[Answered] Drawing parallels with India’s early nuclear diplomacy, evaluate the challenges of treating AI as a strategic asset rather than a global public good. Analyze how India can balance collective governance aspirations with the imperative of safeguarding national interests amidst contemporary geopolitical rivalries.

Introduction

With AI projected to add $15.7 trillion to the global economy by 2030 (PwC) and nations weaponising algorithms, India’s AI diplomacy echoes its 1950s nuclear balancing between universalism and strategic autonomy.

Parallels with India’s Early Nuclear Diplomacy

1. The Bhabha Moment (1955 Geneva Conference): In 1955, Homi J. Bhabha presided over the UN Conference on peaceful nuclear uses, advocating technology access for developing nations. India positioned itself as a bridge-builder—championing Atoms for Peace while quietly building indigenous capacity.
2. Cold War Technological Rivalry: The nuclear contest between the United States and the Soviet Union mirrors today’s AI rivalry between the US and China. In both eras, transformative technologies were dual-use—civilian and military.
3. The Lesson of Strategic Miscalculation: Post-1960s geopolitical shifts and the emergence of export controls culminated in India’s isolation after its 1974 nuclear test. Regimes such as the Nuclear Suppliers Group restricted access to nuclear materials. The experience underscores that moral advocacy without technological capability leads to vulnerability.

AI as Strategic Asset vs Global Public Good

1. Dual-Use Nature of AI: Like nuclear technology, AI underpins both economic growth and military advantage—cyber warfare, autonomous systems, predictive surveillance. Treating AI solely as a global commons risks strategic dependency.
2. Compute Sovereignty and Data Nationalism: Foundation models require advanced semiconductor supply chains and hyperscale compute. Export controls on advanced chips reflect AI’s securitisation. Overdependence could reduce India to a data colony.
3. The Risk of a Digital NPT: Just as the nuclear order differentiated between haves and have-nots, restrictive AI governance regimes could limit access to frontier compute and proprietary models for emerging economies.
4. Technological Colonisation: Concentration of AI power in a few Big Tech firms may replicate asymmetrical global hierarchies. Digital infrastructure dominance translates into normative dominance.

Balancing Collective Governance and National Interest

1. Strategic Autonomy 2.0: India must invest in indigenous AI capabilities—compute infrastructure, semiconductor design, sovereign datasets, and talent ecosystems—under initiatives such as the IndiaAI Mission.
2. Digital Public Infrastructure (DPI) Model: India’s open, interoperable systems (e.g., Aadhaar, UPI) demonstrate that national capability can coexist with global openness. AI layered onto DPI can promote inclusive growth while retaining sovereign control.
3. Middle-Path Diplomacy (Data Non-Alignment): Echoing the Non-Aligned Movement, India can advocate inclusive AI governance—fair standards, interoperability, ethical norms—while avoiding alignment within rigid techno-blocs.
4. Engagement in Global Norm-Setting: Participation in multilateral platforms shaping AI safety, algorithmic transparency, and risk classification allows India to influence standards rather than merely adopt them.
5. South-South Cooperation: By deploying AI in agriculture, health diagnostics, and climate adaptation domestically, India can export scalable governance models to the Global South—turning domestic capability into diplomatic capital.

Contemporary Geopolitical Realities

1. Intensifying US–China Rivalry: AI competition now involves export controls, industrial subsidies, and standards wars. Supply-chain resilience in semiconductors and rare earths is central to strategic leverage.
2. Regulatory Fragmentation: Divergent regulatory models—risk-based (EU), innovation-led (US), state-centric (China)—create compliance complexity. India must craft a calibrated regulatory architecture balancing innovation and safeguards.
3. Economic Stakes: AI’s contribution to productivity, defence capability, and economic competitiveness makes it inseparable from national power metrics.

Way Forward

1. Build sovereign compute and AI hardware capabilities.
2. Invest in frontier research ecosystems and public–private partnerships.
3. Advocate equitable global AI governance grounded in transparency and access.
4. Align domestic regulation with global best practices without compromising autonomy.

Conclusion

As A. P. J. Abdul Kalam reminded in India 2020, strength respects strength; India must anchor AI universalism in computational capability, weaving strategic autonomy with global responsibility in an algorithmic age.