India's Race to Become the World's AI Inferencing Capital

Can India Become the World’s AI Inferencing Capital?

India’s AI market reached USD 22.85 billion in 2025, making it the second-largest in Asia-Pacific behind China, and is projected to grow to between USD 150 billion and USD 200 billion by 2030 at a CAGR of 25–38% (Spherical/Grand View Research). 92% of Indian employees regularly use GenAI at work (BCG survey, July 2025), the highest in Asia Pacific. The country’s ambition, articulated by Prime Minister Modi and reinforced by government policy, is to position India as the global hub for AI model deployment and inferencing — not necessarily building the largest foundation models, but running them at scale for the world.

That ambition is backed by structural advantages: 2.6 million STEM graduates annually (the second-largest globally),the world’s largest young workforce, and an IT services sector that already commands significant global market share. India ranked second globally in active AI researchers and produces 9.2% of global AI research publications, according to the Stanford HAI AI Index 2025.

What Is the IndiaAI Mission and How Is It Democratising AI Access?

The IndiaAI Mission, the government’s flagship AI programme, has deployed 40,000 subsidised GPUs accessible at USD 0.71 per hour — among the lowest rates globally for research-grade AI compute. This pricing is specifically designed to make AI development accessible to startups, universities, and smaller enterprises that cannot afford commercial cloud GPU rates. India’s total AI compute capacity stands at an estimated 40,000 GPUs through the IndiaAI programme, with approximately 1,450 MW of data centre capacity in operation as of 2024.

The programme operates alongside India’s broader digital infrastructure stack: the India Stack (Aadhaar, UPI, DigiLocker) has created what is arguably the world’s most comprehensive digital identity and payments foundation. UPI processed about 19.6 billion transactions in September 2025 and 24.07 billion in September 2026, after a record 24.51 billion in August 2026 (NPCI), generating enormous volumes of financial data that feed AI applications in credit scoring, fraud detection, and financial inclusion. India’s 5G penetration reached 23.1% in 2024, with aggressive rollout continuing through state-owned and private carriers.

Cloud spending in India has been accelerating rapidly, with AWS alone committing USD 8.4 billion to Indian cloud infrastructure. Total cloud investment commitments exceed USD 15 billion across hyperscalers, positioning India as one of the fastest-growing cloud markets globally. The combination of subsidised compute and hyperscaler investment gives India a dual-track infrastructure strategy unmatched in other emerging AI markets.

WhoAre India’s AI Champions?

Krutrim, founded by Ola CEO Bhavish Aggarwal, became India’s first AI unicorn in January 2024 with a valuation exceeding USD 1 billion. Krutrim-2, its flagship model, is a 12-billion-parameter language model trained on 22 Indian languages — a critical capability in a country with 22 official languages and hundreds of dialects. The model achieves a 0.95 sentiment analysis score versus 0.70 for competing models, an 80% code generation success rate, and a grammar correction score of 0.98. In February 2025,Krutrim open-sourced all models, positioning the platform as the default Indian-language AI stack.

Krutrim Cloud provides GPU-as-a-service with all data stored in India, addressing the data Sovereign AIrequirements that are increasingly important for government and enterprise clients. The company faces competition from Sarvam AI, the government-selected sovereign LLM provider with access to 4,000 H100 GPUs, and from Reliance Jio, which announced a Rs 10 lakh crore (about USD 110 billion) AI commitment over seven years in February 2026 — by far the largest private AI investment in Indian history.

India’s IT services giants — TCS, Infosys, Wipro, and HCL — are also pivoting to AI-first strategies, leveraging their existing enterprise relationships to deploy AI across global clients. This services-led AI deployment model is uniquely Indian and could prove to be the country’s most significant AI export.

What Are the Barriers to India’s AI Ambitions?

Despite its strengths, India faces an 82% AI talent shortage rate for AI-specific roles — the highest in Asia. The gap between India’s large STEM graduate pool and the specialised AI skills required by industry remains significant. Many of India’s best AI researchers are drawn to higher-paying opportunities in the US and Europe, creating a brain drain that undermines domestic capacity building.

Infrastructure constraints persist. India’s AI diffusion rate stands at 15.7% (H2 2025), lower than China (16.3%), Japan (19.1%), and Singapore (60.9%). Power availability for data centres is improving but remains inconsistent outside major metros. The country’s GPU access, while subsidised, is still modest compared to China’s 788 intelligent EFLOPS or even Singapore’s 20 PetaFLOPS national compute capacity.

India’s AI market trajectory to 2030 depends on execution across three fronts: infrastructure scaling, talent retention, and the ability to translate its massive digital user base into commercially viable AI applications. The foundations are in place, but the competition — from China, Southeast Asia, and the Gulf states — is intensifying.

See our coverage of digital payments in Southeast Asia for a comparison of fintech-AI convergence across Asian markets.

Read the full AI in Asia 2026 report — market data, country analysis, company profiles, investment landscape, and 2026–2030 outlook → digitalinasia.com/reports

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Data sourced from the Digital in Asia “AI in Asia 2026” report. Last updated: March 2026.

Read more: the Asian AI chip race and Asia’s AI market in 2026 country-by-country

India’s Race to Become the World’s AI Inferencing Capital