Need For India’s Sovereign AI Model

Syllabus: GS3/Science and Technology

Context

• The question of whether India should develop its own sovereign, foundational AI model has gained prominence as the world increasingly relies on artificial intelligence for various applications.
  • With global tech giants dominating the AI landscape, the idea of India building its own AI model is both ambitious and strategic.

About

• As artificial intelligence (AI) becomes central to economic and strategic policymaking, nations are racing to establish their leadership in this transformative technology. 
• The rise of AI foundation models — large-scale AI systems trained on massive datasets — has raised concerns over technological dependence, data security, and national sovereignty. 
• While countries like the United States and China have developed their own sovereign AI models, India currently relies on models built by foreign corporations such as OpenAI, Google DeepMind, and Meta.

Understanding a Sovereign AI Model

• A sovereign AI model refers to an AI system developed, trained, and maintained within a country, using its own resources, data, and infrastructure. 
• Unlike AI models built by multinational corporations, a sovereign AI model ensures that control over the data, decision-making processes, and ethical considerations remains in the hands of national stakeholders.

Why Does India Need Its Own Foundational AI Model?

• Data Sovereignty and Security: AI models are heavily dependent on data, and India generates one of the largest pools of digital data in the world.
  • Relying on foreign AI models raises concerns about data privacy, security, and potential misuse. 
  • A homegrown AI model would ensure that India’s sensitive data—ranging from healthcare records to financial transactions—remains within the country.
• Reducing Dependence on Foreign Technology: Currently, India depends on AI systems built by American and Chinese companies.
  • These models operate under the policies and governance frameworks of their home countries, potentially limiting India’s ability to deploy AI in critical areas like defense, governance, and cybersecurity. 
  • Developing an indigenous model would reduce this dependency and allow India to chart its own AI future.
• Alignment with Indian Values and Languages: Existing AI models are primarily trained on English-language datasets and Western-centric perspectives.
  • A sovereign Indian AI model can be designed to support regional languages and cultural contexts, making it more inclusive for India’s diverse population.
  • It can significantly boost AI adoption in rural and non-English-speaking populations.
• Boosting Innovation and Economic Growth: An indigenous AI model could foster a thriving AI ecosystem in India, encouraging startups, academic institutions, and industry collaborations.
  • It would create high-skilled jobs, attract investment, and position India as a global AI hub.
• National Security and Defense Applications: AI is increasingly being used in military applications, intelligence gathering, and cybersecurity.
  • Relying on foreign-built AI models in such domains can pose a significant national security risk. 
  • A sovereign AI model would ensure that India has full control over its defense AI systems.

Challenges in Building a Foundational AI Model in India

• Computational Power and Infrastructure: Training large AI models requires massive computing resources, including high-performance GPUs and TPUs.
  • India’s current supercomputing infrastructure lags behind global AI powerhouses like the US and China.
  • To build a sovereign model, India would need significant investment in data centers, AI chips, and cloud computing.
• Data Scarcity and Quality: While India generates vast amounts of data, much of it is unstructured, fragmented, and not properly labeled for AI training.
  • The country must focus on improving data collection, annotation, and accessibility to develop high-quality AI models.
• Talent and Expertise: India has a strong IT workforce, but expertise in AI research, particularly in training foundational models, is still limited.
  • The country needs to invest in AI education, research institutions, and global collaborations to build a skilled AI workforce.
• High Costs and Investment Requirements: Developing a sovereign AI model requires billions of dollars in funding.
  • The Indian government must work with private sector companies, startups, and academia to secure the necessary investment. 
  • Unlike tech giants such as Google and Microsoft, Indian firms have limited financial capacity to fund large-scale AI projects.
• Regulatory and Ethical Challenges: India must ensure that its AI model adheres to ethical AI principles, including fairness, transparency, and accountability.
  • Clear regulatory frameworks must be established to prevent misuse and bias in AI applications.

What Should India Need To Do?

• Invest in critical foundation models: Building foundational models for critical areas like national security, healthcare, and governance while relying on global models for less sensitive sectors.
  • India’s own foundation models offer unparalleled advantages in cultural representation, data sovereignty, and strategic autonomy.
• Build a DPI For Foundation Model Builders: India should develop datasets, APIs, tools for labelling and curating data, platforms for delivery of services, fine-tuning to a specific context, etc. It should create this as a mission-mode programme.
  • The initiatives of the AI4Bharat Centre at the Wadhwani School of Data Science and Artificial Intelligence (WSAI) demonstrate that a homegrown model can serve India’s multilingual population better. 
  • Sarvam AI has already developed Sarvam 1, India’s first homegrown large multilingual language model, in collaboration with Nvidia.
• Encourage Advanced AI Research & Translation: India needs to focus on physical AI (embodied in robots), as well as neurosymbolic reasoning (rule-based logic to enhance AI’s decisionmaking).
  • Public-private partnerships, international collaborations, and phased investments in AI research could reduce risks while fostering a robust AI ecosystem.
• Develop National AI infrastructure: Under its IndiaAI Mission, the govt is planning to create a high-performance AI computing infrastructure comprising over 10,000 GPUs, high performance computing clusters, secure cloud storage, and scalable AI research hubs.
  • Other nations are already developing their ‘Nextgen AI Factories’ – Denmark, with its Gefion supercomputer, and Japan, through its AI Grid initiative.

Way Forward: A Collaborative Approach

• Government, industry, and academia collaborate to create an open-source Indian AI model, supported by public-private partnerships.
• India partners with global AI research institutions to leverage existing expertise while ensuring its model aligns with national interests.
• The focus is on developing AI models tailored to India’s needs, such as AI for agriculture, healthcare, governance, and linguistic diversity.

Conclusion: A Strategic Necessity

• While building a sovereign AI model presents significant challenges, it is a strategic necessity for India. AI is set to become a key driver of economic growth, national security, and technological innovation. 
• India must act decisively to invest in AI research, infrastructure, and policy frameworks to develop a homegrown AI ecosystem.

Source: TH