We have researched the use of AI in sustainable agriculture over the past three years, speaking with farmers and IT providers to understand their challenges and experiences. Our conversations reveal how farm organizations integrate traditional farming knowledge with AI-based tools for climate-smart crop management and sustainable agricultural outcomes. This Advisor presents three exemplar cases (pseudonyms have been used for the real farm names).
1. Organic Orchard
Organic Orchard is located in the western part of India. This farm grows fruit and operates a plant nursery. The owner is passionate about organic agriculture and promotes organic farming practices that prioritize soil health and fertility.
In 2021, Organic Orchard implemented an AI-based disease-detection app to support low- or no-chemical fruit plantation management. Using the application involved uploading photos of infected plants to the app to receive AI-generated diagnoses of potential diseases and nutrient deficiencies, along with disease management recommendations.
The owner explained: “The app suggests everything: chemical management, biological management, and mechanical management. Our focus is on organic farming, so whatever information is available regarding organic farming, we apply that.” Once Organic Orchard received information on nutrient deficiencies from the app, workers supplemented the app’s recommendations with traditional ways of fertilizing (e.g., oilseed cake to treat nitrogen deficiencies).
Organic Orchard actively created community awareness and promoted the benefits of the app, including increased productivity and reduced chemical application. However, some farm workers and others in the community were wary of using the app. They perceived it as a threat to their long-held beliefs and local farming practices because it did not provide information on fruits commonly grown in the area. These perceived threats were exacerbated by a lack of engagement from government experts who were responsible for advising farmers on best practices for crop management and pest and disease control.
One participant pointed out: “Technology should be made to reach farmers’ fields and is the responsibility of the extension workers. But you know about the government officers (extension workers); they do not come out of their office rooms.”
To build confidence in the technology, Organic Orchard’s owner organized meetings to share his experience of integrating technology with traditional knowledge and practices. He explained: “Because we work in the fields, we have an idea about the weather. We know pest attack is probable when the clouds gather. So, we already know, and we get confirmation through the app, and we feel that we are going in the right direction.”
Over time, Organic Orchard combined traditional practices like observing atmospheric events with the AI-based tool for disease detection to improve decision-making and support climate-resilient agriculture (CRA) by limiting the application of chemical fertilizers and promoting organic farming to restore soil health.
2. Crop Farm
Crop Farm is situated in the hilly northern region of India, where it grows commercial trees, wheat, and seasonal vegetables. In the past, Crop Farm was successful in applying traditional knowledge gained from observing atmospheric conditions and estimating rainfall. However, changing weather patterns and decreased precipitation increased water problems in the already water-scarce area, rendering traditional knowledge insufficient for effective crop management.
For example, Crop Farm traditionally fertilized its crops 30 days after plantation, but shifting rainfall patterns affected fertilization efficiency, causing low yields. Similarly, the farmer followed the traditional method of harvesting wheat at the end of winter and leaving the harvested wheat grains in the fields to dry. Recently, unpredictable weather and sudden rainfall frequently damaged the grains.
Crop Farm began using AI-based weather-prediction apps to get rainfall estimates in an effort to better manage water levels in the fields. The goal was to better prepare the fields for fertilization, protect threshed grains from damage, and arrange for alternative irrigation sources as required. One farm worker reported: “At times, after threshing, the wheat was kept in the fields, and suddenly it would rain at night, and the wheat would be wet and damaged. Now, we work by watching the forecast. Harvesting and threshing are mostly done after consulting the weather predictions.”
During the implementation and use of the apps, Crop Farm encountered issues due to the remote location of the village. Lack of Internet connectivity and technology infrastructure (e.g., weather stations) created problems with weather-prediction accuracy and efficacy for the apps. Because of these technical barriers, Crop Farm returned to using traditional knowledge of weather predictions for managing farm activities. A farm worker pointed out: “When the temperature has risen to 48-49 degrees Celsius, then usually we get rain after two to three days to lower the temperature. So, we have some of these ways to predict the weather.”
Based on traditional knowledge and observations of the natural rain cycle, Crop Farm’s owners understood the importance of capturing and storing rainwater for irrigation in case of delayed monsoons. They combined their experience and reasoning with app-based weather predictions to adapt to evolving weather patterns resulting from climate change and prioritized rainwater harvesting, as one of the workers explained: “For a long time, there used to be much rain in November–December here, but this year November [and] December were dry, and it only rained in January. So, I have built a temporary dam under my house, where the rainwater gets collected, then the stored water is used for irrigation.”
This combined learning helped them better understand changing weather patterns, implement sustainable and efficient water management methods, and reduce soil erosion.
3. Cereal Farm
Cereal Farm, a family farm in the northeastern region of India that grows cereals, also faces the impacts of climate change. Once known for its high fertility and ample rainfall, the region now experiences droughts. Climate change has led to unpredictable weather patterns, sudden and delayed rainfall, and hailstorms — leading to reduced productivity and crop quality.
To tackle these issues, Cereal Farm deployed an AI-based crop advisory app that provides weather predictions, planting and harvesting recommendations, and disease-detection and remedial recommendations. Simultaneously, as recommended by the app, the owners switched to drought-resistant hybrid maize seeds to enhance productivity and use.
However, farmers expressed concerns about problems like unreliable weather predictions, failure of suggested recommendations for fertilizer applications, unsuitability of hybrid seeds to local conditions, and loss of local seed varieties. One farmer shared: “Our ancestors saved some of the harvest to be used as seeds in the next season. When the technology came, hybrid seeds were suggested to increase crop yield. But when harvesting season came, we realized the seeds hadn’t grown properly. So, people switched from the hybrid seeds to the native seeds they used to collect every year, which led to the betterment of seed quality every year.
Despite using the app, they continued to rely on their intuition, experiences, and traditional knowledge. One farmer said: “Traditional knowledge has its own importance, but when it comes to dealing with climate change, it will be important to use technology and take advantage of it. Both should be considered side by side.”
The combination of traditional knowledge with recommendations from the crop advisory app was the best strategy for planting and harvesting decisions at Cereal Farm. As another farmer put it: “The things that have been carried out through generations about what should be planted in which season, how the field should be prepared, and how things should be done, these are the traditional knowledge. What new do we add to this? When will it rain? Should we irrigate or not? When should the crop be harvested, and where should the products be sold? This is what is new, and with app tools, we get to know how these should be done.”
[For more from the authors on this topic, see: “An Integrated Approach to Sustainable, Climate-Resilient Agriculture.”]
