Clearly, AI is fast reshaping our world with a dazzling array of efficiencies and benefits, alongside concerns about the risks and uncertainties involved. While many markets are still debating AI's promise, though, India is already deep in the business of implementation.
I see this shift not only in policy and investment, but in the day-to-day conversations I’m having with founders, enterprises and technology leaders across the country.
It was also reflected at the AI Impact Summit in New Delhi earlier this year, where Ruby Sinha, President of the BRICS Chamber of Commerce & Industry Women Empowerment Vertical, took the stage to talk about how India has moved through the "wow phase" and "how phase" and is now firmly in the "execution and impact phase."
This transformation is particularly attractive for international tech companies thinking about where to design, build, test and scale their next generation of AI products. India is no longer simply a place to hire engineers or outsource development. Increasingly, it’s a market where AI systems can be developed, deployed and proven at scale.
In the 1990s and 2000s, companies like Infosys, Tata Consultancy Services and Wipro didn’t just turn India into a global IT services hub. They embedded Indian talent inside the operations of some of the world's largest corporations, creating a deep pool of engineers adept at working within complex enterprise systems. That foundation did not appear overnight: it took decades to build and is not easily replicated.
And this meant that, by the time AI arrived as a serious industrial force, India already had the tangible elements needed to move quickly: the talent base, delivery muscle and institutional relationships. The next challenge, however, is to build on this solid foundation.
Professor Manan Suri of IIT Delhi recently emphasised this, underlining that the country is moving from its traditional role as an AI services provider towards becoming an AI OEM.
I’m struck by how operational the conversation about AI has become in India. Whether you look at manufacturing, agriculture, financial services or healthcare, instead of AI roadmaps, you see systems that are already running at scale.
India's Aadhaar identity system and UPI payments network, as two good examples, are generating real-world data that are being used to extend credit, personalise services and optimise logistics nationwide.
The physical infrastructure is catching up, too, though it still has its gaps.
As Harish Krishnan, MD of Cisco Systems India, recently noted: "India generates nearly 20% of global data but has only about 4% of data centre capacity."
Capital is flowing in steadily to close this gap, and the government has removed some major tax barriers for hyperscalers to accelerate investment further.
As part of what Ranganath Sadasiva, CTO of Hewlett Packard Enterprise (HPE) India, has called the move “from experimentation to acceleration”, I’m also witnessing a new generation of startups working alongside established companies to introduce India-centric innovations, ranging from voice infrastructure for non-English speakers to sovereign language models and agricultural advisory tools to reach farmers in their local dialect.
Against this backdrop, India has great appeal to international AI firms, partly because the testing environment is unmatched. In my view, a solution that works in India, across its cultural diversity, infrastructure constraints and sheer scale, is one that will travel globally.
India has also shown it can deploy technology nationwide with remarkable speed. Back at the AI Impact Summit, Sunil Gupta, CEO of Yotta Data Services, reflected on how quickly India’s AI ecosystem has evolved, commenting that the scale and speed of progress would have been difficult to imagine just a few years ago.
He pointed to the rapid build-out of domestic compute infrastructure and the emergence of sovereign AI models as evidence of this shift. And he summarised that “Across the stack, India has come a long way.”
Now, the world’s largest population between the ages of 15 and 29 is actively leaning into AI adoption. The appetite for fast, frugal problem-solving remains high. And Indian startups are unafraid to experiment.
This experimentation is producing globally competitive founders, and now the funding ecosystem is available to help them thrive.
In practice, scaling AI systems is often less of a technical challenge and more a question of infrastructure. To support the fast-evolving market, the Indian government is investing heavily in AI programmes and semiconductor development.
Through the IndiaAI Mission, for instance, GPU infrastructure that was once barely accessible to Indian developers is now being made available through government-backed initiatives such as IndiaAI Compute. This enables shared access to GPU infrastructure for startups, researchers and enterprises and supports a growing wave of indigenous model development. And the recent union budget provided an additional $100 million allocation to the IndiaAI Mission, which will catalyse a further wave of cloud and data centre investment amidst broader ecosystem development.
Alongside infrastructure, policymakers are also grappling with the wider implications of responsible AI adoption.
IBM India’s Executive Director, Kishore Balaji, recently stated: “AI pushes the envelope on continuous education and challenges livelihoods, jobs, and earnings as we know it.” But he added: “We need strong public-private partnerships and skill-building programmes at scale so we can prepare the workforce for this future.”
Placing this within the country’s larger ambition, he said: “Ensuring we’re aligned with global frameworks will not only help us make an India for India, but an India for the world.”
For international companies willing to engage early as partners rather than service buyers, the timing has never been better. From what I’m seeing on the ground, this is India’s AI moment.
To discuss the opportunities for your AI business in India, please get in touch with us at contact@intralinkgroup.com