The AI Systems Race Runs Through India

Strategic competition is no longer decided by who invents the most advanced technology.
It is decided by who can assemble, finance, and deploy entire systems—at scale, at speed, and over time.

In that contest, India has quietly become the most important proving ground in the world.

Not because India is declaring technological leadership.
Not because it is aligning itself with any bloc.
But because it is doing something far rarer: methodically removing the execution bottlenecks that prevent large-scale technology systems from actually being built.

What is emerging in India is not a single policy success or corporate bet. It is the early formation of a plural, open, and partner-based technology stack—one that integrates global capability with domestic execution, and openness with strategic autonomy.

Trusted Networks With Choice

One of India’s most consequential moves received surprisingly little global attention. After the 2020 border crisis with China, India effectively excluded Huawei from its telecommunications infrastructure—not through sweeping bans or ideological declarations, but through trusted-vendor requirements that barred Huawei from 5G trials and core networks.

The distinction matters.

India strengthened the security of its digital backbone without politicizing every procurement decision and without freezing competition. The space left behind did not remain empty. Samsung Electronics, along with trusted global suppliers such as Ericsson and Nokia, expanded their roles in India’s telecom ecosystem.

The result was not dependency or alignment, but choice—interoperable, standards-based networks built through market participation rather than state command. This is how India advances security while preserving autonomy.

Compute Moves Where Certainty Exists

Infrastructure follows certainty, not rhetoric. India’s decision to offer a multi-decade tax holiday for data centers—extending roughly through 2047— sent a powerful signal: if global workloads are run out of India, India will not tax them away.

That clarity unlocked capital.

“U.S. hyperscalers responded at scale. Amazon Web Services, Google Cloud, Microsoft Azure, and Oracle have committed tens of billions of dollars to Indian cloud regions and AI-ready data-center capacity.”

Each brings a different strength—global scale, AI services, enterprise reach, sovereign and regulated workloads—but together they anchor the cloud layer of India’s emerging AI stack. India is no longer just serving domestic demand; it is positioning itself as a global compute node chosen on economic and operational grounds.

From Compute to Ecosystem

At the center of this build-out sits the compute layer.

NVIDIA has become deeply embedded in India’s AI ecosystem, supporting training and inference workloads across hyperscalers, enterprises, startups, and public-sector initiatives. Its role increasingly extends beyond hardware: NVIDIA has joined India’s multi-billion-dollar deep-tech investment efforts as a technical partner, helping train and mentor emerging AI and semiconductor startups.

This signals something important. India is not being treated as a downstream market, but as a place where the AI ecosystem itself is being built.

Intel, meanwhile, maintains one of its largest global R&D footprints in India and has entered into a strategic partnership with Tata Electronics to explore semiconductor manufacturing, advanced packaging, and AI-PC platforms. This reflects a growing convergence between global technology capability and domestic industrial capacity.

This is not technological autarky. It is capability integration.

AI Beyond the Data Center

AI diffusion at population scale will not occur only in hyperscale data centers. It will occur on devices, at the network edge, and across everyday applications.

Qualcomm plays a critical role here—anchoring mobile AI, 5G standards, and on-device inference that allow AI capabilities to reach hundreds of millions of users. Qualcomm, like NVIDIA, has engaged with U.S. and Indian investors backing long-horizon deep-tech development, reflecting confidence that India’s AI future will be built across the stack, not just in the cloud.

On the applications side, OpenAI has introduced lower-priced offerings in India, reflecting purchasing-power realities and signaling that India is increasingly viewed as a scale market, not merely a source of talent or experimentation.

Indigenous Execution as a Strategic Advantage

Equally important, India is not merely hosting foreign technology. Indigenous firms are increasingly integrated into the stack itself.

India’s global IT services leaders—Tata Consultancy Services, Infosys, Wipro, and HCLTech—act as system integrators, embedding global cloud, AI, and semiconductor platforms into enterprise, government, and consumer applications at scale.

This integration layer is one of India’s quiet strategic advantages. It turns infrastructure into adoption—and helps explain why AI deployment in India is more likely to move beyond pilots into real-world use.

Energy, Capital, and Long-Duration Thinking

AI infrastructure does not run on ambition. It runs on power and capital.

India’s decision to open nuclear power to private investment directly addresses one of the hardest constraints in the AI era: reliable, long-duration baseload energy. At the same time, long-horizon, market-based infrastructure investors have committed substantial capital to India’s data centers, energy platforms, and digital infrastructure.

This reflects confidence not in short-term incentives, but in India’s ability to execute complex systems over decades.

Trade as Architecture, Not Alignment

India’s evolving trade relationships with the European Union and the U.S. should not be read narrowly as tariff negotiations. Modern trade policy increasingly shapes system architecture—standards, supply chains, data flows, and deployment pathways.

India is positioning itself not as a subordinate node in someone else’s system, but as a platform economy—open to partners, resilient to shocks, and capable of preserving policy space.

Sovereignty by Design

Taken together, these choices reflect India’s distinctive approach to digital and AI sovereignty. Rather than binding itself to exclusive alliances or constructing closed national champions, India is preserving strategic autonomy by keeping its technology stack plural, competitive, and partner-based.

Sovereignty, in this model, is not about exclusion.
It is about maintaining choice at scale.

The Strategic Meaning

Strategic competition will be decided not by who declares leadership, but by which systems countries choose to plug into.

India is demonstrating—quietly, pragmatically, and at population scale—that open, market-based systems can compete on execution when they clear bottlenecks, sequence reforms, and integrate global capability with domestic strength.

The outcome is not guaranteed. But the test is underway.

And there may be no more important test of whether open technology systems can scale in the twenty-first century than whether they succeed in India.

Development Impact: The development stakes of the AI systems race are profound: countries that can deploy complete, trusted technology systems will unlock productivity and inclusion, while those that cannot risk falling further behind. India offers a rare, real-world test of how that gap can be closed.

In line with my belief that embracing AI is essential to both personal and national success, this piece was developed with the support of AI tools, though all arguments and conclusions are my own.