India’s AI Paradox: Why We Need Cloud Sovereignty Before Model Sovereignty

By Amin Habibi, Co-founder, COO-VergeCloud

As India accelerates toward becoming an AI-driven economy, the debate on model sovereignty (owning and controlling indigenous AI models) has gained momentum. All stakeholders, including policymakers, startups and enterprises, are investing in developing Indian Large Language Models (LLMs) and sector-specific AI systems.

However, in the race towards the finish line, it’s important not to overlook a crucial factor- cloud sovereignty. This is because of the simple fact that it is impossible for India to achieve true AI sovereignty without first securing the cloud infrastructure that powers it. If these systems are hosted or managed outside national jurisdiction, model sovereignty becomes symbolic rather than real.

The Infrastructure Beneath AI
AI does not exist in isolation. It is built upon a multi-layered digital foundation—data collection, storage, compute, networking, and deployment. This entire pipeline resides on cloud infrastructure, making it the backbone of any national AI initiative.

Today, much of India’s AI research and enterprise workloads still depend on global hyperscalers. While these platforms provide scalability, they also open up complex debates around data storage, governance and control. Large volumes of sensitive information, from citizen databases to industrial sensor feeds, often move through or get stored on servers located outside India’s borders. Needless to say, this raises questions about strategic and cybersecurity concerns. This is why clear cloud sovereignty is extremely important, and it would serve us well amidst geopolitical or trade tensions.

Why Cloud Sovereignty Comes First
As is clear, cloud sovereignty is the new pillar supporting national security and having control over infrastructure, data, and digital operations. It has the capacity to safeguard the country’s national interests, including (but not limited to) industrial data, citizen information, and AI workloads.

For India, specifically, building a sovereign digital infrastructure guarantees continuity and trust. It gives the country power to enforce its own data laws, manage computing resources for homegrown AI systems, and stay insulated from the tremors of foreign policy decisions or transnational outages. It’s the digital equivalent of producing energy at home—self-reliant, secure, and governed by national priorities. From the physical servers that store information to the applications that power innovation, sovereignty must run through every layer of the system.

Therefore, it is critical that before thinking about owning AI models, we ensure that the platform hosting them is Indian, secure, and sovereign. Without this, systems designed to fuel national growth would remain dependent on foreign infrastructure for their sustenance.

Security at the Core of Sovereignty
Sovereign infrastructure is less a matter of where data sits and more about who controls it and how securely it is managed. With connected systems, AI workloads spread across networks. This makes it imperative for security to be built into every layer and stage.

As systems grow more connected and AI workloads spread across networks, security needs to be built into every layer of technology, not added as an afterthought. That’s where edge computing and modern cloud-security frameworks come in.

Processing data closer to the use points (edge computing) allows companies to achieve faster performance. Lesser reliance on foreign networks and better compliance with Indian policies. At the same time, strong protections ensure AI models, APIs, and datasets stay secure from cyber threats.

The Cost of Neglecting Cloud Sovereignty
There is a real cost involved in neglecting cloud sovereignty. If our AI models continue to depend upon infrastructure that lies outside our jurisdiction, any changes in foreign regulations might suddenly restrict access to critical training datasets. Even occurrences like widespread power outages could halt operations (that depend on automation) within the country. In the worst case, a breach in a shared cloud could expose sensitive information and severely compromise national security.

All the mentioned scenarios are not imaginary risks. They are very real and can impact our digital self-reliance and economic stability. Therefore, a strong and sovereign cloud infrastructure is the need of the hour.

Building a Sovereign AI-Ready Cloud
To achieve this end, India must prioritise three strategic actions:

Build a Nationwide Edge Cloud Fabric: Set up low-latency edge data centres in important areas so AI tasks and data stay within India’s borders.

Integrate Security as a Core Layer: Features such as WAF, Rate Limiting, DDoS Mitigation, and SSL enforcement must be standardised across sovereign cloud providers.

Foster Public–Private Collaboration: Indian cloud companies, AI startups, and government agencies should work together to create secure rules for sharing data, following AI laws, and hosting AI models within India.

The Path Forward
India is at a critical juncture in its growth journey, especially with respect to AI. While technological advancement is essential, it is equally important to acknowledge that this has to rest on a foundation that is secure, sovereign, and independent.

Here is where cloud sovereignty becomes paramount. It is the invisible nervous system of all AI models. Securing it and ensuring complete control over it is key to accord protection to the promise of development. The next decade of India’s digital growth depends on how effectively we can align AI innovation with cloud sovereignty, ensuring that intelligence built in India runs securely in India.