{"id":19565,"date":"2026-02-16T17:33:24","date_gmt":"2026-02-16T12:03:24","guid":{"rendered":"https:\/\/theeducationoverview.in\/?p=19565"},"modified":"2026-02-16T17:33:24","modified_gmt":"2026-02-16T12:03:24","slug":"artificial-intelligence-ai-transforming-indian-agriculture","status":"publish","type":"post","link":"https:\/\/theeducationoverview.in\/?p=19565","title":{"rendered":"Artificial Intelligence (AI) Transforming Indian Agriculture"},"content":{"rendered":"
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Artificial Intelligence (AI) Transforming Indian Agriculture<\/strong><\/span><\/h2>\n

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Posted On: 14 FEB 2026 10:52AM by PIB Delhi<\/strong><\/span><\/div>\n
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Key Takeaways<\/strong><\/span><\/p>\n

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  • India has created a large-scale digital foundation for agriculture with over\u00a07.63 crore Farmer IDs\u00a0and\u00a023.5 crore crop plots surveyed\u00a0under the Digital Agriculture Mission.<\/strong><\/span><\/li>\n
  • National Pest Surveillance System supports\u00a066 crops and over 432 pest types, providing real-time advisories to more than\u00a010,000 extension workers\u00a0for early pest detection.<\/strong><\/span><\/li>\n
  • As of December 2025,\u00a0the Kisan e-Mitra\u00a0chatbot has answered more than\u00a093 lakh queries, handling over\u00a08,000 farmer queries daily\u00a0in 11 regional languages.<\/strong><\/span><\/li>\n
  • An AI-based pilot for local monsoon onset forecasting for Kharif 2025 reached\u00a03.88 crore farmers\u00a0across\u00a013 states\u00a0via SMS, with\u00a031\u201352%\u00a0of surveyed farmers adjusting sowing and land preparation decisions based on the forecasts.<\/strong><\/span><\/li>\n
  • YES-TECH, CROPIC,\u00a0and the\u00a0PMFBY WhatsApp Chatbot\u00a0are leveraging AI-enabled tools to make crop insurance under PMFBY more innovative, faster, and more transparent for farmers.<\/strong><\/span><\/li>\n
  • The\u00a0Union Budget 2026-27\u00a0proposed\u00a0Bharat-VISTAAR,\u00a0a multilingual AI tool\u00a0to integrate the AgriStack portals and the ICAR package with AI system.<\/strong><\/span><\/li>\n<\/ul>\n<\/div>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

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    Introduction<\/strong><\/span><\/p>\n

    India\u00a0is emerging as a\u00a0global leader\u00a0in\u00a0Artificial Intelligence, ranking third\u00a0worldwide in\u00a0AI competitiveness,\u00a0according to Stanford University\u2019s\u00a02025 Global AI Vibrancy Tool.\u00a0The rapid rise, measured across\u00a0AI growth and innovation between 2017 and 2024, reflects India\u2019s digital capabilities, data ecosystem, and strengths in AI talent, research, startup, investment, infrastructure, and governance. Artificial Intelligence\u00a0(AI)\u00a0is also increasingly emerging as a transformative force in agriculture, offering new pathways to enhance productivity, sustainability, and resilience across farming systems. By leveraging\u00a0data from satellites, sensors, drones, weather stations,\u00a0and\u00a0farm machinery,\u00a0AI-enabled tools support informed decision-making at every stage of the agricultural value\u00a0chain.<\/strong><\/span><\/p>\n

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    What is Artificial Intelligence?<\/em><\/strong><\/span><\/p>\n

    Artificial Intelligence (AI) is the ability of machines to perform tasks that normally require\u00a0human intelligence. It enables systems to learn from experience, adapt to new situations, and solve complex problems independently. AI uses datasets, algorithms, and large language models to analyse information, recognise patterns, and generate responses. Over time, these systems improve their performance, allowing them to reason, make decisions, and communicate in ways similar to humans.<\/em><\/strong><\/span><\/p>\n

