Artificial intelligence becomes farmers' 'engineer'

Artificial intelligence is not only automating one of humanity's oldest professions — it is also reducing the cost of the engineering expertise that small and medium-scale farmers have had to pay for over the years.

According to information compiled by Anadolu, as digitalization rapidly becomes a part of the agricultural sector, AI is being used across a wide range of applications, including animal health monitoring, disease diagnosis, irrigation automation and satellite-based crop tracking.

Some farmers are taking their experience to a new level by integrating AI into their work, delegating time-consuming tasks to the technology while focusing on increasing yields.

Sensors, robotic systems, satellite imagery and weather data now allow real-time monitoring of feed consumption, milk production and plant development, while image analysis enables early detection of crop diseases and faster decision-making.

From leased cows to highly automated facility

Paul Windemuller, a US-based farmer and the first in his family to enter agriculture, uses AI to process and evaluate data across his livestock operation.

Starting with 30 leased cows in 2014, he has since built the business into an AI-assisted facility of hundreds of animals using robotic milking systems.

Windemuller focuses on closing the gap created by the lack of years of hands-on animal observation — the kind of intuitive expertise traditional farmers develop over time — using sensors, data analysis, robotic systems and AI-powered tools.

Cows on the farm are tracked via sensor systems, a local weather station continuously records climate metrics, and milk quality and shipment information is managed through a separate online portal.

Windemuller once had to spend hours each morning working through spreadsheets to monitor his herd, but he has now automated the process using a multi-agent AI system built on Google's Gemini model.

The system calculates how hot and humid weather conditions reduce the cows' feed intake, assesses the impact on herd performance and milk quality, and delivers a daily summary.

Experienced farmers' engineer: artificial intelligence

Hiroki Tomiyasu, who has been farming in Japan for around ten years, grows broccoli, green onions and soybeans across approximately 100 hectares (247 acres).

Having integrated AI into his operation, he photographs black spots on his broccoli and sends the images to OpenAI's ChatGPT model to identify possible diseases.

Rather than purchasing an expensive GPS auto-steering system, Tomiyasu also uses AI to learn how the technology works, and draws on AI assistance to learn about the tools and open-source resources available for agricultural applications, allowing him to build the systems he needs at a much lower cost.

Using a system that draws on his own field data, receives satellite data and regularly collects metrics such as the Normalized Difference Vegetation Index, Tomiyasu can examine his fields through maps derived from satellite imagery.

Having built a system that connects fields, workers, pesticides, fertilizers, sensors and tasks, he describes the AI he uses in these various ways as "an ultra-talented engineer always by your side."