Budget Frames AI as Cross-Sector Growth Enabler

India’s Union Budget for 2026–27 places artificial intelligence (AI) at the center of its growth strategy, linking technology adoption to productivity, governance and workforce transition as the government targets about 7% economic growth and a fiscal deficit of 4.3% of gross domestic product (GDP).

Presenting the budget in Parliament, Finance Minister Nirmala Sitharaman said that “cutting-edge technologies, including AI applications, can serve as force multipliers for better governance.

The budget is structured around three Kartavya priorities of growth, capacity-building and inclusion, with emerging technologies positioned as tools to lift efficiency across sectors such as agriculture, healthcare, manufacturing, financial services and public administration.

Spending priorities reflect that focus. The Ministry of Electronics and Information Technology, which oversees the government’s AI and semiconductor programs, has been allocated ₹21,632 crore for 2026–27.

Budget documents show a tilt toward central sector schemes linked to semiconductor manufacturing, the IndiaAI Mission and electronics component production, underscoring the government’s intent to strengthen domestic technology capacity.

AI Infrastructure

Compute infrastructure and manufacturing form a key plank of the AI push.

Sitharaman announced the launch of India Semiconductor Mission 2.0, saying it will “produce equipment and materials, design full-stack Indian IP, and fortify supply chains,” while also focusing on “industry-led research and training centers to develop technology and skilled workforce.”

The government also expanded support for electronics manufacturing that underpins AI systems. Referring to the Electronics Components Manufacturing Scheme, Sitharaman said, “The Electronics Components Manufacturing Scheme, launched in April 2025 with an outlay of ₹22,919 crore, already has investment commitments at double the target.” She added, “We propose to increase the outlay to ₹40,000 crore to capitalize on the momentum.”

Cloud and data center capacity is another element of the strategy. Budget proposals include long-term tax incentives for foreign companies setting up data centers in India, with benefits extending until 2047 if services are provided through Indian entities, a move aimed at anchoring compute-intensive AI workloads domestically.

AI use cases

The budget also outlines applied AI use cases, particularly in agriculture. Sitharaman proposed Bharat-VISTAAR, describing it as “a multilingual AI tool” that will integrate AgriStack portals and Indian Council of Agricultural Research packages to provide region-specific guidance on crop planning, weather, pest management and market trends in local languages.

Artificial intelligence features in social and assistive technologies as well. Under the Divyang Sahara Yojana, the finance minister proposed support to scale up production of assistive devices, including investments in “R&D and AI integration,” alongside expanded access through retail-style assistive technology centers.

The workforce impact of AI received explicit attention. Sitharaman announced a High-Powered Education to Employment and Enterprise Standing Committee, saying it will “assess the impact of emerging technologies, including AI, on jobs and skill requirements” and recommend corrective measures. 

The budget reiterated technology adoption should be inclusive, referencing women in STEM, youth seeking to upskill and Divyangjan accessing assistive technologies.

Industry responses welcomed the direction while cautioning on execution.

Srikanth Velamakanni, co-founder and group chief executive of Fractal, an enterprise AI and analytics firm, said, “The government clearly sees AI as a catalyst for growth in the federal Budget 2026–27.” 

He added, “The focus on hardware production, data centers, skills and AI use cases in sectors such as agriculture and healthcare is evident, but questions remain on how India will build global competence and leadership in AI.”

Nakul Kundra, chief executive officer and co-founder of Devnagri, a language AI and localization startup, said, “The emphasis on applied technology adoption, including multilingual platforms like Bharat Vistar, signals intent to integrate AI at scale.”

He added, “The outcomes will depend on lowering compute costs, expanding domestic data center capacity and building high quality Indian datasets anchored in consent and trust.”

Krupesh Bhat, founder and chief executive of Melento (formerly SignDesk), a collaborative intelligence platform, said, “The focus on subsidized compute, deeper deep tech funding and clearer policy signals addresses a key bottleneck after experimentation.” He added, “Many AI initiatives struggle not due to lack of ideas, but because production remains expensive and fragmented.”

Talent development was another recurring theme. Abhimanyu Saxena, co-founder of Scaler, said, “India’s success in the AI era will depend as much on people as on technology.” 

He added, “Embedding technology-first thinking early in education and aligning industry, academia and policy will be essential to building long-term, future-ready talent.”