How AI is Reshaping Agricultural Innovation
For decades, we’ve had the most talented scientists in the industry. Now, AI is making them even more impactful. From accelerated breeding cycles to opening up new income sources for farmers — AI is helping transform the future of agriculture.
AI plays a pivotal role for our company in revolutionizing agriculture. We use AI and data science to develop better seeds, more desirable plant traits and bring new crop protection solutions to market faster. AI is the foundation for agronomic recommendations that support crop management decisions such as when to plant and irrigate, that is tailored to the farm so that more can be produced from the same piece of land.
Three Ways AI is Revolutionizing Agriculture
From faster product development to opening up new income sources for farmers, AI’s transformational potential is uncapped. Here are three ways AI is already revolutionizing agriculture today.
Discovering New Seeds Faster
Long before the world awoke to the potential of AI, we’d already built the most powerful and dynamic precision breeding platform in the industry. But when the unparalleled quantity and accuracy of our data met advanced genomics and artificial intelligence, things accelerated quickly.
Our breeders now use machine learning and digital twin technology to write new genetic combinations and anticipate a plant’s performance in thousands of micro-level climatic and soil conditions, helping them design and create crops that are even better matched to meet growers’ needs.
Historically, a single breeding cycle took five or six years to complete, but our precision breeding program powered by AI can complete that cycle in only four months — which will more than double our rate of genetic innovation by 2030.
Generative AI at Bayer
The award-winning E.L.Y. expert GenAI system is up-leveling agronomists in their daily work. We’ve been training a large language model (LLM) with years of internal data, insights from thousands of trials within its vast testing network, and centuries of aggregated experience from Bayer agronomists around the world.
The result is an expert system that quickly and accurately answers questions related to agronomy, farm management, and Bayer agricultural products. Instead of a time-consuming process, the intuitive system responds to natural language and can generate expert information within seconds. Validated by farmer-facing employees, the pilot is already unlocking productivity for Bayer teams in the United States while significantly outperforming out-of-the-box LLMs currently serving the agricultural market.
Bayer internal teams are exploring this technology and testing multiple scenarios where large language model capabilities could add value and increase productivity through the ability to interact with farm data in a natural way.
Discovering New Crop Protection Faster
We're also using AI to help reduce the environmental impact of crop protection products — a commitment that’s long been part of our mission.
Our scientists have developed a new process for uncovering crop protection molecules at an incredible rate. We call this innovative approach CropKey. With the help of AI, we can test a multitude of crop protection molecules virtually, exploring far more potential candidates than before. We use predictive modeling to check safety and sustainability, like how the chemical breaks down in soil and its effects on other organisms. It’s helping us bring new products to market, like a novel fungicide for fruits and vegetables and icafolin, a new broadacre herbicide molecule, within the next 10 years.
Biofuels: Opportunities Beyond the Farm
Beyond the farm, AI is unlocking solutions across transport and energy — especially sustainable biofuels. Bayer’s goal is to help decarbonize the transportation sector and to deliver regenerative agriculture solutions through the investment and development of intermediate oilseed crops to meet the demand of the growing renewable diesel and sustainable aviation fuel (SAF) markets.
AI algorithms accelerate variety selection, optimize rotations, and improve logistics and processing to deliver real carbon reductions without competing with food production. Paired with precision breeding and smarter crop protection, these tools form a rapid feedback loop that preserves genetic gains, sharpens breeding predictions and scales impact across the value chain.
Bayer has announced the launch of newgold® seed in the United States and Canada in 2026, its first multi-crop seed brand developed specifically for low-carbon intensity crops such as camelina and winter canola.
Growing Seed More Efficiently
By being the leading provider of seeds to farmers around the world, we’re also the largest producer of seeds on the planet. So we have to do things efficiently. We’ve turned to advanced data science to grow seeds of new hybrids and varieties in our production fields. The AI models help us decide where to plant and at what density, when to plant, when to irrigate, and when to harvest so more can be produced from the same piece of land, while cutting down on resources. By using these models to inform farming decisions, we’ve been able to increase the productivity of our fields by over 30%.
Predicting the Supply Chain
Given the volatility and complexity of our crop protection supply chain, we use machine learning to help us identify vulnerabilities and understand their impact and work around them. We can virtually see into the future and improve our production, procurement and transportation, considering different demand scenarios. We’re also looking into how these models can improve our active ingredient supply chain.
Now let’s look at how AI can be deployed by farmers.
AI on the Farm
FieldView is Bayer's flagship digital farming platform managing more than 220 million acres in over 20 countries. And it’s now putting AI in the hands of all those growers. This shift in on-the-farm capability can make growers more efficient, successful, and sustainable.
Here’s how it works. First, in applicable regions, the app offers seed scripts, an advanced feature that uses machine learning with satellite images or a farmer's crop yield data to divide a field into different management zones. Next, predictive models suggest how densely to plant the crop in certain areas based on the grower’s specific yield or profit goals.
Through these advancements on and off the farm, Bayer is improving efficiency and productivity while paving the way for a more sustainable and responsive agriculture industry.