suggests that shared rails and good data systems matter more than one-off pilots.
Second, watch whether AI is being funded as governance improvement. IndiaAI’s impact will depend on adoption inside large programmes, where administrative delays and grievances accumulate. The Budget can signal seriousness by creating a modest, explicit window for programme-linked deployments and independent evaluation, tying spending to measurable administrative outcomes rather than fragmented demonstrations. A serious AI push in government is ultimately a people-capacity push. Budget 2026–27 will be judged on whether it finances the human capability to deploy and govern these systems, programme managers, data stewards, and evaluation capacity rather than assuming technology alone will improve administrative performance.
Third, watch how IndiaAI will reach the states. Since many flagship welfare programmes run through state departments and district administrations, uneven adoption will translate into uneven outcomes. A key budget expectation is therefore targeted support for state readiness not through state-wise AI handouts, but through funded enablers such as training roles, data stewardship capacity, and procurement standards that embed transparency and auditability. Since state budgets follow soon after the Union Budget, the Centre’s choices on IndiaAI can act as a template for states encouraging them to invest not just in pilots, but in the people, data systems, and evaluation capacity needed to deploy AI responsibly in public programmes.
The Budget’s AI story should be read through outcomes. The strongest signal will be whether IndiaAI funding builds shared capability that departments can actually use, whether adoption is tied to measurable improvements in programme performance, and whether states are equipped to deploy AI transparently and safely. With India’s strong foundations on digital public infrastructure, AI can strengthen public services and expand inclusion but only if guardrails are financed early, from independent evaluation and audits to grievance redress, and human oversight.
If this is done right, IndiaAI can become a durable investment in state capacity, not just another technology push.