India has launched its decade of AI in earnest, aiming to harness technology across society and the economy. The national IndiaAI Mission was approved in March 2024 with a five-year outlay of ₹10,371.92 crore. In Budget 2025, Finance Minister Sitharaman followed through by earmarking ₹2,000 crore (FY 2025–26) for the Mission. These funds helped exceed initial targets (for example, India provisioned over 38,000 high-end GPUs for AI compute, far above the 10,000 target) and launch new programs (such as a ₹500 crore AI Centre of Excellence in Education). As a result, India has set the stage for AI to touch fields from healthcare to agriculture and governance. Yet experts now warn that sustaining momentum requires continued, targeted support. Economists and industry leaders at recent pre-Budget consultations have explicitly urged tax incentives and policy support for AI and related technologies. Budget 2026 is thus a make-or-break moment to consolidate the gains of the AI Mission and lock in new engines for growth.

Building India’s AI capacity will depend on new investments and incentives. Data centers and cloud infrastructure must expand rapidly to meet demand. Industry analysts note that without large domestic AI datacenters and computing power, India’s AI progress risks remaining “dependent on foreign systems”. To address this, stakeholders want long-term fiscal support. For example, analysts recommend tax holidays or accelerated depreciation for AI datacenter projects, full GST credits on data‐center equipment, and multi-year waivers on import duties for GPUs, TPUs, UPS systems and cooling infrastructure. India’s new Digital Personal Data Protection Act (DPDP) already mandates that sensitive personal and AI-training data be kept within national borders. That makes a strong domestic cloud and edge infrastructure even more critical. The Budget could respond by extending or increasing tax incentives for domestic data centers and “AI-ready” infrastructure, lowering the cost of building and operating them in India.

As AI workloads surge, sustainability must be built in. Analysts warn that a data center boom risks locking India onto a high-carbon path. Budget 2026 could encourage green infrastructure by tying incentives to energy efficiency and renewables. For instance, accelerated depreciation or bonus tax deductions might only apply if a data center achieves a low Power Usage Effectiveness (e.g. PUE ≤1.4) or uses a majority of renewable power. Subordinate measures like concessional loans or interest subventions for adopting water-neutral cooling and solar power can nudge builders towards clean technology without crippling projects financially. In short, the Finance Ministry should craft AI-capital policies that reward efficiency: major tax and investment breaks should come with strict green conditions (renewable energy targets, efficiency benchmarks) to ensure India’s AI backbone is built sustainably.

Infrastructure and Data Access

To power AI at scale, India needs both physical computing capacity and rich data pipelines. Beyond tax breaks, the government can actively subsidize compute resources and data platforms. One promising idea is a national “compute credit” scheme: startups and research labs could receive subsidized GPU/TPU compute hours on domestic infrastructure. This would lower barriers for AI training (avoiding expensive offshore cloud costs) and foster local model development. (Such credit schemes have precedent in cloud sprawl programs abroad.) Another major area is data exchange. The Economic Survey and think tanks emphasize that responsible data sharing – especially of non-personal government data – is key for AI innovation. The Department of Science & Technology and industry bodies have proposed an “India Data Platform” or marketplace to facilitate data pooling. In effect, this would be a common data exchange platform overseen by India’s Digital Data Management Office. It would set standards, metadata and privacy safeguards so that government and private datasets become accessible to AI developers, startups and academia.

India is already building blocks: for example, the Intelligent Urban Data Exchange (IUDX) framework – now formalized as national standard IS 18003 – provides an open, secure platform for sharing city and enterprise data. Budget 2026 could strengthen such initiatives by funding additional data bridges (federating departmental silos), seeding open-data projects, and covering the costs of compliance (e.g. getting datasets and APIs certified to BIS / IUDX norms). This would create a “trusted data commons” across public and private domains. Finance ministry allocations could also support “AI Curation Units” (as proposed in Budget 2025) that curate non-personal data within ministries, ensuring high-value datasets (health statistics, agricultural surveys, geospatial maps, etc.) are cleaned and made available for AI modelling.