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    India-AI Impact Summit 2026: AI for Inclusive Development<\/strong><\/span><\/p>\n

    The\u00a0India-AI Impact Summit 2026,\u00a0being convened, highlights India\u2019s approach to Artificial Intelligence as a tool for inclusive development. The Summit emphasises the\u00a0democratisation of technology\u00a0by promoting more equitable and affordable access to AI capabilities, particularly for underserved communities. It emphasizes India\u2019s approach to technology development, aligned with the vision of\u00a0\u2018Welfare for All, Happiness for All\u2019.<\/em>\u00a0Reinforcing the principle of \u2018AI for Humanity\u00a0‘- positioning AI as a\u00a0human-centric\u00a0and ethical enabler of\u00a0improved governance, service delivery,\u00a0and\u00a0sustainable development\u00a0across sectors. Within this broader context, Indian agriculture stands at a critical turning point, where AI is increasingly being harnessed to\u00a0support farmers, strengthen\u00a0decision-making,\u00a0and\u00a0enhance productivity.<\/strong><\/span><\/p>\n

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    \u00a0<\/em>Artificial Intelligence and Its Uses in Agriculture<\/strong><\/span><\/p>\n

    In agriculture, AI helps turn\u00a0data into simple, actionable advice that farmers can implement in their day-to-day farming practices. By analysing satellite imagery, weather forecasts, soil data, and crop patterns, AI can\u00a0help farmers decide\u00a0what to sow, when to sow, how much input to use, and when to harvest. From early warnings about pests and diseases to better planning for irrigation and fertiliser use, AI is making farming more precise, efficient, and less risky. The\u00a0uses of AI in agriculture\u00a0\u00a0can be categorised as:<\/strong><\/span><\/p>\n

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    • Soil Health Diagnostics<\/u><\/strong><\/span><\/li>\n<\/ul>\n

      AI uses\u00a0deep learning\u00a0and\u00a0image recognition\u00a0to\u00a0monitor soil health\u00a0by analysing signals from satellite imagery, drone-based observations, and farm-level images. This eliminates the need for laboratory testing infrastructure while detecting\u00a0nutrient deficiencies and soil stress. Farmers can take timely action to restore soil fertility.<\/strong><\/span><\/p>\n

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      • Climate-Responsive Crop Monitoring and Advisory Services<\/u><\/strong><\/span><\/li>\n<\/ul>\n

        Indian agriculture is particularly susceptible to climate variability because it relies heavily on rainfall. AI analyses weather and climate data to predict\u00a0changing rainfall patterns, temperature variations, and extreme events, while providing real-time advisories on sowing decisions, irrigation scheduling, pest management, and input application. In addition, AI-enabled monitoring using satellite imagery, drones, sensors, and image analytics facilitates early detection of pests and crop diseases, allowing timely interventions. Collectively, these applications support farmers, particularly in rainfed regions, in managing climate risks and reducing potential crop losses.<\/strong><\/span><\/p>\n

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        • Improving Farm Mechanisation Efficiency<\/u><\/strong><\/span><\/li>\n<\/ul>\n

          AI-powered image classification and\u00a0machine learning\u00a0tools, integrated with drones, remote sensing, and local sensor data,\u00a0improve the utilisation and efficiency of farm machinery. Applications include precision weed removal, early disease detection, automated harvesting, and produce grading.<\/strong><\/span><\/p>\n

          In horticulture, where crops require continuous monitoring across multiple growth stages, AI-based systems offer\u00a0round-the-clock surveillance\u00a0of\u00a0high-value crops.\u00a0This leads to reduced labour dependency, optimised input use, and improved quality control.<\/strong><\/span><\/p>\n

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          • Improving Price Realisation for Farmers<\/u><\/strong><\/span><\/li>\n<\/ul>\n

