From pilots to production

Bhawna Agarwal, MD of HPE India, outlines the critical roadmap for India’s AI growth, projected to add $1 trillion to the economy by 2035.

Written by Guest

February 15, 2026 21:27 IST

Bhawna Agarwal, SVP & MD, HPE India

By Bhawna Agarwal

Artificial intelligence is no longer a future concept in India. It is already shaping how businesses operate, how services are delivered, and how decisions are made. India’s AI market is expected to grow 2.5 times to reach $20-22 billion by 2027, and by 2035, AI could add nearly $1 trillion to the economy. The debate, therefore, is no longer about whether AI matters. It is about whether India is ready to support this growth at scale.

AI does not scale on ideas alone. It relies on physical infrastructure, such as data centres, computing power, networks, and energy, that enable models to be trained and deployed reliably. Despite generating nearly 20% of the world’s data, India hosts only about 3% of global data centre capacity. In practical terms, India is producing vast amounts of data, but much of the infrastructure needed to process it at scale still sits elsewhere. This is where ambition begins to meet reality.

India’s AI ecosystem is moving quickly. Cloud adoption is rising, global technology companies are investing in data centres, and the country is now home to more than 1,300 AI companies. The data centre sector has expanded 2.5 times in the past five years and attracted over $60 billion in investment since 2019, signalling strong market confidence.

Turning momentum into platforms

This gap between innovation and infrastructure is where policy begins to matter. Market forces alone cannot convert ambition into scale and require shared platforms and long-term capacity that individual firms cannot build on their own. The IndiaAI Mission, backed by a Cabinet-approved outlay of over Rs 10,300 crore, represents a deliberate shift in this direction.

Implemented through IndiaAI, the mission integrates shared compute capacity, indigenous model development, national datasets, application deployment, skilling, startup financing, and responsible AI frameworks, creating a full-stack national AI pipeline. Under the mission, shared compute capacity is being expanded to over 34,000 GPUs through public-private partnerships. By lowering the cost of access to high-performance computing, India is treating AI as common infrastructure rather than a privileged resource, enabling innovation to move from isolated experiments to system-level capability.

The real payoff of better infrastructure lies in what it allows India to aim for next. When compute and networks are widely available, companies can move from pilots to production faster. MSMEs can adopt AI tools that were once limited to large firms. Healthcare systems can deploy decision-support tools closer to patients, while agriculture can benefit from real-time, localised intelligence. At scale, this is how AI shifts from isolated use cases to a driver of economy-wide productivity and competitiveness.

Who controls this intelligence?

Infrastructure choices increasingly shape sovereignty. AI is often compared to the new oil, but value is created at refinement. When compute, data, and models are controlled elsewhere, countries risk becoming consumers rather than creators of intelligence. Major economies, including India, are building domestic AI capabilities to reduce foreign technology dependence, secure digital infrastructure, and strengthen economic and national resilience.

Through investments such as shared compute capacity, platforms like AIKosh, and indigenous language models, India is beginning to operationalise this vision. Anchored by the IndiaAI Mission, this approach seeks to democratise access to AI infrastructure, improve data availability, cultivate indigenous capabilities, and embed ethical and legal guardrails alongside technology, a techno-legal pathway to moving India from a large AI consumer to a serious AI creator.

Building for what comes next

Scale, however, must be matched with responsibility. AI infrastructure is energy-intensive, and demand will rise sharply. India’s growing renewable energy capacity offers a chance to build greener, more efficient data centres, while embedding security, privacy, and responsible AI practices early will be critical to building trust.