Skills, Talent and Research

A core constraint is talent. Industry projections estimate roughly one million AI-skilled jobs in India by the mid-2020s (with significant gaps between supply and demand). IndiaAI’s Future Skills pillar is already funding PhD fellowships and student programs (500 PhDs, 5,000 postgraduates and 8,000 undergraduates supported to date) and setting up labs in Tier-2/3 cities. Budget 2026 should scale this further. For example, the government could double down on skilling by increasing scholarships, university AI chairs and NASSCOM‐like industry-academia bootcamps. New budget lines could subsidize AI courses (in engineering and management schools) and incentivize corporate upskilling partnerships (tax deductions for firms that train Indian employees in AI). Expanding the existing five National Centres of Excellence for Skilling (now established nationwide) is another lever: additional funding can equip these centers with GPUs, labs and curriculum development.

On the R&D front, the mission has launched a Foundation Models pillar to develop India’s own LLMs, selecting a dozen startups for public-private model-building. Budget 2026 should continue this push by funding next-gen research. For instance, special grants or prizes could be set up for open-source Indian models (text, vision, speech) trained on local languages/data. Major universities and IITs should get grants to set up AI research labs and high-performance clusters. The ₹20,000 crore “Technology Innovation Fund” announced at Budget 2025 – partly aimed at deep tech startups – can be augmented or targeted specifically at AI and allied fields. In all, the finance ministry should treat AI as a strategic R&D domain: amplify existing programs (PhDs, labs, industry grants) and consider dedicated budget lines for “AI research grants” similar to DST SERB or DRDO efforts.

For startups, Budget 2026 can build on recent measures. The 2025 budget created a scheme to support AI startups going global (15 Indian startups sent to incubators in France, Israel etc.) and hinted at financing 25 deep-tech AI startups through IndiaAI. Going forward, the government could (a) ensure timely release of these funds, (b) add more rounds, and (c) link them with Startup India benefits (longer tax holidays, easier IP norms). One concrete policy is a matching‐fund or fund‐of‐funds structure: NASSCOM praised the idea of a “Deep Tech Fund of Funds” (seeded by ₹20,000 cr) to attract patient capital. Budget 2026 might allocate additional guarantees or sidecar funding for an AI‐focused deep tech fund, giving institutional investors confidence to pour money into nascent AI ventures. Together, these steps would help keep India’s AI innovators and talent at home, rather than pushing them to move abroad or rely on foreign cloud credits.

Public-Private Partnerships and Global Investments

Big tech is already staking India’s AI future with multi‐billion dollar plays – a trend the budget should leverage. Microsoft announced it will invest $17.5 billion in India from 2026 to build cloud and AI infrastructure, including a new hyperscale data centre region in Hyderabad and expanded datacenters in Chennai and Pune. Notably, Microsoft has doubled its pledge to train 20 million Indians in AI skills by 2030. Google has likewise committed ~$15 billion to an AI data centre hub in Andhra Pradesh. Amazon is on track to invest over $35 billion through 2030 in India (up from its earlier $10–15B plans), focusing on “AI-driven digitization” and tools for small businesses. These private investments promise massive new cloud capacity: Colliers predicts India’s total data center load will more than triple by 2030.

The Budget can complement this by aligning incentives. For instance, the government could offer co-investment or concessional capital for infrastructure projects that partner with these firms (e.g. improving grid connectivity or land development for hyperscale zones). Tax policy should ensure much of the value stays local – for example, by granting benefits only if AI hardware is manufactured or assembled in India, or if a certain portion of jobs are filled by Indian engineers. MSFT’s CEO Satya Nadella frames the challenge well: to “build the infrastructure, skills, and sovereign capabilities needed for India’s AI-first future”. In practice, this means the finance ministry should use Budget 2026 to channel and anchor global AI dollars into India’s economy. That could include, for example, capital expenditure programs for regional data centers in smaller cities (so big firms set up multiple regions) or customs duty exemptions tied to investment commitments (as suggested in industry forums).

Policy, Regulations and the Digital Ecosystem

Beyond money, the Budget can also help shape India’s AI policy ecosystem. The Digital India Act and DPDP regulations are establishing a new data and privacy regime; Budget allocations can ensure these frameworks have teeth. This may involve funding enforcement bodies or compliance infrastructure. Likewise, budget provisions might fund model laws for AI governance (building on MeitY’s recent AI policy guidelines) and ethics oversight. Moreover, the Finance Ministry can smooth the path for AI adoption by mandating government use of AI tools, backing open-source AI in government tech stacks, and linking certain public services budgets to AI-enabled improvements (for instance, in public health diagnostics or smart agriculture services).

