India’s AI Stack For Population-Scale Impact

Syllabus: GS3/Science and Technology 

In News

• India is hosting the India AI Impact Summit in New Delhi focusing on practical AI deployment and measurable societal outcomes rather than broad policy discussions. 

Developments and Applications 

• Agriculture:  AI-driven advisory tools are being used to guide sowing decisions, optimise input use and improve yields.
  • AI innovations are helping farmers make data-driven, sustainable decisions. 
  • Neoperk provides rapid soil health analysis for optimized fertiliser use,
    • CottonAce offers pest detection and localized pesticide guidance,
    • Niqo Robotics enables real-time pest and weed control with selective spraying, and 
    • Cropin creates a digital ecosystem for farm monitoring, credit analytics, and climate-smart predictive farming, improving productivity and reducing costs.
• Education:  The National Education Policy 2020 has incorporated AI literacy and applied learning through CBSE curricula, the DIKSHA digital platform and programmes such as YUVAi.
  • The stated objective is to build foundational AI skills at scale rather than confining training to specialist institutions.
  • PadhaiWithAI provides personalised math support, improving pass rates in government schools, Rocket Learning’s AI companion Appu delivers interactive literacy and numeracy activities for young children via WhatsApp, and Belagavi Smart City’s deep learning eBooks adapt in real time to user behaviour, boosting reading comprehension and speed.

• Healthcare: AI tools are being deployed to support early detection of tuberculosis, cancer, neurological disorders and other conditions, strengthening preventive screening and diagnostic workflows within public health systems.
  • AI-based thermal imaging is being  used for low-cost, non-invasive breast cancer screening.
  • Qure.ai rapidly analyses X-rays and CT scans to detect multiple diseases in resource-poor settings.
  • AISteth enables accurate remote diagnosis of heart and lung conditions, empowering frontline health workers and strengthening rural healthcare delivery.
• Judicial administration is also adopting AI-enabled systems.
  • Under e-Courts Phase III, machine learning tools are being used for translation, case scheduling and workflow management, with an emphasis on improving access through vernacular languages.
• Environmental: The India Meteorological Department is using AI for forecasting rainfall, cyclones, fog, lightning and wildfire risk.
  •  Tools such as Mausam GPT are designed to support farmers as well as disaster response agencies.

India’s present  Approach and Initiatives 

• The Economic Survey 2026 stresses that India’s AI strategy must prioritize human welfare and economic inclusion, ensuring AI adoption serves domestic needs and benefits all sectors and citizens.

• IndiaAI Mission supports 12 India-specific AI models with subsidised compute (25% cost offset).
• BharatGen develops India-focused foundation and multimodal models (billions–trillions of parameters).
• IndiaAIKosh hosts 5,722 datasets and 251 AI models from 54 organisations across 20 sectors.
• Bhashini offers 350+ AI models for speech recognition, translation, OCR, text-to-speech, and language detection.
• Startups like Sarvam AI are building sovereign AI models, e.g., Sarvam Vision, outperforming Google Gemini and ChatGPT in some benchmarks.
• Compute Capacity & Semiconductor Ambitions : ₹10,300+ crore allocated over 5 years for AI compute; shared access to 38,000 GPUs and 1,050 TPUs.
  • Dedicated secure GPU cluster (3,000 processors) for strategic AI use.
• India Semiconductor Mission: ₹76,000 crore for fabrication, packaging, and indigenous processors (SHAKTI, VEGA).
• National Supercomputing Mission: 40+ petaflops deployed via IITs, IISERs, national labs; systems like PARAM Siddhi-AI and AIRAWAT support NLP, weather, drug discovery.
• Digital Infrastructure & Data Centres: Nationwide optical fibre and 5G cover nearly all districts and 85% of the population.
  • India has ~3% of global data centre capacity (960 MW), projected to reach 9.2 GW by 2030.
  • Major hubs: Mumbai–Navi Mumbai, Bengaluru, Hyderabad, Chennai, Delhi NCR, Pune, Kolkata.
• Energy & Sustainability: Power is key for AI scale in India. As of FY 2025–26, peak demand reached 242.49 GW with negligible shortages (0.03%), and total generation capacity was 509.7 GW, over half from non-fossil sources.
  • Plans include 57 GW pumped storage and 43,220 MWh battery storage to stabilise grids for data centres. 
  • The SHANTI Act promotes nuclear power, including small and micro-reactors, as a continuous low-carbon energy source for compute-intensive infrastructure.

Conclusion and Way Forward 

• India’s AI strategy emphasizes human welfare, economic inclusion, and contextual innovation, targeting scalable solutions in health, agriculture, and education.
• The government acts as a catalyst and ecosystem orchestrator by facilitating procurement of domestic AI, setting standards for trust, integrating applications into the India AI Applications Stack, and ensuring governance aligns with international standards for global deployment.

Source :IE