            Farmers, particularly those engaged in fruit and vegetable production, often capture only a small share of the final consumer price due to inadequate price discovery, supply chain inefficiencies, and information asymmetries. Artificial intelligence (AI) offers a robust means of addressing these structural constraints by strengthening\u00a0demand-supply forecasting, market intelligence,\u00a0and\u00a0coordination across agricultural value chains.<\/strong><\/span><\/p>\n

            AI-driven predictive analytics leverage large datasets from platforms such as\u00a0e-NAM, AGMARKET, the Agricultural Census,\u00a0and the\u00a0Soil Health Card programme\u00a0to assess price movements, arrival trends, and regional demand patterns. By incorporating both domestic and global commodity signals, these tools support more informed decisions on\u00a0crop selection, sales timing,\u00a0and\u00a0market choice, thereby enhancing price realisation and reducing distress-driven sales. The implementation of\u00a0AI in agriculture\u00a0highlights the breadth of bottom-up adoption across the sector. AI-enabled agricultural networks have improved market access, price discovery, and logistical efficiency for about\u00a01.8 million farmers across 12 states.<\/strong><\/span><\/p>\n

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            AI as a Key Enabler of Precision Farming<\/u><\/em><\/strong><\/span><\/p>\n

            AI enables precision farming by turning data from GPS, sensors, satellites, and drones into actionable farm-level insights. It enables the collection of data on soil properties, moisture levels, and crop health at a highly localised level,\u00a0ensuring that inputs such as water, fertilisers, and pesticides are applied precisely where and when needed. This site-specific approach improves productivity, optimises resource use, reduces waste, and minimises environmental impact.<\/em><\/strong><\/span><\/p>\n<\/div>\n

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            AI-Enabled Precision Farming: A Scalable Approach for Sustainable Agricultural Transformation<\/strong><\/span><\/p>\n

            The experience of\u00a0Rajaratnam Kanakarajan\u00a0illustrates the\u00a0practical and scalable\u00a0application of artificial intelligence in Indian agriculture. By adopting an\u00a0AI-enabled precision farming system\u00a0developed by Farm Again, a Tamil Nadu-based startup, he leveraged solar-powered sensors to monitor soil moisture, irrigation, and fertilizer use in real time through a mobile platform. The system automated farm operations, reduced over-irrigation and input use, and optimised crop conditions, resulting in a doubling of coconut yields.<\/em><\/strong><\/span><\/p>\n

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            This approach has since benefited over\u00a03,500 farmers\u00a0across more\u00a0than 4,000 acres\u00a0in Tamil Nadu. Its adoption has been driven by affordability, with indigenous equipment costing\u00a0(<\/em>\u20b9<\/em>2.5 Lakh)\u00a0<\/em>significantly less than imported\u00a0(<\/em>\u20b9<\/em>25 Lakh<\/em>) alternatives. In addition to productivity gains, the approach has delivered substantial environmental benefits, including annual savings of over 4,00,000 cubic metres of water and\u00a0approximately 1,75,000 kWh of energy, as well as significant emissions\u00a0reductions, avoiding an estimated\u00a020,000 tonnes of CO\u2082-equivalent emissions. The solution\u2019s scalability, demonstrated by its expansion to multiple countries, highlights how locally designed AI innovations can enhance farm productivity, conserve resources, and support sustainable agricultural transformation.<\/em><\/strong><\/span><\/p>\n<\/div>\n

            Government Initiatives in AI-Driven Agriculture<\/strong><\/span><\/p>\n

            The government is actively harnessing the power of Artificial Intelligence to transform the agriculture sector through its various initiatives. The initiatives mentioned below reflect the government’s holistic approach to agricultural growth and development, as reflected in\u00a0policy innovations.<\/strong><\/span><\/p>\n

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            Union Budget 2026-27: Bharat-VISTAAR for AI-Driven Agricultural Advisory<\/strong><\/span><\/p>\n<\/div>\n

