John Deere Tests ‘JD’ AI Assistant That Answers Questions From Farmers’ Own Data

John Deere is testing an AI assistant called JD that answers plain-language questions using a farm’s own field, machine and operational data. Deere says it can help with questions about equipment settings, fuel use and harvest timing, The Verge reported.

JD runs inside Deere’s Operations Center farm management platform. Deere’s examples are specific: comparing fuel use during tillage across years, checking how planting singulation varied between fields, and finding which sprayer operator covers the most acres per hour. “JD changes the experience from navigating through a sea of data to simply asking it a question,” said Jahmy Hindman, Deere’s chief technology officer, according to The Next Web.

The rollout is small for now. Deere is running an Early Access Program in which selected U.S. customers can register interest at the Farm Progress Show in Iowa, with wider availability promised later this year. Deere hasn’t said which AI model powers JD.

A data pledge alongside it

Deere launched the assistant together with a 10-point Farmer Data Commitment. The pledge says farmers control their farm data, Deere doesn’t sell it, farmers can choose which third parties get it and turn off that flow at any time, and Deere won’t use farm data for commodity trading or speculation. The Verge noted that the pledge comes after years of fights with farmers and the FTC over right to repair.

The Next Web pointed out that in Europe, much of the pledge is already law. Since Sept. 12, 2025, the EU Data Act has required makers of connected products to give users their data for free in a machine-readable format and pass it to third parties on request. One provision, Article 4(13), has no equivalent in Deere’s list: it bars a data holder from using the data to derive insights about a user’s economic situation, assets or production methods. Deere hasn’t said whether JD is coming to Europe.

For enterprise software vendors, JD follows a familiar pattern for vertical AI. The assistant’s value comes from proprietary operational data the platform already holds, so how much customers will use it may depend as much on trust in the vendor’s data terms as on the quality of the answers.