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India has long been the driving force behind global technology – deepening engineering strength, scaling enterprise platforms, and building the backbone of modern digital operations. Over decades, India has moved from early experimentation to a thriving ecosystem of start-ups, GCCs, and global tech talent.
But AI changes the equation.
It doesn’t just need people. It needs context — an understanding of real-world workflows. It needs infrastructure, capital, and the ability to move from experimentation to deployment at scale. And quietly, over time, India has built many of these capabilities.
The question now isn’t whether India has the potential. The question is — will it lead?
To understand why India is ready now, you have to look back.
In the 1970s, as the West experimented with personal computers, India was just emerging from centuries of colonial rule. Our premier institutes were beginning to establish computer science departments. While the U.S. built the foundations of Silicon Valley, India was taking its first steps in offshoring — laying the groundwork for what would become a global tech services industry.
In the internet era, as American companies created billion-dollar consumer platforms, India’s policymakers focused on enabling industries that could scale within infrastructure constraints. While the U.S. was building Googles and NVIDIAs, we were setting the stage for our own entrepreneurial ecosystem.
In the early 2010s, when nasscom published its first start-up report, India had just 600 start-ups. Today, we have over 32,000. And in the last few years alone, more than USD 65 Bn in venture capital has flowed into Indian start-ups.
The gap in timing was real. But what India built during that time was foundational — an ecosystem of talent, services, digital infrastructure, and policy momentum. What seemed like a delayed start has now become a deep reservoir of capability.
India didn’t get here by accident. It took decades of quiet, deliberate buildup — from telecom towers to fiber highways, from engineering talent to a world-class digital public infrastructure stack. We’re now the second-largest tech talent pool in the world, and the number one for English-speaking digital workers. It’s why even the smallest global firms want to set up GCCs in India. We’re projecting 10,000 of them by 2030.
This is the foundation India stands on today. But the next leap will require a different kind of playbook.
To lead in AI, it helps to understand where value is created.
The first layer is infrastructure — and it’s heavy. AI workloads demand semiconductors, GPUs, and energy-intensive data centers. For context, the largest data center in Nevada consumes more power than the city of Bangalore.
But India knows how to build infrastructure at scale — and make it affordable.
Take the example of Jio and the IPL finals. Over 700 million people streamed the match simultaneously on budget phones, with no lag. That scale was made possible by decades of invisible infrastructure — thousands of miles of fiber, millions of telecom towers, and business models that pushed down the cost of access.
The same playbook is now unfolding in AI.
India has already committed to investing USD 170 Bn into building next-generation data centers over the next five years. Additional capital is flowing into real estate, power, semiconductors, and networking. We’ve built billion-scale infra before — and this time, we’re doing it with AI in mind.
If infrastructure is the base, then the agent layer is where AI becomes tangible. This is where intelligence meets workflows — HR, finance, procurement, manufacturing, clinical ops — and turns into decision-making and automation.
This is the layer India is best positioned to lead.
Why? Because building AI agents isn’t just about writing code. It’s about understanding deeply embedded business processes. And India already has over a million professionals working across complex workflows — not just in back-office functions, but in highly specialized domains.
Take Healthcare’s Revenue Cycle Management (RCM) — a critical and complex process that powers a USD 5 Tn industry in the US. RCM covers patient intake, billing, coding, claims processing, and denials. Even a minor error can lead to millions in downstream revenue leakage.
Over 100,000 people in India work on RCM. One of our customers, MedExpert, set up their RCM center in Chennai with over a thousand employees running these workflows end-to-end. If you’re building an AI agent to transform RCM, there’s no better place than India.
And it doesn’t stop there.
This is not a future India needs to prepare for — it’s a present India is already building.
For all our strengths, India lags in one critical area: the model layer. This is where foundational intelligence is created. And we are underrepresented.
This isn’t because we lack talent. It’s because we fail to retain it. 70% of IIT-JEE toppers today are outside India. When asked why, they didn’t cite money or lifestyle. They pointed to weak research infrastructure.
Our top five universities receive a fraction of the funding that institutions like MIT or Stanford command. In fact, MIT alone receives nearly 10 times the combined research funding of IITs and IISc.
India produces just one-fifth the number of computer science PhDs as the US. Ironically, we are the second-largest source of CS PhDs in the US. We train the best — but we lose them.
Foundational innovation is a flywheel. It needs talent, capital, academic research, and enterprise-grade experimentation. Once it moves, it builds momentum. But getting it started requires force.
Other nations have done this. South Korea, for instance, was below global averages in R&D spend just a few decades ago. Today, it leads with the highest R&D spend as a percentage of GDP, thanks to public policy, academic investment, and corporate partnership.
India is beginning to move.
Entrepreneurs are stepping up too.
The founders of Ashoka University pooled 30% of their net worth to build India’s answer to liberal arts and research. Anand Jain is working on India-specific health datasets for diabetes research. The Mindtree founders are funding advanced AI labs within IISc.
Imagine what’s possible if this becomes the norm.
India needs to create a flywheel for foundational innovation, powered by three pillars: funding, talent, and research. Each one reinforces the other. And the flywheel only spins when all three move in sync.
That sounds steep — until you realize that India’s GCCs and tech services industry will generate USD 1 Tn in cumulative revenue over the next five years. We can find the capital. What we need is intent.
Because AI is not just a business disruptor; It is a lever of national security, economic independence, and global equity. If we embed AI into our digital public infrastructure, we can ensure it remains affordable, accessible, and locally relevant.
More importantly, when India builds, it builds for everyone.
We’ve done it before — with digital payments, with vaccines, with open APIs and satellite launches. And if we get this right, we won’t just build AI for India. We’ll build it for the 8 billion people the rest of the world is likely to leave behind.
India is not playing catch-up anymore. It’s time to lead.
THANK YOU
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