New Delhi: The Government of India is increasingly leveraging Artificial Intelligence (AI) to strengthen the agriculture supply chain, enhance crop productivity, promote sustainability, and improve farmer livelihoods. Several AI-driven initiatives are now actively addressing long-standing challenges in the farm sector, the Lok Sabha was informed on December 9.
In a written reply, Minister of State for Agriculture and Farmers Welfare Ramnath Thakur said that AI is being deployed across farmer services, pest surveillance, and weather-based crop planning.
One of the flagship digital initiatives is “Kisan e-Mitra”, a voice-based AI-powered chatbot designed to assist farmers with queries related to key government schemes including PM Kisan Samman Nidhi, PM Fasal Bima Yojana, and Kisan Credit Card. The system currently supports 11 regional languages, handles over 8,000 farmer queries daily, and has already answered more than 93 lakh queries, significantly improving access to real-time information for farmers.
To tackle rising crop losses due to climate change, the government has implemented the National Pest Surveillance System, which uses AI and Machine Learning to detect pest infestations through image-based analysis. The platform is currently used by over 10,000 extension workers and supports 66 crops and more than 432 pest species. Farmers can upload pest images for rapid identification and timely intervention, helping reduce crop damage. AI-based analytics is also being applied to satellite-based crop mapping and crop-weather matching for improved monitoring of sown areas.
In another major step, an AI-based pilot project was conducted during Kharif 2025 in collaboration with Development Innovation Lab–India to generate local monsoon onset forecasts across parts of 13 states. The project used an open-source blended model that included NeuralGCM, the European Centre for Medium-Range Weather Forecasts’ AI Forecasting System (AIFS), and 125 years of historical rainfall data from the India Meteorological Department.
The probabilistic forecasts focused specifically on predicting local monsoon onset, which is critical for determining sowing dates. These localized forecasts were sent via SMS through the M-Kisan portal to over 3.88 crore farmers in five regional languages—Hindi, Odia, Marathi, Bangla, and Punjabi.
To assess impact, telephonic feedback surveys were conducted in Madhya Pradesh and Bihar through Kisan Call Centres. The results showed that 31–52% of farmers modified their planting decisions, mainly by adjusting land preparation, sowing time, and even crop and input selection based on the AI-generated forecasts.
The government highlighted that these AI-driven interventions are strengthening the entire agriculture supply chain—from pre-sowing decision-making and pest management to real-time farmer advisory services—marking a significant shift toward data-driven, climate-resilient, and technology-enabled farming in India.