AI Sovereignty in Bharat Through Development of AI Hardware, LLM Foundational Model and Data Localization

The global artificial intelligence (AI) race has just begun, and India stands at a critical juncture. While the United States and China currently dominate AI research and development, India possesses distinct advantages that can propel it forward. However, we must act with a sense of urgency and adopt a mission-driven approach to ensure that we do not become a mere technological colony of these global powers. Instead, we must harness our strengths to become a leading AI innovator.

In an era where artificial intelligence (AI) is reshaping economies, governance, and society at large, ensuring AI sovereignty has become a crucial strategic priority for nations. AI sovereignty refers to a nation’s ability to independently develop, deploy, and regulate its AI technologies in alignment with its values, security needs, and legal frameworks. Countries such as China and the United States have already established their foothold in AI with sovereign AI systems like DeepSeek and OpenAI, demonstrating the significance of national control over AI development. For India, a country with a burgeoning digital economy and a vast repository of user data, AI sovereignty is no longer an option but a necessity. This article explores how India can achieve AI sovereignty through the development of a foundational Large Language Model (LLM) and data localization via nuclear-powered mid-size data centers.

India’s Moment in the Global AI Race and Leadership: A Call for Innovation and Sovereignty

Open Source is the way forward, but true AI sovereignty will require more than just software advancements. We must integrate software with cutting-edge computing power and leverage strategic engineering to develop sovereign frontier models. These models must be trained on Indian datasets, ensuring they are free from inherent biases and representative of our diverse linguistic and cultural landscape.

A unique strength of India is its linguistic diversity—22 official languages and hundreds of regional dialects. This presents a compelling case for India to lead in developing multilingual and multimodal foundational AI models. By doing so, we can create AI systems that are more inclusive and reflective of the needs of our vast population, bridging the digital divide and ensuring equitable access to AI-driven services.

As a member of the Quad, India must push for equitable AI governance. The restrictions imposed under the U.S. AI Diffusion Rules on GPUs and high-performance AI chips should not hinder India’s progress. We must advocate for policies that support our AI ambitions and ensure that India is not subjected to unjust controls that could stifle our technological growth.

The urgency of this mission cannot be overstated. AI is not merely an industry—it is the foundation of the future global economy. Owning our AI hardware capabilities is essential in a technology-driven world. Investment in AI hardware will not only create jobs and attract capital but will also trigger a ripple effect of innovation across industries, from healthcare and agriculture to finance and education.

The Need for AI Sovereignty

With AI-driven industries booming, reliance on foreign AI models and cloud computing services raises concerns regarding data privacy, security, and economic dependency. Currently, AI models like OpenAI’s GPT, Google’s Bard, and Meta’s Llama are developed and controlled by tech giants based in the U.S. or China. India, with its massive user base and growing digital economy, must ensure that its data is processed and stored within its borders to safeguard national security and economic interests.

Development of an Indigenous LLM Foundational Model

1. Leveraging India’s Multilingual Data

India’s diverse linguistic landscape provides a unique opportunity to build a multilingual LLM capable of understanding and generating content in several Indian languages. Unlike existing models that primarily focus on English, an indigenous LLM can bridge the digital divide by providing AI-powered services in regional languages.

2. Public-Private Collaboration

Developing a foundational model requires immense computational power and high-quality datasets. A collaborative effort between government agencies, academia, and private enterprises can accelerate progress. Initiatives such as Digital India and the National AI Strategy should be leveraged to promote research, development, and funding for indigenous AI.

3. Open-Source Approach with National Security Measures

To ensure transparency, scalability, and security, an open-source approach with controlled access for government and industry stakeholders should be adopted. This would facilitate innovation while preventing undue foreign influence over critical AI infrastructure.

Data Localization: A Pillar of AI Sovereignty

A key prerequisite for AI sovereignty is data localization, which mandates that data generated within a country’s borders be stored and processed within its jurisdiction. By localizing data, India can ensure greater control over critical information, protect user privacy, and enhance national security. AI models are trained on vast datasets, and unrestricted access to national data by foreign entities could lead to economic and security vulnerabilities. Many nations have already implemented stringent data localization laws to protect their digital assets, and India must follow suit.

The Indian government has taken steps in this direction with policies such as the Personal Data Protection (PDP) Bill and sector-specific regulations requiring local storage of sensitive data. However, full-fledged AI sovereignty demands robust infrastructure to support data localization at scale. This necessitates a significant expansion in India’s data center capabilities, which must be both scalable and energy-efficient.

India’s approach to AI must be nimble, cost-effective, and energy-efficient—following the exemplary model of the Indian Space Research Organisation (ISRO), which has consistently achieved world-class results with limited resources. Our AI innovations must be characterized by the ability to do more with less, leveraging smart engineering, indigenous ingenuity, and frugal innovation.

According to ICRA, India’s data centre capacity is expected to double from 950 MW in FY24 to approximately 2,000 MW by FY27. To put this in perspective, the combined power needs of India’s data centres will soon resemble that of an entire city. India’s central government is looking into nuclear energy and a dedicated grid for data centers. The Power Ministry has previously been asked by the Ministry of Electronics and Information Technology (MeitY) to evaluate the viability of this plan.

The Role of Nuclear-Powered Mid-Size Data Centers

As AI applications grow in complexity, the computing power required for data storage and processing increases exponentially. Traditional data centers consume enormous amounts of electricity, raising concerns about sustainability and energy security. A viable solution for India is the establishment of mid-size data centers powered by nuclear energy, leveraging Small Modular Reactors (SMRs) to meet the increasing demand for AI-driven data processing. SMRs offer several advantages, including a compact footprint, enhanced safety features, and a stable, clean energy supply, making them ideal for AI-centric data centers. Nuclear energy presents a viable, sustainable, and stable solution.

