Webinar “AI in Agriculture: Transforming the Food System from Data to Decisions to Action”

Webinars

A detailed look at how AI is already being deployed across U.S. agriculture — from precision spray systems reducing herbicide use by half, to acoustic sensors detecting disease before symptoms appear — and the policy choices that will determine who benefits from these technologies.

September 14, 2026
By Communications Office

Presented by Dr. J. Alex Thomasson · Professor & Director, Agricultural Autonomy Institute, Mississippi State University

Session Highlights

Precision Application John Deere’s See & Spray technology — tested by the University of Arkansas — can reduce herbicide applications by roughly 50% by identifying and targeting individual weeds in real time.

Animal Health Monitoring Acoustic AI systems can detect respiratory disease in swine before clinical symptoms appear, enabling early intervention and reducing the need for broad antibiotic use.

Physical AI in the Field Robotic harvesters that estimate fruit ripeness, plan a collision-free path, execute a grasp, and adjust grip force in real time — the complete perception-to-action pipeline running on a farm.

Data Ownership & Policy Who owns the data generated by farm equipment? Current AI subscription models often don’t cover operating costs. Policy frameworks for informed consent and equitable access are still unresolved.

Adoption Landscape Adoption is moving fastest in production machinery and food processing. AI is already deployed in per-unit food inspection — a domain where 100% coverage was previously impractical.

Q&A: Edge vs. Cloud, Biosecurity, Resources Attendees asked about edge computing tradeoffs, satellite monitoring accuracy, risks from agentic AI in agriculture, and whether data centers compete with farms for water and energy.

About the Presenter

Dr. J. Alex Thomasson
Professor & Director, Agricultural Autonomy Institute · Mississippi State University

Dr. Thomasson is a biological and agricultural engineer specializing in agricultural automation, machine vision, and remote sensing. He is the lead author of the CAST policy brief AI in Agriculture: Transforming the Food System from Data to Decisions to Action and has spent his career at the intersection of AI systems and real-world agricultural deployment environments — one of the most demanding settings for AI in any sector.

Policy Brief Landing Page

Full context, key findings, and additional author information
→ https://cast-science.org/publication/ai-in-agriculture-transforming-the-food-system-from-data-to-decisions-to-action/