Experts Warn That AI Gains May Stall Without Funding
AI is reshaping how farmers use agrichemicals, leading to safer, more effective, and more sustainable practices. But experts say these advances depend on stable research funding and reliable data.
At a recent House subcommittee hearing, researchers and industry leaders shared how AI has transformed agricultural research. Brian Lutz from Corteva Agriscience said AI has helped discover pest-targeting molecules faster and more affordably. The technology is also used to optimize production and advise farmers on fungicide use.
“We might think of crop protection molecules as ‘keys,’ and those ‘keys’ are intended to fit very specific targets in pests—usually proteins,” said Lutz.
AI is helping reduce agrichemical use. At the University of Illinois, AI trained on satellite images identified red crown rot in soybeans. It allowed farmers to target only affected areas, cutting chemical use by up to 75%.
But experts say innovation depends on strong support for university research. Daniel Swale of the University of Florida said, “A commitment in fundamental science by the federal government is critical for the US to remain at the leading edge of innovation.”
Current proposals to cut National Science Foundation funding by over 50% threaten this progress. Also, removal of climate data from USDA websites limits the information needed to train AI models.
Lutz added that, without data, tools like fungicide timing models might stop working. Lawmakers also debated the chemical approval process. While some pushed for faster reviews, Rep. Zoe Lofgren warned of health risks in farming communities.
Despite these challenges, researchers say continued investment in science and data is key to keeping AI innovation in agriculture moving forward.