In New Delhi, India is striving to achieve a leading position in global technological innovation, and its agricultural sector is demonstrating the potential of this transformation.
Artificial Intelligence (AI), previously confined to specialized fields, is now being applied to address one of agriculture's most persistent challenges: predicting unpredictable conditions.
AI models, using data from soil moisture sensors and local weather patterns, provide Indian farmers with an early warning system, modernizing agriculture, enhancing resilience to climate change, and promoting data-driven and inclusive farming practices.
One example is Microsoft's partnership with ADT Baramati, which is transforming sugarcane farming in Maharashtra by bringing high-tech AI to the fields.
Through Microsoft's AI technologies, including Azure Data Manager for Agriculture, FarmVibes.AI, and the Agripilot.ai app, ADT Baramati's "Farm of the Future" project empowers farmers to increase sugarcane yields, use less water and fertilizers.
These AI-driven insights, delivered in local languages through a mobile app, are helping to bridge the digital divide, promote sustainable farming, and attract a new generation to agriculture.
"When we talk about agriculture, the first thing that comes to mind is the unpredictability that farmers face," said Himani Agrawal, COO of Microsoft India & South Asia. "There is a lot of available information, such as satellite data or soil health data, but this information is complex and not readily accessible to farmers."
Agrawal added, "We have worked with ADT Baramati to make this information accessible to sugarcane farmers, through technologies like Azure Data Manager for Agriculture, FarmVibes.AI, and Azure open AI models. This allows farmers to easily access and understand the complex information, identify patterns, and receive relevant recommendations through a mobile application or WhatsApp in their local language."
This AI-driven transformation is transforming farming from a reactive struggle into a predictive science, enabling targeted interventions that save crops, increase output, and reduce costs.
AI is also being used to combat pest attacks in fields. This transformation is enabled by AI's ability to process vast amounts of real-time data.
By integrating information from IoT-based soil sensors and climate monitors, AI models can identify the specific conditions, such as humidity levels or wind directions, that precede pest outbreaks.
This allows farmers to opt for targeted interventions instead of traditional blanket pesticide spraying, which is expensive and environmentally damaging.
This is particularly important given that, according to Niti Aayog, the cost of cultivation, including labor and inputs, has increased by 20-40% since 2021.
The impact of these technologies is already visible. The Saagu Baagu project, a joint initiative of the Government of Telangana and the World Economic Forum (WEF), has significantly improved the value chain for over 7,000 chilli farmers.
Farmers participating in the program have seen a 21% increase in chilli yields per acre, a 9% reduction in pesticide use, a 5% decrease in fertilizer usage, and an 8% improvement in unit prices due to quality enhancements.
Contrary to the common perception that technology intervention would raise costs, AI actually offers the potential to reduce overhead and operating costs.
"Imagine using micro sensors in the soil to understand the soil's content, moisture levels, and nutrient levels, and then correlating this with weather data," said S Anjani Kumar, Partner, Deloitte India. "This allows farmers to predict what will happen in the next 3-4 days, determine the optimal time to sow seeds, and harvest crops, and even use drones for spraying. All of this can be done at a fraction of the cost."
Previously, yield improvement required expensive machinery and overheads, but small-scale farmers lacked the capital needed to make such investments efficient on limited rural acreage.
AI makes it possible to do this on a per-hectare basis, Kumar explained.
AI also helps with post-harvest functions, assisting farmers in selecting markets where they can get the best price for their produce by studying trends and patterns, Kumar noted.
"This eliminates the guesswork and uncertainty," he said. "Farmers can now access data-driven information on where they can get the best prices."
The AI-led transformation extends far beyond the planting season. With India losing about 15-20% of produce (as per Niti Aayog) to post-harvest losses due to poor storage and transport, AI is stepping in to optimize the value chain.
Innovations include AI-driven machines that automatically sort and grade produce by size, shape, and color, and digital twins, which are virtual replicas of fields and crops that allow farmers to simulate different scenarios and outcomes before they even get into sowing.
As the India AI Impact Summit nears, and the nation gears up to showcase applications that bridge the gap between digital experimentation and real-world utility, these use cases serve as a powerful reminder that the "Intelligent Revolution" is no longer a distant dream – it is already helping Indian farmers secure their livelihoods and the nation's food security.