India is positioning itself at the forefront of Artificial Intelligence (AI)-driven governance, and agriculture has emerged as one of its most ambitious frontiers. With over 7.63 crore Farmer IDs generated, 23.5 crore crop plots surveyed, AI-enabled pest surveillance, monsoon forecasting pilots, and smart crop insurance systems, India is building a data-powered agricultural ecosystem. This transformation is not merely technological; it seeks to enhance productivity, resilience, transparency, and farmer welfare in a climate-stressed agrarian economy.
From AI Ambition to Agricultural Application
India’s global rise in Artificial Intelligence competitiveness, as reflected in Stanford University’s 2025 Global AI Vibrancy Tool, coincides with a domestic push to embed AI in public service delivery. Agriculture, which sustains nearly half of India’s workforce, has become central to this vision.
Artificial Intelligence refers to the capacity of machines to perform tasks requiring human-like reasoning, learning, and decision-making. In agriculture, AI systems process vast datasets drawn from satellites, drones, weather stations, sensors, and market platforms to generate real-time, actionable advisories. This shift marks a movement from generalized extension advice to hyper-local, data-driven recommendations.
The approach was reinforced at the India-AI Impact Summit 2026, which emphasised “AI for Humanity” — positioning AI as a human-centric instrument for inclusive growth.
Building the Digital Backbone: The Digital Agriculture Mission
Launched in 2024, the Digital Agriculture Mission is laying the foundation for a Digital Public Infrastructure (DPI) for agriculture. Its core pillars include:
- AgriStack: A unique digital identity (Farmer ID) linked to land records, crops, livestock, and benefits. Over 7.63 crore Farmer IDs have been generated against a target of 11 crore by 2026–27.
- Digital Crop Survey: Conducted across 492 districts during Rabi 2024–25, covering 23.5 crore plots to create verified, plot-level crop data.
- Krishi Decision Support System (KDSS): Integrates satellite, soil, weather, and crop data to generate crop maps, yield estimates, and drought/flood monitoring outputs.
- Soil Profile Mapping: High-resolution mapping at 1:10,000 scale to promote scientific land-use planning.
This infrastructure shifts agricultural governance from scheme-based disbursement to evidence-based policymaking, improving targeting, transparency, and responsiveness.
AI in Action: From Pest Alerts to Monsoon Forecasts
AI tools are now directly shaping farm-level decisions.
The National Pest Surveillance System supports 66 crops and over 432 pest types, enabling image-based pest detection and real-time advisories. More than 10,000 extension workers use the platform for early detection and intervention.
Similarly, an AI-based pilot for local monsoon onset forecasting during Kharif 2025 reached 3.88 crore farmers across 13 states via SMS. Surveys revealed that 31–52% of farmers adjusted sowing and land preparation decisions based on these forecasts — demonstrating behavioural change driven by predictive analytics.
Kisan e-Mitra, an AI-powered multilingual chatbot, has answered more than 93 lakh farmer queries as of December 2025, handling over 8,000 daily queries in 11 languages. By simplifying access to schemes such as PM-KISAN, KCC, and crop insurance, it reduces informational asymmetry.
These interventions represent a shift from reactive to preventive agriculture.
Precision Farming, Insurance and Market Intelligence
AI is enabling precision agriculture by guiding site-specific input application. By analysing soil moisture, nutrient levels, and crop health data, AI reduces overuse of fertilisers, water, and pesticides — enhancing productivity while minimising environmental costs.
Under the Pradhan Mantri Fasal Bima Yojana (PMFBY), AI-based tools such as YES-TECH and CROPIC are transforming crop insurance:
- YES-TECH uses remote sensing and AI analytics for technology-based yield estimation.
- CROPIC enables geotagged, time-stamped crop images for real-time damage assessment.
- The PMFBY WhatsApp Chatbot improves accessibility and transparency.
Between 2016–17 and 2024–25, PMFBY and RWBCIS covered 78.51 crore farmer applications and disbursed ₹1.90 lakh crore in claims — underscoring its scale. AI integration enhances speed, accuracy, and trust in claim settlement.
AI is also addressing structural inefficiencies in agricultural markets. By leveraging data from e-NAM and other platforms, predictive analytics supports better crop planning, improved price discovery, and reduced distress sales. AI-enabled networks have reportedly improved market access for nearly 1.8 million farmers across 12 states.
Startups, Robotics and the Emerging Agri-Tech Ecosystem
The Innovation and Agri-Entrepreneurship Development programme under RKVY has supported over 2,282 agri-startups with grants amounting to ₹186.55 crore. These startups operate across:
- AI and IoT-based farm monitoring
- Drone-enabled crop surveillance
- Climate-smart agriculture
- Supply chain digitisation
- Waste-to-wealth innovations
Simultaneously, ICAR–IARI is advancing agricultural robotics in soil sampling, harvesting, and crop monitoring. Autonomous tractors and robotic harvesting systems signal the gradual mechanisation of Indian farms through intelligent automation.
The “Future Farming in India: AI Playbook for Agriculture,” developed with the World Economic Forum and IndiaAI, outlines the IMPACT AI framework — structured around Enable, Create, and Deliver pillars — to scale responsible AI adoption.
Governance, Ethics and the Road Ahead
While AI promises productivity gains and climate resilience, its expansion raises important governance questions:
- Data privacy and farmer consent in AgriStack.
- Digital divide affecting small and marginal farmers.
- Affordability and accessibility of AI tools.
- Capacity of extension systems to interpret AI outputs.
The proposed Bharat-VISTAAR multilingual AI platform in the Union Budget 2026–27 seeks to integrate AgriStack with ICAR advisories, moving toward a unified advisory ecosystem.
India’s AI-driven agricultural transformation represents a model of state-supported digital public infrastructure combined with private innovation. The long-term challenge lies not merely in technological adoption but in ensuring equitable access, farmer trust, and ecological sustainability.
What to Note for Prelims?
- Digital Agriculture Mission (2024) – Outlay ₹2,817 crore.
- AgriStack – 7.63 crore Farmer IDs generated.
- National Pest Surveillance System – 66 crops, 432 pests.
- Kisan e-Mitra – 93 lakh queries answered.
- AI-based Monsoon Pilot – 3.88 crore farmers reached.
- YES-TECH and CROPIC under PMFBY.
- IMPACT AI framework – Enable, Create, Deliver.
What to Note for Mains?
- AI as Digital Public Infrastructure in agriculture.
- Role of AI in climate resilience and precision farming.
- Governance challenges: data protection, digital exclusion.
- AI-enabled insurance reform under PMFBY.
- Balancing innovation with inclusivity and sustainability.