India’s deep-tech democracy for inclusive AI

Source: The post “India’s deep-tech democracy for inclusive AI” has been created, based on “India’s deep-tech democracy for inclusive AI” published in “The Hindu” on 15 November 2025.

UPSC Syllabus: GS Paper 3- Science and technology

Context: Artificial Intelligence has emerged as a defining force in shaping economies and transforming societies, but access to AI capacity remains unequal across the world. A handful of advanced nations control most high-end compute, proprietary datasets, and talent, creating a new digital divide between technology creators and technology consumers. India, through the IndiaAI Mission (2024), is attempting to bridge this divide by treating AI as a public good and building a democratic, inclusive, and sovereign AI ecosystem.

How IndiaAI Mission Addresses Global AI Imbalances

1. Democratising access to compute, data, and talent: India is creating a digital public infrastructure for AI that expands access to shared compute, open data, and decentralised talent. This ensures that start-ups, researchers, and students from every region can participate in technological progress.
2. Building India’s first national AI compute grid: Over 38,000 GPUs are being deployed to form India’s national AI compute grid, reducing dependence on global tech giants and lowering entry barriers for innovators.
3. Unlocking open and locally relevant datasets: The AI Kosh platform is providing 360+ curated, non-personal datasets across agriculture, climate, health, and governance. This helps innovators build solutions grounded in India’s diverse realities rather than imported assumptions.
4. Promoting multilingual, inclusive AI: The Digital India Bhashini framework supports AI tools in 22 Indian languages, while Project Vaani’s 150,000-hour dataset strengthens language diversity. This makes AI accessible to India’s linguistic and cultural spectrum.
5. Decentralising AI innovation: The Mission is establishing 570 AI labs in Tier-2 and Tier-3 cities and providing 13,500 AI fellowships, ensuring deep-tech innovation is not limited to metropolitan hubs.
6. Embedding India’s collaborative governance approach: India’s model draws from the Samaj–Sarkar–Bazaar philosophy, ensuring societal, governmental, and market cooperation so that technologies are ethical, transparent, and people-centric.
7. Safe and trusted AI ecosystem: A dedicated safe and trusted AI pillar is framing safeguards against misinformation, deepfakes, and algorithmic biases. Ethical guardrails are being built into AI systems to ensure accountability and human dignity.
8. Leveraging India’s Digital Public Infrastructure (DPI): AI integrated with platforms such as UPI, Aadhaar, and ONDC ensures population-scale impact. When AI is trained on Indian languages and delivered through public platforms, benefits directly reach farmers, small traders, students, and citizens at the last mile.
9. Global collaboration through India-AI Impact Summit 2026: The upcoming summit will convene leaders from the Global South to explore how AI can drive equity, accessibility, and inclusive growth, signalling India’s outward-looking and cooperative AI leadership.

Challenges in India’s Public AI Model

1. High cost and sustainability of compute infrastructure: Massive GPU deployment requires continuous investment, long-term maintenance, and stable power and cooling infrastructure.
2. Limited availability of specialised AI talent: Although India is expanding training, the demand for high-end AI researchers, data scientists, and semiconductor specialists remains far greater than supply.
3. Concerns around data governance and privacy: Large-scale open datasets raise questions about data security, consent, anonymisation, and responsible use.
4. Risk of algorithmic bias and unethical AI deployment: Even with safeguards, biases in models trained on uneven datasets may reinforce social inequalities.
5. Uneven adoption across states and institutions: Some states, rural colleges, and smaller institutions may not immediately benefit due to weak digital infrastructure and limited awareness.
6. Dependence on imported hardware: India still relies heavily on foreign semiconductor supply chains, making compute infrastructure vulnerable to global disruptions.

Way Forward

1. Accelerate domestic semiconductor manufacturing: Strengthening India’s chip ecosystem will reduce hardware dependency and ensure long-term compute sovereignty.
2. Establish national ethical AI and audit frameworks: Mandatory AI audits, impact assessments, and transparency standards can minimise risks of bias, misinformation, and misuse.
3. Expand training for AI talent at scale: AI courses in universities, vocational centres, and industry partnerships must be enhanced to build a strong talent pipeline.
4. Strengthen data protection and open-data governance: Robust privacy frameworks, anonymisation protocols, and secure data-sharing mechanisms will enhance trust in the ecosystem.
5. Increase collaboration with the Global South: Joint datasets, shared compute, and knowledge partnerships with Africa, Southeast Asia, and Latin America can help build a collective AI capacity.
6. Promote inclusive access through DPI integration: Linking AI innovations with UPI, ONDC, DigiLocker, and telehealth platforms will ensure that benefits reach the poorest and most remote communities.
7. Encourage responsible industry participation: Incentives for start-ups and ethical guidelines for private players can foster innovation while maintaining public-interest safeguards.

Conclusion: India’s public model of AI innovation represents a shift from proprietary, exclusive technological progress to democratic, accountable, and inclusive AI development. By socialising access to compute, data, and talent, India is ensuring that the competitive frontier shifts from “who can afford AI” to “who can innovate responsibly.” As the world prepares for the India-AI Impact Summit 2026, India’s message is clear: AI must uplift all and leave no one behind. The true measure of technological progress lies not just in advancing machines, but in advancing human dignity and shared prosperity.

Question: India is pioneering a public model of AI innovation through the IndiaAI Mission. Discuss how this model addresses global AI imbalances. Also highlight key challenges and suggest a way forward.