            The\u00a0Union Budget 2026-27\u00a0proposed\u00a0Bharat-VISTAAR\u00a0(Virtually Integrated System to Access Agricultural Resources)-\u00a0a multilingual AI tool\u00a0that shall integrate the AgriStack portals and the ICAR package on agricultural practices with AI systems. This will increase farm productivity,\u00a0enable better decisions for farmers, and reduce risk by providing customized advisory support.<\/strong><\/span><\/p>\n

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            AI-Enabled Advisory and Decision Support Services for Farmers<\/strong><\/span><\/p>\n<\/div>\n

            Kisan e-Mitra:<\/u><\/strong><\/span><\/p>\n

            Kisan e-Mitra, launched in 2023, is a voice-enabled, AI-powered chatbot designed to support farmers by answering queries on key government schemes, including\u00a0PM Kisan Samman Nidhi, the Kisan Credit Card,\u00a0and\u00a0the Pradhan Mantri Fasal Bima Yojana. The platform operates in\u00a011 regional languages\u00a0and currently addresses over\u00a08,000 farmer queries\u00a0each day. As of December 2025, it has successfully responded to more than\u00a093 lakh queries, enhancing accessibility to scheme-related information for farmers across the country.<\/strong><\/span><\/p>\n

            National Pest Surveillance System:<\/u><\/strong><\/span><\/p>\n

            The\u00a0National Pest Surveillance System (NPSS),\u00a0launched in 2024, utilises Artificial Intelligence (AI) and Machine Learning (ML) to enable early detection of pest infestations and crop diseases. Accessible through a user-friendly mobile application and the online portal, the system allows farmers to upload images of affected crops or pests for rapid identification and diagnosis.<\/strong><\/span><\/p>\n

            Using image analytics, NPSS provides real-time crop protection advisories, guiding farmers on appropriate pest and disease management practices and enabling timely interventions to reduce crop losses. As of December 2025, NPSS is being used by over\u00a010,000 extension workers\u00a0and supports\u00a066 crops\u00a0and more than\u00a0432 pest species.<\/strong><\/span><\/p>\n

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            AI-Enabled Local Monsoon Onset Forecasts for Informed Kharif Sowing Decisions:<\/u><\/strong><\/span><\/p>\n

            An AI-based pilot was implemented during Kharif 2025 to generate location-specific monsoon onset forecasts across parts of\u00a013 states. The initiative was carried out in collaboration with the India Meteorological Department (IMD) and the Development Innovation Lab-India. The pilot employed an open-source blended modelling approach, combining NeuralGCM, the European Centre for Medium-Range Weather Forecasts\u2019 (ECMWF) Artificial Intelligence Forecasting System (AIFS), and\u00a0125 years of historical rainfall data from IMD. To guide optimal sowing decisions, focusing on local monsoon onset, probabilistic forecasts were disseminated via SMS through the mKisan portal to over\u00a03.88 crore farmers\u00a0in five regional languages across 13 states. Follow-up surveys in Madhya Pradesh and Bihar indicated that\u00a031\u201352 percent\u00a0of farmers modified their planting decisions based on the forecasts, primarily by adjusting land preparation, sowing timelines, and crop and input choices.<\/strong><\/span><\/p>\n

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            Data-Driven Governance through the Digital Agriculture Mission<\/strong><\/span><\/p>\n<\/div>\n

            The\u00a0Digital Agriculture Mission, launched in 2024 with a total outlay of\u00a0\u20b92,817 crore\u00a0and an allocation of\u00a0\u20b954.972 crore\u00a0for FY 2025\u201326, aims to advance the delivery of innovative, farmer-centric digital solutions in the agriculture sector. The Mission seeks to ensure timely access to reliable crop-related information for all farmers by leveraging verified datasets on farmers, landholdings, and crops, alongside advanced digital technologies such as data analytics,\u00a0artificial intelligence,\u00a0and\u00a0remote sensing.<\/strong><\/span><\/p>\n

