Half of US Farmers Use AI Tools, But Only 24% Trust Them

American farmers are experimenting with artificial intelligence at significant rates, but a deep trust gap threatens broader adoption across the agricultural sector.

A new survey from agricultural marketing firm MorganMyers and market researcher Ag Access found that 48% of farmers and ranchers use AI tools like ChatGPT or Gemini on at least a weekly basis. Yet only 24% of those surveyed said they fully or somewhat trust the recommendations these models generate for their farming businesses, according to the report first published by Iowa Capital Dispatch.

The disconnect is stark: 45% of farmers said they feel "uncomfortable" allowing AI to influence real operational decisions.

Why it matters

The agriculture industry faces mounting pressure to increase yields while managing climate variability, labor shortages, and narrow profit margins. AI promises precision farming improvements and efficiency gains, but this survey suggests the technology won't scale without addressing fundamental trust barriers—particularly around accuracy and data transparency.

Accuracy tops farmer concerns

The survey, which included 166 producers, identified accuracy of AI recommendations as farmers' primary concern. Data ownership and privacy ranked second, followed by worries about model bias and the potential displacement of human expertise.

"Farmers and ranchers aren't resistant to AI," said Greg Ehm, senior vice president of agriculture at MorganMyers, in a statement. "Our survey confirms they're trying it out and can already see areas where it delivers value."

To build confidence, 62% of farmers said they need to see "real-world farm results" from AI applications. Thirty percent want the ability to override AI suggestions, while 27% called for transparent data sources.

Ehm noted that producers are "weighing" AI recommendations against "years of personal experience and practical knowledge."

Adoption patterns vary by operation type

The research revealed significant differences in AI uptake across farm types. Dairy operations showed the highest adoption, with 64% classified as "active users." Large-scale operations and farmers under 35 also demonstrated higher usage rates.

In contrast, 55% of row crop farmers reported low or no AI use.

Among farmers who do use AI regularly, 49% apply it primarily for personal research and drafting tasks. Forty percent use AI for crop planning or planting decisions, while over 30% leverage it for livestock nutrition insights or business management.

Built-in AI features lag behind general tools

Farmers showed less enthusiasm for AI features integrated into agricultural platforms than for general-purpose models. Only 39% use AI-enabled features in their existing ag platforms daily or weekly, compared to 48% who use tools like ChatGPT or Claude with that frequency. Thirty percent never use the integrated AI features at all.

Agricultural retailers surveyed showed even lower adoption. Among fewer than 40 retailers polled, 60% reported low or no trust in AI business recommendations, and only 38% use AI tools weekly or more often.

A 2025 study from agricultural company Syngenta found similar trust challenges. That research noted farmers found the term "digital farming" more relatable than AI, even though GPS guidance, cloud management platforms, drones, and weather apps—all forms of digital agriculture—are already widespread in U.S. farming.

MorganMyers concluded that AI models will succeed in agriculture only if they demonstrate real-world outcomes, support rather than replace human expertise, and improve existing farmer workflows.

These findings were first reported by Iowa Capital Dispatch.