STARKVILLE, Miss. – AI is helping researchers, farmers and food companies improve efficiency, strengthen resilience, conserve resources, and deliver a safer food supply, however federal policy is not keeping pace.

 “Artificial intelligence has advanced so fast that it’s not really just a research tool anymore; it’s embedded in agricultural practice now,” said Alex Thomasson, Mississippi State University professor of agricultural and biological engineering.

“From autonomous weed spraying to AI-assisted seed selection to real-time food safety inspection on processing lines, the technology is already changing how farmers work, how food moves through the system, and what we expect from that system,” added Thomasson, also the university’s Agricultural Autonomy Institute director. “The policy conversation needs to catch up.”

Thomasson is also the author of a policty brief issued by the Council for Agricultural Science and Technology (CAST) in Ames, Iowa, examining how artificial intelligence (AI) is already reshaping American food and agriculture, while federal policy lags behind.

Entitled “AI in Agriculture: Transforming the Food System from Data to Decisions to Action,” the brief produces current peer-reviewed research to assess where AI adoption stands today, where it is headed, and what gaps in federal policy, infrastructure and workforce development must be addressed to realize its full potential.

Thomasson said the brief identifies five key findings: First, AI is no longer a future promise: it is in active use across crop production, animal agriculture and food supply chains, creating benefits for farmers and consumers, but also creating new policy questions.

Second, he said, AI is changing from a data analysis tool to a system that takes physical action – what the brief terms “physical AI” – with autonomous machinery and robotics increasingly moving from demonstration to commercial deployment.

Third, he said, data quantity and quality are foundational to AI performance, making rural data infrastructure a critical policy priority. Fourth, he said, AI is being applied across every segment of the food system, from genetic seed selection to optical food safety inspection.

Fifth, he added, federal policy decisions on data centers, rural broadband, data ownership and workforce development play a role in how AI benefits American agriculture, and whether rural communities capture the economic gains of AI locally.

Chris Boomsma, CAST executive director, told Farm World this policy brief grew out of CAST’s ongoing commitment to provide policymakers and other stakeholders with timely, science-based information on issues shaping the future of food and agriculture.

He said this commitment builds on CAST’s earlier publication, “AI in Agriculture: Opportunities, Challenges, and Recommendations,” which was also led by Thomasson, and a multidisciplinary team of authors and reviewers: “That publication examined the opportunities, challenges and emerging applications of AI across agriculture.

“Since then, the pace of AI innovation and adoption has accelerated significantly,” he added. “At the same time, policymakers are increasingly examining a range of issues connected to AI, including rural broadband and connectivity, infrastructure, data centers, workforce development, data ownership and governance, research investment and the AI competitive landscape.”

He said CAST recognized the need for a concise, peer-reviewed resource that reflects the latest science, and helps inform those conversations with credible, objective information, where CAST worked closely with Thomasson through its established publication development and peer-review process.

“Consistent with CAST’s mission, the goal was not to advocate for specific policy outcomes, but rather to provide an objective, science-based assessment of AI’s opportunities, challenges and implications for agriculture, helping policymakers, industry leaders and the public make informed decisions based on the best available evidence,” he said.

Thomasson told Farm World, “Based on limited feedback, farmers are saying, ‘We need to be using AI more on the farm.’ AI, specifically generative AI, is simple to use and free at a basic level, so it’s relatively easy to get started with, and I think this is driving faster adoption than with many other technologies.”

According to Mississippi State, generative AI refers to AI systems like ChatGPT and Gemini that use algorithms and machine learning to create new text, images and other media based on user prompts.

“This usage applies to answering agronomic questions, to analyzing data, both agronomic and financial, and to generating reports and the like,” Thomasson said. “Ultimately, AI will also help growers with solving complex problems, and even controlling autonomous machines to do specific farm tasks like weeding and harvesting.”

He said how AI develops, how it is used in agriculture, and who has access to it over time are going to be heavily influenced by policy decisions, many of which are made by legislators: “We need funds for research, we need broadband connectivity in rural areas, we need clarity around data ownership, and we need to invest in the workforce that can build and maintain these systems. None of that happens without policy.”