            By strengthening\u00a0data-driven decision-making, the Mission is designed to enhance the efficiency, transparency, and responsiveness of agricultural services. It envisages developing a comprehensive Digital Public Infrastructure (DPI) for agriculture, including platforms such as\u00a0AgriStack and the Krishi Decision Support System (KDSS), as well as an integrated\u00a0Soil Fertility and Profile Map, thereby laying the foundation for a robust, scalable digital agriculture ecosystem in India.<\/strong><\/span><\/p>\n

            AgriStack:<\/u><\/strong><\/span><\/p>\n

            AgriStack is a core component of the Digital Agriculture Mission, providing farmers with a unique digital identity (Farmer ID) linked to land records, livestock ownership, crops cultivated, and benefits availed, enabling secure identification and access to agricultural services. \u00a0Against a target of\u00a011 crore Farmer IDs\u00a0by\u00a02026\u201327, over\u00a07.63 crore IDs\u00a0have been generated as of 27 November 2025, including\u00a01.93 crore IDs\u00a0for women farmers. To accelerate creation and verification,\u00a0\u20b910 per Farmer\u00a0ID has been earmarked from PM-KISAN administrative funds. AgriStack also supports a\u00a0mobile-based Digital Crop Survey\u00a0that captures real-time, plot-level data on crop type and area under cultivation. The survey covered\u00a0492 districts\u00a0and over\u00a023.5 crore plots\u00a0during Rabi 2024\u201325,\u00a0with nationwide rollout planned across all districts in FY 2025\u201326 to strengthen planning, monitoring, and policy implementation.<\/strong><\/span><\/p>\n

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            Krishi Decision Support System:<\/u><\/strong><\/span><\/p>\n

            The\u00a0Krishi Decision Support System (KDSS)\u00a0integrates data from multiple sources, including satellite imagery, weather information, soil and water resources, crop data, and government scheme databases, to\u00a0generate comprehensive analytical outputs\u00a0such as digital crop maps, soil maps, yield estimates, and drought and flood monitoring assessments. The system supports informed\u00a0decision-making by enabling crop diversification advisories\u00a0and facilitating technology- and model-based yield assessments for crop insurance settlement. Simultaneously, KDSS strengthens evidence-based policymaking and programme implementation by providing government agencies with reliable,\u00a0real-time insights.<\/strong><\/span><\/p>\n

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            Soil Profile Maps:<\/u><\/strong><\/span><\/p>\n

            The\u00a0Nationwide Soil Resource Mapping project,\u00a0undertaken by the Soil and Land Use Survey of India (SLUSI), aims to generate a comprehensive village-level soil inventory at a high spatial resolution of\u00a01:10,000\u00a0by integrating high-resolution satellite imagery with field-based observations. The resulting standardized soil maps provide a scientific basis for informed land-use planning, crop selection, and the promotion of sustainable agricultural practices. As of September 2024, approximately\u00a029 million hectares\u00a0have been mapped, against the mission target of 142 million hectares of agricultural land. For the implementation of the mission,\u00a0\u20b91,076 crore\u00a0has been provided to\u00a0six states- Uttar Pradesh, Madhya Pradesh, Rajasthan, Maharashtra, Tamil Nadu, and Andhra Pradesh. Also, the state has been encouraged to adopt the\u00a0camp-mode approach to organise field-level camps and mobilise the local administration, with an allocation of\u00a0\u20b915,000\u00a0per camp.<\/strong><\/span><\/p>\n

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            AI-Enabled, Technology-Driven Crop Insurance for Resilient Agriculture<\/strong><\/span><\/p>\n<\/div>\n

