India is emerging as a critical market in the global artificial intelligence shift, not because it leads in building foundational models, but because it is becoming a large-scale testing ground for AI applications. The SenseAI State of AI 2026 report describes India as “not just the largest AI user base globally but fast becoming the AI application factory for the world.”

This positioning is driven by scale. India has over 1.4 billion people, more than 900 million internet users, and handles roughly half of the world’s real-time digital payments through UPI. The combination of high digital adoption and diverse use cases makes it a valuable environment for training and deploying AI systems.

“India combines unmatched scale and diversity… making it one of the most valuable markets not just for user adoption but also to capture usage data for training AI,” the report notes.

Consumer behaviour reinforces this. Around 62% of Indian users already use generative AI for shopping, while 64% rely on it for product research. Adoption cuts across age groups, with millennials leading, followed closely by Gen Z and Gen X.

At the same time, trust levels are unusually high. Nearly 90% of Indians approve of AI, and over 79% accept AI-driven decisions without question, often viewing them as more objective than human judgement. This trust is translating into faster adoption compared to global averages.

Global AI firms have taken note. Companies are offering free premium subscriptions in India to build early user bases and collect multilingual data. The report highlights that India is already the second-largest market for ChatGPT, with more than 100 million weekly users.

An application-first ecosystem takes shape

India’s AI ecosystem is developing differently from the US and China. Instead of focusing on expensive foundational models, most capital and activity are concentrated in applications.

Nearly 80% of AI funding in India is directed towards application-layer companies, while only a small share goes into infrastructure and foundational AI. This is largely a function of capital efficiency and resource constraints. “Applications are not only capital lean, but also where value typically accrues,” the report states.

Startup data reflects this trend. India recorded 164 AI deals in 2025, the highest on record, with total funding rising sharply to $2.5 billion from $0.9 billion the previous year.   Average deal sizes also jumped 2.6 times, indicating larger bets by investors.

The ecosystem itself remains early-stage. About 71% of funding rounds are still at the seed level, while only a small fraction of companies have reached late-stage funding.

More importantly, the type of companies being built is different. Around 75% of startups are focused on AI applications, especially in enterprise SaaS, fintech, healthcare, and infrastructure. These sectors mirror India’s real economy and digital infrastructure, such as UPI and Aadhaar.

“AI in India is application-first, not model-first,” the report notes, adding that founders are embedding AI into workflows rather than building core models.

This approach has led to faster monetisation. Nearly 60% of startups are already generating revenue at early stages, reflecting quicker adoption cycles.

Infrastructure gap remains a constraint

Despite strong demand and startup activity, India still lags in core AI infrastructure. While the country generates about 20% of the world’s data, it holds less than 3% of global data storage capacity.

Closing this gap is now a priority. The report highlights over $200 billion in infrastructure commitments announced at the AI Impact Summit, alongside investments from global tech firms and domestic conglomerates.

“The first time India is building the compute layer,” the report notes, signalling a shift toward long-term capability building.

For now, however, India’s strength lies in applying AI rather than building it from the ground up. The combination of scale, cost efficiency, and rapid adoption positions it as a key execution layer in the global AI stack.