Precision farming technologies gather data from a variety of points, such as GPS coordinates from tractors, seeding rates from planters, pesticide volumes from sprayers, moisture readings from soil probes, and yield estimates from combines.

The services—from Bayer, Deere, Corteva, Trimble, and others in the ag-tech sector—increasingly use artificial intelligence to detect patterns, weaving together farmers’ data with other feeds, like satellite images and weather station readings. Farmers can open dashboards on their smartphones or computers to see overviews of conditions and trends, along with suggestions about practices to tweak.

Nelson takes advantage of many of these capabilities, feeding his spraying data to Bayer Climate FieldView to receive recommendations on chemical applications. He allows John Deere Operations Center to collect data from his tractors and combines to provide him insights on equipment performance and efficiency.

But the fifth-generation grower doesn’t share all his field-level data with the services. “I’ve read the terms and conditions,” says Nelson. “But giving some of that information to the person that I’m having to buy a three-quarter of a million-dollar machine from just doesn’t sit quite right.”

Ads for these AI-powered services promise to “empower” farmers to “harness” their data and “make better decisions,” boosting yields and unearthing efficiencies. In the U.S., uptake is relatively high, with 27 percent of farms or ranches using the tools, according to the U.S. Government Accountability Office. And market analysts project double-digit growth for these tools, expecting them to reach as high as $27 billion by 2030 worldwide. Aiding the growth are multiple tailwinds, including incentives bundled in the latest draft of the U.S. farm bill.

With the industry poised to expand exponentially over the next few years, small-scale farmers and sustainability advocates worry that big companies will leverage their data to sell more products and services, corner markets, or even threaten their livelihoods.

‘Small’ Data in Big Hands

California almond grower Rebekka Siemens has resisted sales pitches for expensive “smart” irrigation systems. “On the one hand, it’s attractive that the reporting can be integrated or exported for reporting purposes easily,” says Siemens. “On the other hand, it could harm you . . . . It feels exposing, the lack of privacy. We don’t know who’s doing what with it.”

There may be little value in “small” data from more modest plots of land, but corporations see aggregated pools of information as a gold mine. And training AI systems on the capture of feeds from thousands of farms raises questions of who should hold the intellectual-property rights.

“It’s essentially like we’re being charged to use the service and then the company is making even more money off of us by selling our data,” Siemens says.

Most ag-tech services insist that they are granting farmers ownership of their data. “Farmers own their own data—full stop,” said Brian Leake, a spokesperson for Bayer, pointing out that the Climate FieldView technology has been certified by the auditing nonprofit Ag Data Transparent since 2021. “They can choose to share their data with others and request that their individual farm data is deleted.”

Watchdog groups warn, however, that legalese within click-to-sign contracts favors the businesses. Surprises can lurk within a 10,000-word software license agreement, they say. And a contract that prevents a tech company from selling data to a third party may nevertheless grant a business partner broad rights to exploit and share anonymized pools of data.

A gray zone exists regarding who controls the bits and bytes, which the ag-tech providers store with the likes of Amazon Web Services, Microsoft Azure, and Google Cloud.

Advocates also raise red flags about the perceived marriage between Big Tech, which profits from people’s data, and the Big Ag companies blamed for industrializing agriculture and squeezing out family farms.

The fears are manifold. What if the main purpose of collecting all this data isn’t to help farmers, but to sell more products? Where does data go if a startup folds? What if a bad foreign actor uses intelligence to disrupt the food system? Could government use evidence of fertilizer use today to punish a farm later for nitrogen pollution? What if the data lands with hedge funds or investors who manipulate commodity markets or drive down land prices to further concentrate land ownership?

Elizabeth Vaughan, senior manager of the Small-Farm Tech Hub at the Community Alliance with Family Farmers, worries that AI might further concentrate power outside farmers’ hands.

“Is Amazon going to be our food producer 50 years from now, or Microsoft—or are we still going to have small farmers that provide for their local communities, grow culturally relevant crops, and have resilient community food systems?” she asks.