            The\u00a0Pradhan Mantri Fasal Bima Yojana (PMFBY)\u00a0was launched to safeguard farmers against crop losses arising from unforeseen events by offering affordable crop insurance through low, fixed premium rates. Farmers contribute only\u00a02 percent\u00a0for Kharif food and oilseed crops,\u00a01.5 percent\u00a0for Rabi food and oilseed crops, and\u00a05 percent\u00a0for commercial and horticultural crops, with the remaining premium subsidised by the government. In the North-Eastern States, Jammu & Kashmir, and Himachal Pradesh, the full premium is borne by the government to\u00a0ensure coverage for vulnerable farmers.<\/strong><\/span><\/p>\n

            The scheme has progressively integrated AI-enabled technologies to enhance efficiency and transparency.<\/strong><\/span><\/p>\n

            The\u00a0YES-TECH\u00a0(Yield Estimation System based on Technology) employs remote sensing and AI-driven analytics to generate\u00a0accurate yield estimates. Introduced for paddy and wheat in Kharif 2023 and extended to soybean in Kharif 2024, YES-TECH assigns a\u00a0minimum 30 percent\u00a0weightage to technology-based assessments. As of January 2025, it has been adopted by nine states, with Madhya Pradesh fully transitioning to\u00a0technology-based yield estimation, thereby enabling timely loss assessment and faster claim settlement.<\/strong><\/span><\/p>\n

            CROPIC (Collection of Real-Time Observations and Photographs of Crops)\u00a0is an AI-enabled tool used to monitor crop health and assess crop damage. Through a mobile application, farmers and field coordinators upload geotagged, time-stamped crop images from smartphones. These time-series photographs support crop validation against insured crops and enable accurate damage assessment during localised calamities. CROPIC provides a transparent, real-time, evidence-based system that strengthens crop insurance implementation, disaster response, and data-driven decision-making.<\/strong><\/span><\/p>\n

            The PMFBY WhatsApp Chatbot\u00a0<\/u>is an AI-based chatbot accessible via WhatsApp to assist farmers with information on the PMFBY scheme.<\/strong><\/span><\/p>\n

            WINDS (Weather Information and Network Data System),\u00a0launched in 2023, is a national platform that\u00a0integrates multiple weather systems\u00a0to provide real-time, reliable weather data. It enables\u00a0accurate weather monitoring, planning, and risk assessment in agriculture.<\/strong><\/span><\/p>\n

            PMFBY\u00a0has emerged as\u00a0India\u2019s most extensive crop insurance\u00a0programme. Introduced alongside PMFBY, the Restructured Weather-Based Crop Insurance Scheme\u00a0(RWBCIS)\u00a0is a weather index-based insurance scheme that complements yield-based coverage. Between\u00a02016\u201317\u00a0and\u00a02024\u201325\u00a0(as of October 2025), the Pradhan Mantri Fasal Bima Yojana (PMFBY) and the Restructured Weather-Based Crop Insurance Scheme (RWBCIS) together covered over\u00a078.51 crore farmer applications. During this period, farmers contributed\u00a0\u20b935,919 crore\u00a0in premiums, while claims amounting to\u00a0\u20b91,90,374 crore\u00a0were disbursed, benefiting more than\u00a023 crore farmer applications. Focusing on the recent period from 2020\u201321 to 2024\u201325 alone (as of 31 October 2025), the schemes covered over\u00a055.28 crore applications\u00a0and paid\u00a0\u20b993,891 crore in claims, benefiting more than\u00a014.97 crore farmer applications. These facts underscore the expanding reach, credibility, and impact of PMFBY in\u00a0protecting farm livelihoods against production risks.<\/strong><\/span><\/p>\n

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            AI-Enabled Agri-Tech Startups and Emerging Agricultural Innovations<\/strong><\/span><\/p>\n<\/div>\n

