Don’t Bet on an AI Trickle-Down

UPSC Syllabus: Gs Paper 3- Indian economy and Infrastructure

Introduction

Artificial Intelligence (AI) is no longer following the traditional path where advanced technologies gradually become accessible to everyone. Instead, AI is emerging as a strategic asset shaped by geopolitics, export controls, and selective access. Since AI capabilities improve rapidly, delays in obtaining frontier technologies can create lasting technological gaps. India has made a credible beginning, but securing long-term AI sovereignty will require stronger domestic capabilities and carefully balanced international partnerships.

Why AI is Becoming a Geopolitical Weapon

1. AI Changes the Nature of Strategic Competition: AI is not just another technology. It is a general-purpose technology that strengthens innovation, economic growth, defence, and decision-making across many sectors.
2. Control Over AI Creates Strategic Advantage: Countries leading in frontier AI have strong incentives to restrict access instead of allowing technology to spread freely. This helps them maintain their technological advantage.
3. Interdependence is Becoming a Tool of Power: Modern countries increasingly use economic and technological dependence as strategic leverage instead of treating it as mutual cooperation.
4. Earlier Examples Show the Same Trend: Countries have increasingly used strategic resources as geopolitical tools. This was seen during COVID-19 vaccine nationalism, disruptions around the Strait of Hormuz, and export controls on critical minerals and rare earths.
5. Self-Reinforcing AI Advantage: Frontier AI improves by learning from its own outputs. This allows leading countries to widen their technological lead much faster than in earlier technologies.
6. Rapid AI Progress Reduces the Value of Waiting: AI capability improves within months rather than decades. Waiting for technology to naturally become cheaper may leave countries permanently behind.
7. Technology Trickle-Down Cannot Be Assumed: The belief that advanced technologies will automatically become available over time is becoming less reliable as strategic competition grows.

How the US is Restricting Access to Frontier AI

1. Export Controls Extend Beyond Chips: The 2025 AI Diffusion Framework placed restrictions not only on advanced chips but also on AI model weights, bringing frontier AI under export controls.
2. Access is Becoming Country-Specific: Although some rules later became more flexible, access is now decided through country-by-country discretion, keeping strategic control intact.
3. Temporary Model Suspension Showed Real Risks: Washington directed Anthropic to suspend access to its advanced Mythos and Fable models for users outside the United States. Although access resumed from July 1, it demonstrated how quickly access can be withdrawn.
4. Trusted Partnership Determines Availability: At the G7, frontier AI models were presented as technologies reserved for trusted partners, making access dependent on political relationships.
5. AI Access is Becoming a Strategic Privilege: Frontier AI is no longer available simply through market demand. Governments can extend or withdraw access based on strategic interests.
6. Control Now Covers Both Hardware and Software: Restrictions increasingly apply to both advanced computing hardware and the AI models built on that hardware, strengthening technological control.
7. Market Forces Alone Cannot Guarantee Access: Commercial demand is becoming less important than geopolitical considerations in determining who receives frontier AI technologies.

India’s Strategic Dilemma in the Emerging AI Order

1. India is Not at the Frontier of AI Development: Like Europe, India does not currently possess frontier AI capabilities and remains dependent on access provided by leading AI powers.
2. China Offers an Alternative AI Ecosystem: China is promoting open-weight AI models that are cheaper and easier to adopt, creating a strong commercial attraction for many countries.
3. Strategic Dependence Creates New Risks: Relying on foreign AI systems raises concerns about data sovereignty, security, and long-term strategic dependence.
4. India Faces Pressure From Both Major Powers: India risks being restricted by the United States in accessing frontier AI while becoming increasingly dependent on Chinese AI ecosystems.
5. Commercial Contracts Cannot Remove Geopolitical Risks: Businesses can manage commercial risks, but they cannot protect themselves when governments impose strategic restrictions on AI technologies.
6. Limited Domestic Frontier Capability Increases Dependence: India still relies on foreign frontier AI systems because developing such models requires enormous computing power and sustained investment.
7. Research Investment Remains Limited: India spends only about 0.6–0.65% of GDP on research and development, with the private sector contributing only about one-third of this spending, limiting frontier AI development.
8. India Cannot Win Through Spending Alone: The projected $50 billion compute spending of OpenAI is more than six times India’s annual private R&D spending. India therefore needs strategic partnerships along with stronger domestic capabilities instead of trying to match global leaders financially.

