The move signals a push to deploy artificial intelligence (AI) and digital technologies across Indian agriculture to improve real-time decision-making on weather, soil, irrigation and pest management, as policymakers seek to raise farm productivity and reduce losses in a sector that supports nearly half of the country’s workforce.
As per a CropLife India-YES Bank knowledge report, harvest worth about ₹2 trillion is lost annually due to pests in India.
Support for AI-based crop monitoring, yield forecasting and early warning systems could help reduce losses and improve planning at both farm and policy levels.
India has undertaken multiple digital agriculture initiatives for over a decade, and many of the elements now being highlighted under the DAM were piloted earlier, but they remained fragmented, limited in coverage, or advisory-only. For instance, the National e-Governance Plan in Agriculture (NeGP-A), launched in 2010, enabled digital delivery of advisories related to weather, crops and inputs, but it relied largely on static datasets and SMS-based information rather than AI-driven, real-time decision systems. Similarly, Soil Health Cards, remote sensing for crop area estimation, and weather-based agromet advisories have existed for years, but they functioned as standalone silos, not as a unified decision-support ecosystem.
India had announced launch of the DAM in FY22 for five years and approved an outlay of ₹2,817 crore in September 2024. The scheme is proposed to be extended till FY30 with an outlay of over ₹7,500 crore.
The mission, with the Department of Agriculture as its nodal agency, envisages creation of a digital public infrastructure (DPI) for agriculture, including AgriStack, the Krishi Decision Support System (KDSS) and a comprehensive soil fertility and profile map, to enable a robust digital agriculture ecosystem in the country.
The government had launched IndiaAI Mission in March 2024, with a budget over ₹10,372 crore. It aims to build a national AI ecosystem by supporting computing infrastructure, data platforms, indigenous models, and AI adoption across sectors.
The use of AI to boost agriculture assumes significance given that the sector and its allied segments account for around 18% of India’s gross domestic product (GDP), with nearly 46% of the country’s workforce dependent on it.
“Investments in digital infrastructure such as rural broadband, satellite imagery, sensors and drones will be critical to scaling these technologies,” said the first official cited above, requesting anonymity.
The government takes the final call on several budget proposals closer to its presentation date, which is 1 February.
Queries sent to the spokespersons of the ministries of finance and agriculture on 8 January remained unassured until press time.
The budget may also announce financial assistance to states for onboarding farmers on the Virtually Integrated System to Access Agricultural Resources (VISTAAR), a unified platform for farmers to access reliable, real-time info on crops, markets, schemes, and climate-smart practices.
This will be done by leveraging agri-tech startups and AI to offer personalized advice through chats to improve farmer livelihoods and drive sustainable agriculture. Farmers will also be able to ask questions and receive instant responses in local languages through voice and text, supported by Bhashini, the AI-powered language translation platform aimed at breaking language barriers across India.
Farmers are likely to be onboarded on the scheme next month, the officials said.
“The mission is expected to strengthen food security by improving crop forecasting, enabling early warning systems, and reducing yield losses through data-driven farm planning,” said Binod Anand, a sector expert and a member of the government’s panel on minimum support prices.
Experts said AI has the potential to address long-standing productivity and information gaps in Indian agriculture, provided digital tools are deployed at scale with strong institutional support.
“The real opportunity lies in translating complex data such as weather patterns, soil health, crop imagery and market signals into simple, actionable guidance delivered in real time. To move from pilots to widespread impact, India will need strong data infrastructure, last-mile access and coordinated public-private collaboration to ensure these solutions are inclusive, affordable and scalable,” said Sushma Vasudevan, managing director and partner, agriculture practice at Boston Consulting Group.
“By combining satellite imagery, weather intelligence and AI-driven crop models, stress related to water, nutrients or pests can be identified well before it becomes visible in the field. This enables timely and precise interventions, resulting in 15-20% higher yields and up to 30% lower input costs, while strengthening resilience to climate volatility without adding technological complexity for farmers,” said Rajesh Shirole, co-founder and chief operating officer of MapMyCrop, an AI- and satellite imagery-based precision agriculture platform focused on comprehensive field monitoring.
The government has been increasing its focus on agriculture. Budgetary outlay for the sector rose from ₹1.18 trillion in FY24 to ₹1.41 trillion in FY25 (revised estimate) before easing marginally to ₹1.38 trillion in the budget for FY26.