            The Government of India has been promoting the\u00a0rapid growth of agri-tech startups\u00a0through the\u00a0Innovation and Agri-Entrepreneurship Development programme\u00a0under the Rashtriya Krishi Vikas Yojana (RKVY) since 2018\u201319. In parallel, the programme supports the adoption of emerging technologies, including\u00a0Artificial Intelligence (AI), machine learning, precision farming, drones, and climate-smart agriculture. Agri-tech startups are ushering in a\u00a0new era for Indian agriculture, integrating agricultural practices with artificial intelligence. These startups, dubbed a \u2018ray of hope\u2019, are driving innovation and transforming agrarian operations across the country.<\/strong><\/span><\/p>\n

            Under the programme,\u00a0Knowledge Partners (KPs)\u00a0and\u00a0RKVY Agribusiness Incubators (R-ABIs)\u00a0provide structured technical and financial support to agri-startups at the idea or pre-seed stage (up to \u20b95 lakh) and the seed stage (up to \u20b925 lakh), enabling them to develop, pilot, and scale innovative products and services. As of January 2026, more than\u00a06,000 agri-startups\u00a0have received training, and between FY 2019\u201320 and FY 2025\u201326, a total of\u00a02282 startups\u00a0have been supported with financial and technical assistance, with cumulative grants amounting to\u00a0\u20b9186.55 crore.<\/strong><\/span><\/p>\n

            The supported startups operate across key domains, including precision agriculture,\u00a0AI and IoT\u2013based solutions, farm mechanisation, post-harvest and food technologies, supply chain management, waste-to-wealth initiatives, and organic farming, thereby driving innovation and enhancing efficiency across agriculture and allied sectors.<\/strong><\/span><\/p>\n

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            AI-Enabled Robotics Transforming Farm Operations<\/strong><\/span><\/p>\n<\/div>\n

            The Agricultural Engineering Division of\u00a0ICAR\u2013Indian Agricultural Research Institute\u00a0(IARI)\u00a0is actively engaged in developing agricultural robotics for a range of farm operations, including soil sampling, sowing, harvesting, and crop surveillance. Complementing these efforts,\u00a0India\u2019s agrarian robotics\u00a0ecosystem has witnessed notable advances, including autonomous tractors, robotic harvesting systems, and\u00a0AI-enabled tools\u00a0for crop monitoring, reflecting the\u00a0growing integration of automation and intelligent technologies\u00a0into agricultural practices.<\/strong><\/span><\/p>\n

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            Future Farming in India: The IMPACT AI Framework<\/strong><\/span><\/p>\n

            The Government of India released a publication titled\u00a0\u201cFuture Farming in India: AI Playbook for Agriculture\u201d<\/em>\u00a0on\u00a022 October 2025. Developed as an\u00a0insight report\u00a0by the\u00a0World Economic Forum\u00a0in collaboration with the Office of the Principal Scientific Adviser to the Government of India, IndiaAI (MeitY), and BCG X, the\u00a0playbook provides\u00a0a policy-oriented roadmap for the\u00a0responsible and scalable adoption of artificial intelligence (AI) in Indian agriculture, with a specific focus on\u00a0small and marginal farmers.<\/strong><\/span><\/p>\n

            The playbook aims to bridge the\u00a0transition from pilot-stage AI applications\u00a0to large-scale implementation by addressing critical constraints, including fragmented data ecosystems, limited digital infrastructure, affordability barriers, and last-mile delivery challenges. It positions artificial intelligence as an\u00a0enabler of data-driven decision-making\u00a0in routine farm operations, with the potential to enhance productivity, strengthen climate resilience,\u00a0optimise resource use,\u00a0and\u00a0improve market access.<\/strong><\/span><\/p>\n

            The report highlights priority\u00a0AI use cases\u00a0across the agricultural value chain, including AI-enabled crop planning, rapid soil-health analysis, pest prediction and control, and smart digital marketplaces. A central contribution of the playbook is the\u00a0IMPACT AI framework, built on the following pillars, to guide ecosystem-wide action, clarify stakeholder roles, and support effective deployment of AI solutions:<\/strong><\/span><\/p>\n