India’s Existing Strengths and Ongoing Initiatives

1. Demographic Advantage: India has the world’s largest population, a median age below 30, and one of the world’s largest software talent pools. These strengths provide a strong foundation for AI development.
2. Hard Infrastructure is Equally Important: India’s talent must be supported by advanced semiconductors, reliable electricity, data centres, patient risk capital and strong university-industry linkages to build frontier AI.
3. Dependence on Imported Technology: India still imports advanced chips instead of manufacturing them domestically. This limits its ability to develop frontier AI independently.
4. IndiaAI Mission: The IndiaAI Mission has created a shared national compute facility with more than 34,000 GPUs and is expanding further through support for startups and universities.
5. Progress in Indian Language AI: At the India AI Impact Summit, organisations such as Sarvam released competitive open AI models designed for Indian languages, improving AI accessibility and local relevance.
6. Growing AI Talent Base: India is the second-largest employer of enterprise AI talent globally, with over 250,000 AI/ML professionals working in Global Capability Centres (GCCs), strengthening its long-term AI ecosystem.

What India Must Do to Achieve AI Sovereignty

1. Prepare for AI Supply Disruptions: India should prepare for a future where advanced AI models or chips may become unavailable because of geopolitical decisions rather than market forces.
2. Secure Long-Term AI Access: India should seek binding guarantees for access to advanced compute and frontier AI models instead of relying on temporary political goodwill.
3. Diversify Strategic Partnerships: Stronger cooperation with Europe and other middle powers can reduce excessive dependence on a single AI ecosystem.
4. Build Domestic Semiconductor Capacity: Faster development of semiconductor manufacturing will reduce India’s dependence on imported silicon and strengthen technological sovereignty.
5. Expand Compute Infrastructure: India should accelerate investment in reliable electricity, data centres, and high-performance computing infrastructure needed for frontier AI.
6. Strengthen Research and Innovation: Greater investment in universities, research institutions, talent development, and patient capital is essential because frontier AI requires long-term scientific capability.
7. Reduce Strategic Dependence: India should steadily reduce dependence on foreign AI technologies while remaining connected to global innovation and technology networks.
8. Promote Open AI Models: Open models can reduce reliance on foreign APIs, lower costs, improve transparency, and better support Indian languages and local applications.
9. Develop Sovereign AI Infrastructure: India should build the capacity to host and operate large language models within the country to improve strategic control and technical expertise.
10. Balance Globalisation with Industrial Policy: International partnerships and domestic industrial policies should complement each other. Both are necessary to build a resilient AI ecosystem.
11. Learn from Other Sectors: India’s continued dependence on imported pharmaceutical ingredients despite domestic incentives shows that industrial policy builds capability over time but cannot provide immediate strategic resilience.
12. Act Within the Closing Opportunity Window: AI leadership is built through continuous investment over many years. Delaying action today could make catching up much harder as technological advantages grow rapidly.

Conclusion

The global AI landscape is shifting from technology diffusion to strategic control. India possesses talent, growing capabilities, and a credible foundation, but these advantages must translate into technological self-reliance. Timely investment in research, infrastructure, and trusted partnerships will determine whether India becomes a frontier AI developer or remains dependent on external technological powers.

Question for practice:

Examine the emerging geopolitical challenges in the global AI landscape and discuss the measures required for India to achieve AI sovereignty.

Source: Indian Express