AI AgriBench

AI-based advisory services for agronomy and crop management are emerging worldwide, reaching hundreds of thousands of farmers in the United States, India, Africa, and beyond. Agricultural professionals are using public chatbots to get answers, and some organizations have developed their own. Until now, users have not had a systematic way to assess the accuracy, relevance, or general usefulness of the answers obtained from these generative AI ag information services. 

Led by the Center for Digital Agriculture (CDA) at the University of Illinois Urbana-Champaign (UIUC), the AI AgriBench consortium provides users of public chatbots and crop management advisory services with a trusted framework to evaluate and build confidence in the new generation of digital tools that support farmers and the broader agricultural community.

The AI AgriBench benchmarking service is designed to answer a simple but critical question: “Is agronomic advice from large language models (LLM’s) and AI-based agricultural advisory tools accurate?” The first version of the AI AgriBench benchmark, being released widely today, addresses core agronomic understanding, a key technical foundation for on-farm advice.

“It is exciting to be able to release our first benchmark evaluating agronomic knowledge in public chatbots and ag advisory services. It is encouraging that state-of-the-art LLMs have achieved a deep understanding of this technical area, but of course, real-world farmer questions require additional challenging capabilities which will be addressed in future versions of the benchmark,” says Vikram Adve, Donald B. Gillies Professor of Computer Science, AIFARMS PI, and director of the AI AgriBench Consortium.

AI AgriBench is a public benchmarking consortium led by the Center for Digital Agriculture at the University of Illinois Urbana-Champaign, created to evaluate the accuracy, relevance, and practical usefulness of AI-powered advisory services for agriculture. The consortium provides a transparent, expert-reviewed benchmark grounded in real-world agronomy and farm management questions drawn from land-grant university extension publications. AI AgriBench assesses public chatbots and AI-based advisory systems using curated, field-level scenarios that reflect real decisions faced by farmers and agronomy professionals, and reports results through a public leaderboard. The benchmarking methodology is based on research conducted within the CropWizard project of the AIFARMS National AI Institute. AI AgriBench brings together academic, industry, nonprofit, and extension partners worldwide to support trustworthy, responsible adoption of AI in agriculture. Founding and member organizations include AIFARMS, Bayer Crop Science, Extension Foundation, Kissan AI, John Deere, Microsoft, DeepRoot Strategies, Farmers Business Network, Taranis, Precision Development, and Digital Green.