Farmers in the United States and Argentina hold sharply divergent views on what artificial intelligence can do for their operations, according to a new survey of grower sentiment in both countries.

The headline finding is the split itself: producers in the two leading agricultural economies — together major suppliers of corn, soybeans, wheat and beef to world markets — do not see eye to eye on whether AI belongs on the farm at all.

The survey asked farmers directly what they think about artificial intelligence in their day-to-day operations. The result, summarized by the pollsters as "two countries, two outlooks," points to a gap between how U.S. and Argentine growers weigh the technology's promise against its costs and risks.

For input makers, machinery manufacturers and farm software firms, that divergence matters. Adoption of AI-driven tools — from variable-rate seeding prescriptions and sprayer guidance to yield modeling and grain marketing analytics — depends on whether growers believe the technology pays for itself. If U.S. and Argentine farmers answer that question differently, suppliers will likely have to price, position and support the same tools differently in each market.

The gap also has implications for farm margins. AI adoption in row-crop production typically runs through input spending: better targeting of seed, fertilizer and crop protection is supposed to reduce per-acre costs or lift yields enough to cover subscription and hardware fees. Farmers skeptical of those paybacks will hold back, regardless of what agronomic trials show.

The contrast between the two countries is notable given how similarly their row-crop sectors compete. Both are major soybean exporters selling into the same global demand pool, and both have embraced precision-agriculture hardware in earlier waves of technology. That shared baseline makes the difference in AI sentiment harder to explain by equipment access alone, and points instead to factors such as farm structure, financing conditions, connectivity in rural areas and trust in data handling.

The survey's release comes as ag-tech companies press AI features into nearly every product line, from autonomous machinery to farm-management platforms. Grower willingness to pay for those features — and to share the field data that trains them — remains the open question the survey set out to measure.

No harvested results, acreage figures or yield outcomes from AI deployments are claimed in the findings; the data reflect farmer opinion, not measured performance, and readers should treat them as a sentiment reading within the survey's sampling frame rather than evidence of agronomic or economic results.

Future rounds of the survey will show whether the U.S.–Argentina gap narrows as early adopters in each market report actual cost and yield effects from AI tools now moving onto more farms.