Budget 2026: India puts AI at the core of growth, but execution risks loom

On February 1, Finance Minister Nirmala Sitharaman presented the Union Budget 2026, placing artificial intelligence and digital infrastructure at the core of India’s next growth phase. Framed around three kartavya, the Budget positioned AI not as a standalone sector but as a system-wide productivity layer spanning governance, agriculture, education, employment, and services-led growth.

From incentives for large-scale data centre investments and cloud infrastructure to AI-led platforms like Bharat-VISTAAR in agriculture and a renewed push to embed AI into skilling and employment pathways, the Budget signalled a shift from experimentation to institutionalisation. However, even as policy intent sharpened around compute, talent, and adoption, industry experts flagged execution risks, underpowered funding for IndiaAI, and the absence of a long-term roadmap for frontier AI capabilities.

Post-Budget analysis: AI, infrastructure, and India’s execution challenge

The Union Budget 2026 marks a decisive shift in how India is choosing to engage with artificial intelligence. Instead of announcing a headline sovereign AI fund or a marquee national model, the government has opted for a more structural approach, betting on infrastructure, policy incentives, and sectoral deployment to scale AI across the economy.

Data centres and compute as national infrastructure

One of the most consequential announcements came in the form of long-term tax incentives for cloud and data centre investments, including a 21-year tax holiday extending to 2047 for foreign cloud service providers using Indian data centres to serve global customers.

According to Jameela Sahiba, Associate Director at The Dialogue, the move resolves long-standing tax ambiguities around permanent establishment while sending a clear signal to hyperscalers. She notes that the exemption is likely to catalyse over $70 billion in data centre investments by 2035, while simultaneously enforcing data localisation through mandatory use of Indian data centres for domestic customers. “This harmonises economic incentives with sovereignty imperatives,” she says, adding that lower compute costs and improved reliability could significantly benefit Global Capability Centres, startups, and large enterprises alike.

The Budget also backs this infrastructure push with allocations for semiconductors, electronics components under ISM 2.0, sustainable energy for data centres, and green technologies including carbon capture. Together, these measures position AI not as an isolated policy goal, but as embedded national infrastructure.

A trust-based shift in regulation

From a regulatory standpoint, the Budget reflects a subtle but important tonal change. Rohit Kumar, Founding Partner at The Quantum Hub argues that the focus on compute, semiconductors, and data infrastructure is directionally correct, particularly when paired with tax holidays, customs duty exemptions for critical capital goods, and expanded safe harbour provisions.

“These measures suggest a move toward a more trust-based regulatory regime, where the government places greater faith in businesses rather than defaulting to bad-faith assumptions,” he says. If implemented well, this could reduce litigation, improve investor confidence, and reshape how the state engages with the private sector.

However, Kumar flags a critical gap. “The Budget stops short of addressing sustained R&D funding, private-sector innovation incentives, and long-term access to frontier AI capabilities,” he cautions.

IndiaAI Mission: ambition vs execution

That gap is most visible in the IndiaAI Mission. Despite being envisioned as a ₹10,370 crore, five-year programme to build domestic AI capability and subsidised compute access, execution has lagged.

Kumar points out that of the ₹2,000 crore allocated last year, only about ₹800 crore was spent, while this year’s allocation has been reduced to ₹1,000 crore. “Mid-year signals of expanding the Mission to ₹20,000 crore have instead given way to contraction,” he says, warning that this risks slowing momentum at a critical stage when global AI competition is accelerating.

The absence of a clear scale-up plan has left industry divided between appreciating the infrastructure-first strategy and questioning whether India is under-investing in its own AI backbone.

From infrastructure to institutions

While funding debates continue, policy thinkers argue that Budget 2026 reflects a deeper pivot. Dhruv Garg, Partner at the Indian Governance and Policy Project (IGAP) sees the Education-to-Employment and Enterprise Standing Committee as a signal that India is moving from AI infrastructure to AI institutionalisation.

By formally assessing AI’s impact on jobs and skills, and targeting a 10 percent global services market share by 2047, the government is acknowledging that workforce readiness is now the primary bottleneck. “This is less about subsidies and more about standards,” Garg says, adding that the real test will be how quickly committee recommendations translate into curricula, certifications, and training systems that can keep pace with AI-driven change.

AI at the last mile: Bharat-VISTAAR

Sectoral deployment is another pillar of the Budget’s AI strategy. The launch of Bharat-VISTAAR, a multilingual AI platform integrating AgriStack with ICAR’s agricultural practices, aims to address the long-standing last-mile challenge in Indian agriculture. Garg describes it as a shift from digital to intelligent infrastructure. “When an AI can speak to a farmer in their regional language about crop planning and market intelligence, we are not just digitising agriculture, we are democratising agricultural intelligence,” he says. Adoption in non-English speaking rural India, however, will determine whether the platform delivers real productivity gains.

From an industry lens, M Chockalingam, Director Technology for AI and Frontier Tech at Nasscom, says the Budget positions AI as a cross-sector productivity enabler, moving India from pilots to scaled adoption. “The emphasis on digital public infrastructure supports responsible AI, but success will depend on ecosystem partnerships, talent readiness, and translating intent into operational outcomes,” he notes, particularly for MSMEs and services-led businesses.

Jobs, productivity, and inclusion

The employment implications of this approach are central to the Budget narrative. Kartik Narayan, CEO of Apna.co, views the push for shared compute under the IndiaAI Mission as a sign of policy maturity. “Positioning AI as foundational infrastructure rather than an elite capability can lift worker productivity at scale,” he says, arguing that wider access to compute is critical for building vernacular and locally relevant solutions that address employability gaps.

Similarly, Balasubramanian A, Senior Vice President at TeamLease Services, believes the Budget lays the groundwork for future-ready employment by aligning AI investments with skilling, research, and global trade partnerships.

Betting on infrastructure before models

Notably, the Budget avoids direct competition with global AI model builders. Kartik Mehta, CBO and Head of Asia at Channel Factory, says this is a pragmatic choice.

“India may not yet have a globally dominant AI model, but by focusing on data centres and cloud infrastructure, the government is enabling the ecosystem that models depend on,” he says. The tax holiday for data centre-led cloud services, he adds, strengthens India’s position as a global AI participant rather than a peripheral consumer.

A deliberate pause before bigger announcements

For some experts, the absence of a headline AI fund is strategic rather than accidental. Sourya Banerjee, Associate Director, Public Policy Communications at Jajabor Brand Consultancy argues that the government is treating AI as a productivity layer embedded across sectors, rather than a single labelled line item.

He notes that upcoming announcements, possibly at the AI Action Summit later this month, could fill some of the gaps. “This Budget enables private capital and public deployment first,” he says, suggesting that larger AI-specific moves may be deliberately sequenced.

Taken together, Budget 2026 positions AI as invisible but foundational infrastructure, embedded across policy, platforms, and people rather than packaged as a single flagship programme. The strategy is clear: enable compute, build institutions, and let adoption scale through services, agriculture, and employment.

Whether this approach delivers will now depend less on intent and more on execution, spending efficiency, and the speed at which policy frameworks translate into skills, standards, and scalable AI outcomes on the ground.