[Answered] Analyze how the global alignment on Artificial Intelligence risks creating a ‘digital divide’ for the Global South. How can India leverage its model of Digital Public Infrastructure to champion equitable global AI governance?

Introduction

With the India AI Impact Summit 2026 adopting the New Delhi Declaration and the Economic Survey 2025–26 emphasizing AI-led productivity, India seeks to democratize AI through inclusive Digital Public Infrastructure (DPI).                     

Global AI Alignment and the Emerging Digital Divide

1. Global AI governance is increasingly shaped by three dominant models EU’s regulation-first approach, U.S. market-led innovation, and China’s state-driven AI ecosystem.
2. This concentration of compute, data and standards risks creating digital neo-colonialism, where the Global South becomes a technology consumer rather than a technology creator.

How Global AI Alignment Risks a Digital Divide

1. Compute & Infrastructure Monopoly: Frontier AI development is concentrated among a few corporations controlling GPUs, cloud infrastructure and foundation models. Developing nations remain dependent on imported AI services. Example: GPU concentration.
2. Data Colonialism: Global South supplies valuable linguistic and behavioural data while value creation occurs abroad. Domestic innovation and economic gains remain limited. Example: Data extraction.
3. Regulatory Exclusion: Global frameworks focus largely on existential AI risks rather than developmental priorities. High compliance costs disadvantage startups in developing countries. Example: Bletchley process.
4. Linguistic & Cultural Bias: Large Language Models predominantly reflect English-centric datasets. Indigenous languages and local knowledge systems remain underrepresented. Example: Low-resource languages.
5. Strategic Dependence: Dependence on foreign AI ecosystems exposes countries to export controls, sanctions, technology restrictions. Limits strategic autonomy. Example: Semiconductor controls.
6. Innovation Inequality: Brain drain, inadequate R&D and limited compute widen the technology gap, countries become perpetual AI consumers. Example: Startup ecosystem.

India’s Digital Public Infrastructure (DPI)

1. Democratising AI Infrastructure: Extend India’s successful DPI model (Aadhaar, UPI, DigiLocker, ONDC, Bhashini) into AI. Promote open APIs, interoperability and affordable AI access. Example: India Stack.
2. Open-Source Foundational Models: Support multilingual indigenous models through the IndiaAI Mission and BharatGen. Reduce dependence on proprietary AI platforms. Example: BharatGen.
3. Trusted Data Commons: Build privacy-preserving public datasets for agriculture, healthcare and education. Enable innovation while ensuring data sovereignty. Example: Bhashini datasets.
4. Affordable Compute for Global South: Expand sovereign GPU infrastructure under the ₹10,000-crore IndiaAI Mission. Offer subsidised compute partnerships for developing nations. Example: IndiaAI Compute.
5. Inclusive AI Governance: Champion principle-based governance balancing innovation, safety and inclusion. Operationalise India’s AI Governance Guidelines and AI Safety initiatives. Example: Responsible AI.
6. Global South Digital Diplomacy: Use G20, GPAI, BRICS, BIMSTEC and the UN to promote interoperable standards, shared datasets and capacity-building. Example: South-South cooperation.

Way Forward

1. Institutional: Establish a Global AI Commons under India’s leadership for shared datasets, benchmarks and open models. Example: Trusted AI Commons.
2. Technological: Scale open-source multilingual AI and Digital Public Infrastructure exports. Example: Bhashini.
3. Economic: Promote AI financing, digital skilling and sovereign cloud partnerships for developing countries. Example: Digital capacity.
4. Legal: Advocate transparent, development-oriented global AI norms aligned with SDGs while protecting data sovereignty. Example: UN AI dialogue.
5. Geopolitical: Build a Global South AI Alliance for compute sharing, interoperable standards and ethical AI. Example: India–Africa partnership.
6. Innovation: Expand AI sandboxes for healthcare, agriculture and education using open-source DPI. Example: Kisan AI.

Conclusion

Echoing Mahatma Gandhi’s principle that “the world has enough for everyone’s need,” India can transform AI into a Global Public Good, ensuring innovation advances equity, sovereignty and shared prosperity.