Finally, Budget 2026 should signal a long-term vision. The Finance Ministry’s task is to balance fiscal discipline with future growth. But AI’s economic stakes are enormous: experts estimate AI could add $1.7 trillion to India’s GDP by 2035. Given that scale, even modest budgetary measures can be highly cost-effective. The focus must be on catalytic funding – using public money to unlock much larger private investments, skill-building and innovation. In short, India’s Finance Ministry can make Budget 2026 the budget that cements the AI decade, by aligning fiscal policy, incentives and funding with the technology’s strategic promise.

What Budget 2026 Should Deliver for AI

• Raise IndiaAI Mission 2.0 funding: Extend multi-year support with a higher outlay. For example, sanction a second phase of the IndiaAI Mission with increased grants for infrastructure (GPUs, HPC), new Centres of Excellence, and sector-specific AI challenges. Ensure full utilization of past allocations (e.g. the ₹2,000 crore) by timely disbursements.
• Incentivize AI infrastructure: Offer extended tax holidays or accelerated depreciation for data centres and AI hardware projects. Grant GST and customs relief on GPUs, TPUs, microchips, high-end servers and related cooling/power equipment. Tie benefits to performance (e.g. mandated renewable energy use) to promote green datacenters.
• Support domestic compute access: Launch a national Compute Credit program, letting startups and labs use subsidized cloud/GPU hours on India-based platforms. Allocate funds to build and operate large shared AI compute centres (through PPP models if needed).
• Build data exchange platforms: Fund the creation of a unified India Dataset Platform (IDP) for public-private data sharing. Invest in projects like IUDX and NDAP by paying for API creation, data standardization, and security audits. Allocate grants for AI dataset generation (e.g. multilingual corpora, healthcare records, satellite imagery).
• Bolster AI skills and education: Increase scholarships and incentives for AI/ML PhDs and advanced degrees. Expand AI labs and curriculum development in universities and polytechnics. Provide tax benefits or grants to companies that train Indian workers in AI (e.g. MSME subsidies for AI upskilling). Embed AI modules in school and vocational curricula through CBSE/NCERT programs.
• Fund research and startups: Augment R&D spending by extending tax credits or direct grants for AI research. Allocate budget for deep-tech seed funds or matching funds (like the proposed “Deep Tech Fund of Funds”). Continue financing the IndiaAI Foundation Models and Startup initiatives, including support for open-source AI and collaborations with global research centers.
• Encourage adoption and innovation: Earmark funds for AI projects in priority sectors (public health, agriculture, education, smart cities) to drive real-world use-cases. Establish prize competitions or challenges (with government prize money) to spur solutions to national issues (e.g. AI for river cleaning, energy optimization, etc.).
• Tax and policy measures: Clarify and enhance R&D incentives – for example, expand the 150% R&D deduction to AI algorithms and data science projects. Consider a reduced GST rate for approved AI products/services. Improve ease-of-doing-business for AI startups by simplifying tax compliance and customs clearance for tech imports.
• Green AI incentives: As recommended by Deloitte and others, link fiscal benefits to sustainability benchmarks. For instance, grant additional tax relief to AI/data projects that achieve high water recycling or procure 50%+ of power from renewables.
• Facilitate PPP models: Provide matching funds or viability gap funding for large AI infrastructure projects (e.g. setting up cloud data parks in Tier-2 cities). Use budgetary outlays to de-risk private investments in strategic areas (such as semiconductor fabs for AI chips, if announced under Make-in-India).
• Data protection and innovation balance: Allocate resources to implement the DPDP Act and Digital India Act effectively, ensuring personal data privacy while not stifling innovation. Fund compliance bodies and certification programs that let startups build AI on public data safely.

Each of these measures should be framed to unlock private investment. As Deloitte observes, new budgetary support for emerging sectors like AI is crucial. By coupling fiscal incentives with policy clarity and funding for public datasets and talent, India can ensure that Budget 2026 supercharges its AI ecosystem rather than leaving it to chance.

Budget 2026 must reinforce India’s AI trajectory. The government has already shown bold intent – tripling the AI mission budget and launching new CoEs in 2025. Now the Finance Ministry can deliver on that vision by plugging gaps in infrastructure, data, skills and incentives. With big tech firms pouring billions into India’s AI future, even a relatively modest share of public funding can have multiplicative impact. By enacting the recommendations above, India’s next budget will not only accelerate “AI for All” but also help build the foundation of a Viksit Bharat 2047, powered by homegrown AI innovation.