Responding to a question in the Lok Sabha, the Government of India highlighted its intensified efforts to integrate Artificial Intelligence (AI) and drone technology into agriculture to boost productivity and minimise crop losses.
The Ministry of Agriculture and Farmers Welfare is leveraging AI across several domains from crop health monitoring to pest surveillance in order to tackle challenges such as climate change, crop management, and access to timely agronomic advice.
A total of 2,622 drones have already been distributed under various government schemes, as per the recorded response.
Exploratory Stage
S V Suresha, vice chancellor, University of Agricultural Sciences, Bangalore, said that while the medical sciences are already seeing significant applications of AI, agriculture remains in its early, exploratory stages.
One of the flagship tools mentioned is Kisan e-Mitra, a voice-based AI chatbot that answers farmer queries related to schemes like PM Kisan Samman Nidhi in 11 Indian languages. With a current daily load of 20,000 interactions, it has answered over 95 lakh queries so far.
However, when AIM ran tests, the tool failed to function. Despite multiple attempts in different languages, it repeatedly displayed an “internet error,” quashing all the claims around its success. (image attached)
Another tech intervention which employs AI and machine learning to detect pest outbreaks early is the National Pest Surveillance System. Over 10,000 extension workers use it to photograph and identify pest infestations, enabling timely solutions.
The system currently supports 61 crops and detects more than 400 pest types. AI also plays a role in satellite-based crop mapping and crop-weather monitoring, providing insights for improved planning and yield forecasting.
Drone Didi and Arya.ag
To complement AI tools, the government is promoting drone use through subsidies under the Sub-Mission on Agricultural Mechanisation (SMAM). Institutions like ICAR, KVKs and SAUs can get up to ₹10 lakh per drone for field demos. Farmer producer organisations (FPOs) receive up to 75% subsidy, while small, marginal, SC/ST, women, and Northeast farmers are eligible for 50% subsidy (up to ₹5 lakh). Other farmers can avail 40% subsidy (up to ₹4 lakh).
Suresha noted that “not all Krishi Vigyan Kendras (KVKs) are equipped with drones. It’s still in the exploratory stage.”
Launched with an outlay of ₹1,261 crore for 2023–26, the ‘Namo Drone Didi’ scheme aims to distribute 15,000 drones to Women SHGs, making them drone service providers and agri-tech entrepreneurs. The scheme offers up to 80% subsidy on drone packages (maximum ₹8 lakh), with SHGs contributing the remaining 20% through internal funds or low-interest loans under the Agri Infra Financing scheme.
In the first year (2023–24), 1,094 drones were distributed by lead fertilizer companies using their internal resources. Of these, 500 drones were specifically allotted under the Namo Drone Didi initiative.
The government confirmed that it is working on a concrete expansion plan to deploy AI and drone technologies in more districts. With targeted incentives and schemes, the aim is to scale adoption, especially in underserved areas, and enable data-driven, precision farming practices.
While AgriStack is still in the rollout phase, parts of its vision are already operational on the ground. Platforms like Arya.ag are actively using digital IDs, AI-based quality checks, blockchain traceability, and satellite-linked crop data to power services like credit access, warehousing, and insurance.
“We use AI across key stages of storage, grain grading, credit access, farm monitoring, and market linkage,” says Prasanna Rao, co-founder and CEO of Arya.ag. When a farmer stores his/her produce with Arya.ag, the system assigns a digital identity to each bag of grain. AI tools assess its quality and estimate its value in real time.
“As part of our AI-led grain quality initiative, we have introduced computer vision models and ML techniques that replicate expert grading at scale. Based on this information, credit decisions are made quickly, using only the farmer’s KYC,” Rao said. So far, more than ₹12,000 crore in loans have been disbursed through this system.
Satellite data and AI help the company monitor over one million farms. Their models observe changes in vegetation, signs of water stress, and early indicators of pest outbreaks. These insights are shared through the AryaShakti app, which delivers simple, local-language advisories to farmers, FPOs, and MSMEs. In climatically vulnerable regions like Bundelkhand and Marathwada, this information helps collectives plan procurement and manage inventory more effectively.
“To enhance security, our warehouses are also equipped with AI-enabled surveillance systems that track activity in real time,” Rao added.
This enables a model of storage that is scientific, safe and close to home. Close to 40% of Arya.ag’s borrowers are new to formal finance. Many belong to women-led collectives or smallholder-run FPOs in remote areas.
AI also supports commerce. It helps match stored inventory with buyer demand, tracks price movements, and provides full visibility into the condition and location of commodities, said Rao.
Agriculture involves many moving parts. Weather, logistics and market conditions often shift without warning. AI offers early signals, which help reduce guesswork and friction.
“We do not expect automation to replace judgement. Instead, we design technology to offer clarity in moments when choices are difficult,” Rao added.
Challenging Landscape
Other players like Kissan AI are also seeing enthusiastic adoption of generative AI for agriculture. “By working directly with agribusinesses and farmers and learning from every partnership, we have discovered a strong enthusiasm for GenAI solutions such as vernacular voice-based agronomy advice, AI-driven product discovery, and agents that empower field and sales teams,” said Pratik Dessai, founder of Kissan AI.
“Encouraged by government initiatives like the IndiaAI Mission, this collaboration has placed Indian firms at the global forefront of agricultural AI, leading in domain-rich datasets, multilingual model adaptations, and scalable deployments.”
While most farmers are not yet utilising AI tools in their day-to-day practices, the future looks promising for AI-driven solutions, especially for a new generation of farmers. “Farmers are not using hardcore AI in farming at present,” said Ritutaj Sharma, founder and CEO, Zetta Farms, adding, “but I see a future for chatbots as young people without much background or traditional knowledge about farming turn to agriculture.”
India’s agricultural landscape, marked by small and fragmented landholdings, presents its challenges. “When even mechanisation is difficult, AI and drone implementation at the level of individual farmers will take time,” Suresha pointed out. According to him, a more realistic path would be to roll out these technologies through collectives, large farms, or farmer-producer organisations that have the capacity to afford and manage them.
The post Where Does India Stand in Leveraging AI for Agritech? appeared first on Analytics India Magazine.