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            Enable:<\/u>\u00a0The Enable pillar focuses on\u00a0creating the basic systems needed to scale AI in agriculture. It emphasizes government-led actions such as developing clear AI strategies, supportive policies, data-sharing frameworks, and digital infrastructure to enable adoption.<\/strong><\/span><\/p>\n

            Create:<\/u>\u00a0The Create pillar focuses on\u00a0developing and testing AI solutions for agriculture. It highlights collaboration between start-ups, technology providers, and research institutions to design, validate, and refine AI applications.<\/strong><\/span><\/p>\n

            Deliver:<\/u>\u00a0The Deliver pillar focuses on\u00a0ensuring AI solutions reach farmers effectively. It strengthens extension systems, integrates AI into advisory services, and uses field feedback to improve outcomes.<\/strong><\/span><\/p>\n

            Conclusion<\/strong><\/span><\/p>\n

            India is undergoing a profound\u00a0technological transformation in agriculture, leveraging Artificial Intelligence to move from traditional methods to a data-driven, precision-based ecosystem. This shift is anchored by the creation of a massive\u00a0digital public infrastructure, including the Digital Agriculture Mission and AgriStack, which provides a verified foundation for delivering targeted services to millions of farmers. The integration of AI is delivering tangible benefits across the entire agricultural value chain.<\/strong><\/span><\/p>\n

            Tools like\u00a0Bharat-VISTAAR\u00a0and\u00a0Kisan e-Mitra\u00a0provide multilingual, real-time advisory services, making expert knowledge accessible even in remote areas and further enhancing decision-making. AI-powered systems for\u00a0monsoon forecasting\u00a0and\u00a0pest surveillance\u00a0(NPSS) allow farmers to proactively manage climate and biological risks, significantly reducing potential losses and increasing resilience. Innovations in\u00a0precision farming, agri-robotics, and AI-enabled crop insurance through\u00a0YES-TECH and CROPIC\u00a0are optimizing resource use and ensuring faster, more transparent claim settlements.\u00a0Furthermore,\u00a0AI-driven analytics seeks to address structural constraints in the supply chain, improving\u00a0price discovery\u00a0and market access for\u00a0small and marginal farmers.\u00a0Collectively, these initiatives reflect a\u00a0human-centric approach\u00a0to technology, aiming for\u00a0sustainable agricultural growth\u00a0that prioritizes inclusive development and the welfare of the farming community.<\/strong><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

            Artificial Intelligence (AI) Transforming Indian Agriculture Posted On: 14 FEB 2026 10:52AM by PIB Delhi Key Takeaways India has created a large-scale digital foundation for agriculture with over\u00a07.63 crore Farmer IDs\u00a0and\u00a023.5 crore crop plots surveyed\u00a0under the Digital Agriculture Mission. National Pest Surveillance System supports\u00a066 crops and over 432 pest types, providing real-time advisories to more …<\/p>\n","protected":false},"author":2,"featured_media":19566,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-19565","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-education-news"],"_links":{"self":[{"href":"https:\/\/theeducationoverview.in\/index.php?rest_route=\/wp\/v2\/posts\/19565","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/theeducationoverview.in\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/theeducationoverview.in\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/theeducationoverview.in\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/theeducationoverview.in\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=19565"}],"version-history":[{"count":1,"href":"https:\/\/theeducationoverview.in\/index.php?rest_route=\/wp\/v2\/posts\/19565\/revisions"}],"predecessor-version":[{"id":19567,"href":"https:\/\/theeducationoverview.in\/index.php?rest_route=\/wp\/v2\/posts\/19565\/revisions\/19567"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/theeducationoverview.in\/index.php?rest_route=\/wp\/v2\/media\/19566"}],"wp:attachment":[{"href":"https:\/\/theeducationoverview.in\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=19565"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/theeducationoverview.in\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=19565"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/theeducationoverview.in\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=19565"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}