AI for Agriculture

Farmers and agricultural producers are increasingly turning to AI, using it to enhance productivity, efficiency, and food security through more accurate yield predictions, pest and disease detection, food loss and waste reduction, and improved scale management strategies that assist farm, forest, and ranch managers in decision-making. There are over 200 AI-based agricultural startups in the U.S. alone, helping farmers decrease water consumption, improve food quality, and effectively manage pest control.

Helping Farmers Cut Emissions and Improve Soil Health

Andes

Andes is using AI and biotechnology to help farmers cut emissions and improve soil health. Their microbial seed treatments work with crops like corn, wheat, and soybeans to capture atmospheric carbon dioxide and lock it into the soil as stable inorganic carbon. AI helps analyze soil and environmental data to optimize applications, ensuring farmers get the most impact without changing their existing practices. Through the Andes Carbon Program, farmers can even earn payments per treated acre, while Andes provides the inoculant and verifies carbon capture through soil sampling and audits.


Cutting Herbicide Use with Real-Time Weed Detection

John Deere’s See & Spray

John Deere’s See & Spray uses camera vision and machine learning technology to differentiate in-season crops from weeds and only sprays the weeds. See & Spray applies herbicide only where needed, reducing the growth of herbicide-resistant weeds and promoting cost efficiency for farmers. This technology allows growers to strategically use herbicides for weed control, which, in turn, saves the grower money, time, and resources. During the 2025 growing season, the technology was used across more than five million acres, and customers cut non-residual herbicide use by an average of nearly 50%, saving close to 31 million gallons of herbicide mix in a season marked by heavy weed pressure and frequent rains. With See & Spray, farmers spend less on inputs, and less chemical reaches the surrounding environment.

 

Helping Farmers Irrigate with Less Water

Amazon and Arable’s Smart Irrigation Project

Amazon is working with agricultural technology company Arable and Mississippi State University to equip farmers in the Mississippi River Valley with sensors that run on AWS, analyzing soil moisture, weather conditions, and crop water needs in real time. Machine learning models process historical patterns and deliver plain-language irrigation recommendations to a farmer’s phone, and the project is expected to reduce agricultural water withdrawals by 150 million gallons a year, enough to supply more than 1,600 Mississippi households.