This Budget Could Be the Spark Behind India’s AI Power Shift
The Union Budget 2026 arrives at a moment when India’s artificial intelligence ambitions are well-funded and articulated, yet increasingly constrained by execution and policy clarity.
Over the last two years, the government has laid a strong foundation. The approval of the Rs 10,372 crore IndiaAI Mission in March 2024 marked a turning point, positioning AI as core national infrastructure rather than a niche technology play. Since then, access to subsidised compute has expanded rapidly—from an initial target of 10,000 GPUs to over 38,000 GPUs today—while datasets, skilling programmes, foundation models, and safety frameworks have begun taking shape.
Budget 2025 Reinforces AI Direction
Budget 2025 reinforced this direction, with allocations for AI-linked schemes surging. Rs 2,000 crore was earmarked for the IndiaAI Mission in FY26—over a tenfold jump from the previous year’s revised estimates.
- Scheme / Programme
- 2023–24 Actual
- 2024–25 Budget
- 2024–25 Revised
- 2025–26 Budget
- IndiaAI Mission: – Rs 551.75 crore Rs 173.00 crore Rs 2,000.00 crore
A fourth Centre of Excellence for AI, focused on education, was announced with a Rs 500 crore outlay, and overall spending on AI-related programmes crossed Rs 4,300 crore. Yet, as AI moves from pilots to production, industry leaders indicate that the next phase requires less signalling and far more structural reform.
From Ambition to Execution
“India’s data centre and AI infrastructure ecosystem is now constrained less by capital and more by execution,” stated Ankit Saraiya, Director and CEO of Techno Digital. “The Union Budget can play a catalytic role by strengthening execution enablers—particularly power availability, approvals, and long-term policy certainty.”
AI workloads are fundamentally power-hungry. As GPU-led computing expands, data centres are becoming denser, more energy-intensive, and harder to scale without regulatory support. Industry estimates suggest India’s data centre capacity could grow from around 1,450 MW today to over 4,500 MW within five years, largely driven by AI demand.
To make that possible, operators are seeking assured access to competitively priced green power, faster approvals for captive and renewable-linked capacity, dedicated power corridors, relaxed demand charges, and a separate tariff category for data centres. Transmission and distribution bottlenecks are also emerging as a key constraint.
Governance Gap
If infrastructure is one pillar, governance is the other. Despite the enactment of the Digital Personal Data Protection (DPDP) Act and various draft advisories, India lacks a unified AI governance architecture. “AI is still treated primarily as a technology issue rather than a socio-technical governance ecosystem,” notes Manpreet Singh Ahuja, Chief Clients and Alliances Leader at PwC India.
The absence of clarity around liability—who is responsible when an AI system causes harm—has become a major bottleneck, especially in high-risk sectors like healthcare, finance, and mobility. Without defined accountability, enterprises are hesitant to move beyond pilots.
Furthermore, there is no calibrated AI risk framework that distinguishes between low-risk and high-impact use cases. Industry leaders argue that Budget 2026 should push for a clear risk classification system linked to proportionate regulation, rather than a one-size-fits-all approach that could stifle innovation.
Compute Access: Scale Matters
A central theme among stakeholders is the need for compute access. India is currently the world’s third-largest AI talent hub, but domestic GPU capacity meets only a fraction of demand. Industry leaders warn that without large-scale, affordable compute access, India risks exporting its most advanced AI workloads and value creation offshore.
The most impactful step to make India an AI leader is scaling compute access nationwide. Initiatives like the IndiaAI Mission have onboarded 38,000 GPUs, but the next phase must dramatically expand capacity while linking it directly with skilling, research, and industry adoption.
There is broad consensus that subsidies should focus on access, not ownership. The preferred model is compute-as-public-infrastructure: government-funded GPU pools accessed via time-bound, usage-based credits for startups, universities, and research labs. Milestone-linked compute credits and efficiency benchmarks could ensure public money delivers measurable outcomes.
Data, Languages, and Inclusion
India’s AI opportunity extends beyond scale; it encompasses specificity. Much of today’s global AI is English-first, leaving large sections of India underserved. Initiatives like Bhashini and BharatGen AI are addressing this gap, but the industry seeks targeted budgetary support for Indian-language datasets and last-mile use cases in agriculture, healthcare, education, and governance.
The call is for funding linked to real-world deployment, not just academic outputs. This includes sustained investment in high-quality public datasets and incentives for models trained on India-specific data.
Government as Lead Customer
Another recurring demand ahead of Budget 2026 is for the government to act as a lead customer, not just a regulator or funder. Public-sector procurement has traditionally struggled to keep pace with emerging technologies. High entry barriers and risk-averse audits often exclude startups.
Industry leaders argue that preferential procurement for domestic AI firms, outcome-based contracts, and innovation sandboxes could unlock real demand at scale. There is also growing support for deeper AI adoption within government operations—from tax administration to public services.
Capital and Patience
Finally, founders and investors emphasize that India’s AI pipeline still lacks patient, deep-tech capital. Although over 1,000 AI startups raised nearly $2 billion in 2025, the gap between prototype and scale remains wide. Long-horizon funds, risk-sharing mechanisms, and procurement-linked revenue certainty are crucial for startup sustainability.
What Next?
India enters Union Budget 2026 from a position of strength, with a large talent base and rising enterprise adoption. What the industry now asks for is the next leap—faster execution, clearer rules, cheaper and cleaner power, scalable compute, and a government willing to both regulate and consume AI responsibly.
If Budget 2026 can deliver on these fronts, India’s AI narrative could shift decisively from promise to global leadership.
