Welfare for all — the AI race India should win

UPSC Syllabus: Gs Paper 3- Science and technology

Introduction

India’s AI journey must move beyond global competition and technological display. The real opportunity lies in solving basic development gaps. Seventy per cent of global food comes from low-productivity small farmers. 4.5 billion people lack essential healthcare. 739 million adults and 250 million children lack basic literacy. AI offers practical tools to address these deep welfare challenges. The focus should be on improving lives, not winning a geopolitical race.India already has a growing AI ecosystem that can support this welfare-oriented transformation.

Current status of India’s AI ecosystem

1. Strong digital public infrastructure base: India’s digital public infrastructure gives AI developers a rare structural advantage. Platforms such as Aadhaar, UPI, DigiLocker, Bhashini, and DEPA allow fast scaling of identity, payments, data sharing, and service delivery. This integrated national architecture supports real-world AI use at population scale, which few countries can replicate.
2. Rapid growth in AI adoption and industry size: India’s technology sector is projected to cross USD 280 billion in annual revenue. Over 6 million people are employed in the tech and AI ecosystem. Around 87% of enterprises actively use AI solutions, with strong adoption in BFSI, healthcare, manufacturing, retail, and automotive
3. Expanding startup and developer ecosystem: India hosts around 8 lakh startups, and nearly 89% of new startupslaunched last year used AI in their products or services. The country has 1,800+ Global Capability Centres, including 500+ AI-focused centres. India is also the second-largest contributor to AI projects on GitHub, showing strong developer participation.
4. Global recognition and competitiveness: India ranks among the top four countries in AI skills and policy readiness and stands third globally in AI competitiveness. This reflects talent depth, research output, startup activity, and digital infrastructure, but the strength remains skewed towards deployment rather than core model building.

India’s Potential to Use AI

1. AI for Agriculture:

• Improving smallholder productivity: Most of the world’s food comes from small farmers with low productivity. AI tools can improve yield, reduce costs, and increase income.
• Kisan E-Mitra chatbot: The national chatbot handles 20,000 queries daily in 11 regional languages. It supports farmers at scale.
• Saagu Baagu project in Telangana: The AI-led project doubled chilli farmers’ earnings. It increased yield, reduced pesticide and fertiliser use, and improved sale prices.

2. AI for Healthcare Access

• Severe doctor shortage: India’s doctor-to-patient ratio in public hospitals is 1:11,000. This creates a huge access gap.
• eSanjeevani telemedicine platform: By mid-2025, it conducted 389 million virtual consultations. It expanded access without physical infrastructure.
• AI-based disease detection: Qure.ai’s TB detection algorithms have reached millions. AI supports diagnosis at scale.

3. AI for Human Capital and Skills

• Large but under-skilled workforce: India has 950 million workers, but only 5% have formal skill training. Skill building is a major challenge.
• FutureSkills PRIME: The programme enrolled 1.6 million learners. 41% are women and 85% are from Tier II and Tier III cities.
• DIKSHA platform: It reached 275 million users with 70% rural penetration. AI can democratise learning across regions.

Structural Issues in India’s AI Road

1. Digital divide and gender gap: Only 24% of rural households have internet access compared to 66% in urban areas. India is near the bottom in digital gender parity among 125 countries studied.
2. Energy and infrastructure stress: Weak grid reliability and transmission capacity will face more pressure due to AI’s growing energy demand.
3. Talent shortage in AI roles: For every 10 AI roles, only one qualified engineer is available. Talent is limited.

1. Dependence on foreign supply chains: India imports over 90% of semiconductor chips. The US–China rivalry has fragmented the global tech system.

5. Weak data and regulatory systems: India lacks high-quality annotated datasets, especially in regional languages. Complex customs and varying state rules slow innovation.
6. Funding and physical infrastructure gaps: Late-stage startups lack scale funding and rely on foreign capital after Series B. Traffic congestion and fragmented operations increase costs.

Initiatives taken to strengthen India’s AI strategy

1. IndiaAI Mission: The government launched the IndiaAI Mission in March 2024 with over ₹10,300 crore to build a strong indigenous AI ecosystem. It aims to democratise AI technology, improve data quality, and boost competitiveness.
2. INDIAai National Portal: INDIAai is India’s national AI portal supporting knowledge sharing, research insights, industry news and resources to connect stakeholders across the ecosystem.
3. AI Governance Guidelines: Government has rolled out governance guidelines under IndiaAI that aim to make AI safe, inclusive and pro-innovation without heavy regulation that stifles growth.
4. Centres of Excellence (CoEs):The government set up three CoEs in Healthcare, Agriculture, and Sustainable Cities, and announced a fourth CoE for Education in Budget 2025, to support collaborative and scalable AI innovation.
5. Sarvam AI and BharatGen Models: Initiatives like Sarvam AI (for smarter public services) and BharatGen AI (multilingual, multimodal model) focus on homegrown capabilities that reflect India’s linguistic and cultural diversity.
6. AI Impact Summit 2026: India will host the AI Impact Summit to showcase its AI capabilities, encourage innovation and build international collaborations.

Conclusion

India represents a fourth path beyond the US–China–EU model. AI leadership should be measured by higher farm productivity, better healthcare access, and improved literacy. The goal is not AI for power, but AI for people. India must build advanced AI systems while closing digital, energy, talent, and infrastructure gaps together.

Question for practice:

Examine how India can use artificial intelligence to improve agriculture, healthcare, and human capital while addressing structural challenges in its AI ecosystem to achieve inclusive welfare.

Source: The Hindu