How India Can Turn AI into Foreign Policy

UPSC Syllabus Topic: GS Paper 3– Science and Technology – Developments and their applications and effects in everyday life.

Introduction

India’s Global AI Summit marks a shift from symbolism to statecraft. The focus is not on displaying technological power but on building credibility. As trust becomes central to global AI adoption, India is positioning itself as a reliable partner through governance-first policy, real-world deployment, and AI diplomacy. By developing AI systems under real constraints such as low bandwidth, multiple languages, and uneven infrastructure, India is turning complexity into a strategic advantage that strengthens its foreign policy ambitions.

Current Status of India’s Artificial Intelligence Ecosystem

1. Governance-first AI vision: India follows a governance-led model instead of fear-based regulation. The seven-pillar AI Chakras framework focuses on safe and trusted AI, democratized access, and inclusion by design.
2. Enablement over restriction: Unlike Western regulatory caution or Chinese techno-nationalism, India supports innovation through enablement. The approach shows that safety and scale can coexist.
3. Population-scale deployment: AI is already in active use. Millions of farmers receive AI advisories, hospitals use AI tools to screen TB and stroke, and the Supreme Court uses AI for multilingual translation.
4. From pilots to rollout: While many countries remain at experimental stages, India has reached nationwide deployment, proving that AI can work for large populations.
5. Digital Public Infrastructure foundation: Platforms such as Aadhaar, UPI, DigiLocker, and DEPA (Data Empowerment and Protection Architecture) form an interoperable public stack. These systems are built openly and function at national scale.
6. Trust-based credibility advantage: India relies on transparent institutions and political legitimacy rather than competing on raw compute power.

What Are the Challenges of India’s Artificial Intelligence Ecosystem?

1. Trust without capacity risk: Trust alone cannot sustain leadership. Without infrastructure support, credibility may weaken over time.
2. Limited compute accessibility: AIRAWAT national compute infrastructure remains difficult to access. Opaque processes restrict use by startups and academic institutions.
3. Slow scaling of indigenous models: Bharat GenAI efforts remain confined to pilots, limiting large-scale model development.
4. Weak safety research ecosystem: AI safety research lacks dedicated institutional funding, despite increasing deployment risks.
5. Data constraints: Public datasets, especially for low-resource Indian languages and regulated sectors, are limited and often not audit-ready.
6. Institutional guardrails lag: Governance systems are not evolving at the same speed as deployment, creating regulatory gaps.
7. Unclear liability framework: There is no clarity on responsibility when AI systems fail. Developer, deployer, and data custodian roles remain undefined, raising risks for industry.
8. Absence of strong sandboxes: India lacks sector-specific, regulator-backed AI sandboxes with legal protection for testing high-risk systems.

India’s ‘Third Path’ for the Global South

1. Global governance dilemma: Developing countries face limited choices. Western AI systems are costly and compliance-heavy. Chinese systems come with strategic dependencies.
2. India’s alternative model: India offers a third path based on openness, interoperability, and inclusion, avoiding both restriction and control.
3. Growing global interest: Countries across Asia, Africa, and Latin America are studying India’s DPI architecture.
4. Adoption of Indian systems: Some nations are adopting UPI-based payment models, while others test Aadhaar-like digital identity systems.
5. From technology export to capacity export: India’s approach shifts focus from selling tools to building national capabilities.
6. From follower to framer: By shaping governance models, India moves from being an AI user to a rule-setting contributor.

AI as an Instrument of Foreign Policy

1. Emergence of AI diplomacy: India is using the Global AI Summit as a diplomatic platform to extend cooperation beyond national borders. Through this platform, it brings Global South researchers together, invites global impact challenges, and co-creates AI solutions with multilateral institutions.
2. Alignment without coercion: India does not demand ideological alignment. It offers cooperation on mutually acceptable terms.
3. Ecosystem-building strategy: The focus is not on winning markets but on shaping long-term AI ecosystems.
4. Soft power expansion: AI becomes a tool of diplomacy, strengthening influence through shared governance and joint capacity building.
5. Replacing dependency with partnership: India’s model emphasizes mutual capacity instead of technological dependence, enhancing global trust.

Way Forward

1. Compute access reform: AIRAWAT must move from concept to access, with transparent procedures so startups, researchers, and academic institutions can use national compute easily.
2. Scale Bharat GenAI: Model development efforts under Bharat GenAI must expand beyond pilot projects to build domestic AI capability at meaningful scale.
3. Fund safety research: AI safety research requires dedicated institutional funding to manage risks as deployment expands into governance and public services.
4. Open public datasets: Public datasets, especially for low-resource languages and regulated sectors, must be made open, usable, and audit-ready.
5. Clear liability norms: A clear framework is needed to define accountability among developers, deployers, and data custodians when AI systems fail.
6. Regulatory sandboxes: Sector-specific, regulator-backed sandboxes with legal cover must be created to test high-risk AI systems before formal regulation.

Conclusion

India’s AI strategy blends trust, deployment, and diplomacy into foreign policy. The summit places India at the center of the global trust debate. Yet credibility depends on delivery. With stronger coordination, infrastructure, and governance, India can show that democratic AI at scale is not a contradiction, but a workable global model.

Question for practice:

Examine how India is using artificial intelligence as a tool of foreign policy by leveraging trust-based governance, large-scale deployment, and cooperation with the Global South.

Source: Businessline