Artificial intelligence is often associated with chatbots, content creation, coding and other high-tech applications. But in India, AI is also being used to solve much more basic, everyday problems.
Across rural India, AI is finding applications in agriculture, dairy farming and pest management. These systems are helping farmers access useful information through voice calls, regional languages and basic mobile phones.
This is important because many rural users may not have smartphones, reliable internet connections or the digital skills needed to use complex applications. Instead of expecting users to adapt to new technology, these AI systems are being designed around the way people already communicate and work.
AI that works without a smartphone
One of the biggest challenges in taking advanced technology to rural areas is access. A smartphone, a stable internet connection and the ability to read and type are often taken for granted by digital services. India’s rural AI applications are taking a different approach.
Read More | AI Safety vs AI Race: From Jacob Coxon to Trump’s AI Czar — Where Is This Story Heading?
Some platforms allow farmers to simply make a phone call and speak in their local language. Others can run directly on low-cost devices without needing a constant internet connection.
This makes AI more accessible to people who may otherwise be left out of the digital economy. The technology can provide information on everything from livestock health and crop diseases to weather conditions and market prices.
AI Sarlaben: Bringing AI to dairy farmers
India is the world’s largest milk producer, with a large part of its dairy industry supported by small farmers. For these farmers, rising input costs, changing weather conditions and livestock diseases can directly affect their income.
To help address some of these challenges, the Gujarat Co-operative Milk Marketing Federation, commonly known as Amul, introduced AI Sarlaben. What makes the system different is that farmers do not need a smartphone or a dedicated application to use it.
Read More | India’s Renewable Energy Problem: Why Green Power Is Going to Waste
More than three million dairy farmers use basic feature phones to interact with the system. They can call a designated number and speak in their local Gujarati dialect. There is no app to download and no complicated interface to learn.
How does AI Sarlaben work?
The system is built using a large collection of dairy-related data. This includes more than two billion historical milk procurement transactions and data from over 30 million cattle. When a farmer calls for help, the system can provide information related to animal health, breeding cycles, government subsidies and feeding schedules.
For small dairy producers, having access to this information can help them make decisions about their animals and daily operations. The system is also significant because many of the farmers in the dairy co-operative network are women. Providing information directly to them through a device they already use can reduce their dependence on intermediaries.
Read More | India’s SIM Card Limit Explained: Why the Limit Is 6 in J&K and Northeast
MahaVISTAAR and Vasudha AI: Making farm advice more local
Agriculture depends heavily on timing. A farmer may need to sow a crop before a particular weather event or act quickly when a pest begins spreading. The Maharashtra government’s MahaVISTAAR platform uses AI to provide agricultural advice through Vasudha, a voice-based AI assistant. Farmers can interact with Vasudha in their native language. The platform is designed to provide more than general agricultural information.
Advice based on the farmer’s own land
MahaVISTAAR uses a feature called the Farm Diary, which is linked to the farmer’s AgriStack identification. This allows the system to use information about the farmer’s location, soil and crops. As a result, the advice can be tailored to a particular farm rather than being based only on information for an entire state or region.
Read More | AI Tokens Explained: What Are Tokens and How Do They Work?
For example, the system can provide weather forecasts, market information and warnings about crop pests. If a pest is identified in a nearby district, the system can also warn farmers whose crops may be at risk. This type of local information can help farmers make decisions such as when to sow or harvest their crops, particularly when weather patterns are difficult to predict. The approach is also being used as a reference for similar agricultural technology projects outside India, including developments in Ethiopia.
KissanAI and Dhenu: Building AI specifically for agriculture
General-purpose AI models are designed to handle a wide range of subjects. But agriculture has its own language, terminology and local knowledge. Farmers may need advice about specific soil conditions, fertiliser quantities, crop diseases or changes in the appearance of a plant. Generic AI systems may not always understand these requirements accurately. This is where KissanAI’s Dhenu model comes in. Dhenu is designed specifically for agriculture and the needs of farmers in the Global South.
Why agricultural data matters
Instead of relying mainly on general information from the internet, Dhenu was trained using millions of agricultural documents, research papers and local farming practices. The platform also focuses heavily on voice interaction. Farmers can ask questions in spoken Hindi and other regional dialects instead of typing a query or reading a long advisory document.
For example, a farmer can ask about soil health, the right amount of fertiliser or a sudden change in a crop. Dhenu processes the question using its agricultural knowledge base and provides conversational guidance. This could reduce farmers’ reliance on informal sources of advice, such as pesticide sellers, who may have commercial interests when recommending products.
Wadhwani AI Cotton Ace: AI that works offline
Not every rural area has a reliable mobile network. This creates another challenge for AI systems that normally depend on cloud computing. Wadhwani AI’s Cotton Ace takes a different approach by bringing AI directly onto the device. The system was developed to help cotton farmers monitor the pink bollworm, a pest that can seriously affect cotton crops.
Read More | Mumbai’s Data Centre Boom: How Much Can the City Take?
How does Cotton Ace work?
Farmers place pheromone traps in their cotton fields and take photographs of them. The AI system analyses the images and counts the pests it identifies. It then uses established entomological rules to assess the level of infestation.
The technology can work without an internet connection. This is possible because the AI model has been made small enough to run on a low-end device. The model was compressed to less than five megabytes, allowing it to perform its analysis directly on the device.
This also means farmers do not have to repeatedly upload large images over unreliable mobile networks. It can help reduce battery use as well, which matters in areas where electricity supplies can be inconsistent.
Turning pest detection into action
The system does more than identify pests. Based on the level of infestation, it provides recommendations on when to spray pesticides and how much to use. This can help farmers respond to a pest problem when action is actually needed, rather than spraying chemicals in advance or waiting until the crop has already suffered serious damage.
Read More | What Happens When AI Gets Permission to Spend Your Money?
What makes these AI systems different?
The examples of Sarlaben, MahaVISTAAR, Dhenu and Cotton Ace show that AI does not always need to look like a chatbot on a smartphone. Each system is designed around a specific rural problem. Sarlaben uses basic phones and voice calls to support dairy farmers.
MahaVISTAAR and Vasudha use local information to provide more personalised agricultural advice. Dhenu focuses on agricultural knowledge and regional languages. Cotton Ace brings AI directly onto a device so that farmers can use it even when internet connectivity is limited. The common idea is simple: the technology is adapted to the user, rather than forcing the user to adapt to the technology.
From advanced AI to everyday problems
These applications show how advanced computing can be used to address practical problems faced by farmers and dairy producers. A farmer does not necessarily need to understand how an AI model works. What matters is whether the technology can provide useful information at the right time and in a form that is easy to access.
Read More | What Happens When You Get Rich and Let Technology Run Your Life?
For rural users, that could mean making a phone call in their own language, receiving advice based on their own farm or using an AI system that works without an internet connection. This approach could make AI more accessible to communities that have traditionally faced barriers related to language, literacy, hardware and connectivity.
The bigger lesson is that the impact of AI is not limited to the latest smartphones or high-speed internet. In rural India, some of its most useful applications are being built around basic phones, voice and local knowledge. By putting practical, data-based information within easier reach of farmers, these systems are changing how technology can support agriculture and rural livelihoods.
Indrani Priyadarshini is a journalist and editorial professional specialising in technology, artificial intelligence, smart cities, green energy, and digital transformation. With over four years of experience in tech journalism and digital media, she is known for turning complex industry developments into clear, engaging, and insightful stories. Her expertise spans reporting, editorial strategy, digital publishing workflows, and in-depth coverage of emerging technologies shaping the future.
