What Farmers’ Advisors Really Want From AI

Study finds crop advisors favor AI that supports judgment, protects data, and keeps costs clear over tools that simply promise accuracy

1 Mar 2026

A new peer reviewed study is reshaping how we think about artificial intelligence in agriculture. Published in February 2026, the research offers one of the clearest looks yet at how crop advisors judge AI tools in real working conditions.

The study, led by researchers at Virginia Tech and the University of Vermont, surveyed Certified Crop Advisors across North America. Using a discrete choice experiment, participants weighed trade offs between accuracy, cost, precision, and data ownership. The goal was to understand what actually drives trust and adoption in tools used for fertilizer planning, pest detection, and irrigation decisions.

The results push back on a common belief in ag tech circles. Accuracy alone is not enough. Advisors placed greater value on tools that are easy to use and that handle data responsibly. Systems that allowed users to keep control of their farm data ranked far higher than those requiring full company ownership, even when performance was strong.

There was also a clear preference for AI that works alongside human expertise rather than replacing it. Advisors favored tools that let them adjust recommendations, factor in local conditions, and confirm results in the field. This human in the loop approach, the researchers argue, should be built into systems from the start, not added later.

Cost and transparency emerged as key concerns as well. Lead researcher Maaz Gardezi noted that advisors want tools that support their judgment without locking them into rigid pricing or opaque data practices. Co author Asim Zia pointed to broader implications, stressing that AI must serve farms of all sizes if it is to strengthen food systems.

As adoption remains uneven across the sector, the study offers a practical roadmap. By listening to the advisors who guide day to day decisions, developers may build AI tools that are not only smarter, but also trusted where it matters most.