• Reliability: Unlike renewable energy sources that depend on weather conditions, nuclear power provides a continuous, stable energy supply essential for AI and cloud operations.
• Efficiency: Small modular reactors (SMRs) can be deployed in strategic locations to power mid-size data centers, reducing dependency on fossil fuels.
• Cost-Effectiveness: While initial investments are high, nuclear power offers long-term cost savings due to lower operational costs and energy efficiency.

Developing nuclear-powered data centers aligns with India’s commitment to clean energy and reduces dependence on fossil fuels. The Indian government, in collaboration with the Defense Research and Development Organization (DRDO) or ISRO and private-sector partners, can establish SMR-powered data centers under a Public-Private Partnership (PPP) model. Such an initiative would not only bolster AI sovereignty but also create a robust energy infrastructure to support future digital advancements. 

Strategic Benefits for India

1. Enhanced National Security: Localized data storage prevents foreign entities from accessing or exploiting critical information, reducing cybersecurity threats.
2. Economic Growth: A strong AI ecosystem will attract investments, spur innovation, and generate employment in AI research, development, and deployment.
3. Energy Security: Nuclear-powered data centers provide a sustainable and uninterrupted power supply, reducing dependence on unreliable energy sources.
4. Regulatory Autonomy: AI sovereignty enables India to shape AI ethics and governance policies in alignment with national interests rather than adhering to global norms dictated by foreign tech giants.

Achieving AI Sovereignty in India While Avoiding Sovereignty Traps

Artificial intelligence (AI) has emerged as a crucial driver of economic growth, national security, and technological advancement. AI sovereignty, defined as a nation’s ability to independently develop, deploy, and regulate AI technologies, is increasingly becoming a priority for many countries, including India. However, while pursuing AI sovereignty, nations must be cautious of sovereignty traps—scenarios where excessive focus on domestic AI independence leads to unintended consequences such as stifling global cooperation and introducing biases that could compromise security and ethical governance.

Understanding Sovereignty Traps in AI Development

Even countries with abundant resources and access to AI technology must navigate sovereignty traps carefully. A major concern is that governments pushing forward with sovereign AI might risk undermining international collaboration meant to ensure AI is used in a transparent and equitable manner. AI is a global endeavor, and isolating its development within national borders can lead to fragmented technological ecosystems, reducing the safety and reliability of AI models.

A clear example of this risk is when AI systems trained on a local set of values are used for national security or law enforcement. If such systems are not designed with cultural and contextual sensitivity, they may misinterpret behaviors that do not align with local norms as potential threats, leading to biased and unfair decision-making. This issue can create ethical dilemmas and international tensions, making AI sovereignty a double-edged sword.

India’s Standing in AI Strategy and Infrastructure

According to the Tortoise Media Global AI Index 2024, which evaluates government strategies and infrastructure for AI development across different countries, India has made significant progress in its AI strategy. The rankings are based on factors such as the depth of commitment, strategic planning, government spending on AI, and the infrastructure available to execute AI policies. India has demonstrated strong commitment to AI through initiatives such as:

• National AI Strategy (NITI Aayog’s AI for All), which aims to make AI accessible and beneficial for all sectors.
• Increased investments in AI research, including collaboration with academia and private enterprises.
• Emphasis on AI-driven governance, particularly in sectors like healthcare, agriculture, and smart cities.

While India has performed fairly well in developing an AI strategy, its AI infrastructure needs significant improvements in order to become a global leader in AI. This includes:

• Chip Manufacturing: Establishing domestic semiconductor production to reduce reliance on foreign imports.
• Data Centers and Data Localization: Expanding data center capacity and enforcing localized data storage policies to enhance security and computational efficiency.
• Compute Capacity: Investing in high-performance computing resources to support advanced AI research and applications.

Striking a Balance: Sovereign AI with Global Cooperation

India must adopt a balanced approach that fosters AI sovereignty while embracing responsible AI governance and international collaborations. Some key recommendations include:

1. Data Localization with Ethical Oversight: Ensuring AI sovereignty through data localization while maintaining clear ethical guidelines to prevent misuse and overreach.
2. International AI Partnerships: Engaging with global AI consortiums and policy discussions to uphold best practices and standards.
3. Bias-Free AI Development: Training AI models on diverse and unbiased datasets to prevent sovereignty-driven AI discrimination.
4. Transparent AI Regulations: Establishing a regulatory framework that balances national security with fundamental rights and freedoms.

Conclusion

Achieving AI sovereignty in India is not just a technological ambition but a strategic necessity. By developing an indigenous LLM foundational model and localizing data through nuclear-powered mid-size data centers, India can secure its digital future, enhance economic growth, and ensure national security. A well-planned roadmap integrating policy support, infrastructure development, and stakeholder collaboration will pave the way for India to become a global leader in AI.

By prioritizing AI sovereignty, India can safeguard its digital future, strengthen its technological independence, and become a formidable force in the global AI landscape.AI sovereignty is crucial for India’s digital future, but it must be pursued with caution. Avoiding sovereignty traps by maintaining ethical AI standards, fostering international cooperation, and ensuring transparency will help India build a strong and responsible AI ecosystem. As the global AI landscape evolves, India has the opportunity to set an example by demonstrating how sovereign AI can be developed without compromising safety, equity, and collaboration on a global scale.

When future generations look back at the history of AI, this must be the moment when India transitioned from being a service provider to becoming a global AI innovator. The choices we make today will determine whether India becomes a leader in AI or remains dependent on foreign technology. Now is the time to act decisively, invest strategically, and innovate relentlessly. The future of AI must be Indian, and we must seize this opportunity with the urgency and ambition it demands.

(The views expressed are the author's own and do not necessarily reflect the position of the organisation)