Input dealers overpredicted farmer adoption of precision agriculture technologies across nearly all of 26 tools studied, in every survey wave from 2000 through 2025. That is the core finding of "Is Precision Agriculture Technology Adoption Persistently Overestimated?", a new analysis of 21 waves of the CropLife–Purdue Precision Agriculture Dealership Survey published at DOI:10.1002/agr.70085.

The agri-tech sector has spent more than two decades building investment cases, staffing plans and service capacity on adoption numbers that never materialized, the study concludes. The pattern held across technologies, time periods and market cycles — evidence, the authors argue, of a structural forecasting problem rather than isolated misjudgments.

No clean pattern in the errors

Co-author Chad Fiechter, Assistant Professor of Agricultural Economics at Purdue University, told AgTechNavigator the overestimation defies simple explanation. "Beyond the persistent overestimation, there doesn't appear to be a strong pattern among the technologies," he said. "For example, within Variable Rate Technology (VRT) technologies, the prediction errors are smallest for fertiliser and largest for lime applications… Technologies that gather information for decision-making generally exhibit larger prediction errors than technologies that use this information."

That distinction carries margin implications for dealerships. Information-gathering tools — soil mapping, drone imagery, scouting platforms — demand upfront service capacity and trained staff before revenue arrives. Where dealers overestimated demand most, they likely carried the costliest idle capacity.

The gap widened in the 2020s

The overestimation gap grew even larger in the early 2020s, a period when adoption of several precision ag tools flattened or declined while dealers continued to forecast steady growth.

Fiechter suggests the slowdown may reflect structural industry shifts rather than technology failures. "Farmers may be achieving scale large enough so that they are acquiring their own Precision Agriculture Technology capacity, not relying on dealers," he said — a shift that erodes the dealership service revenue model even as overall technology use on farms holds up.

Three technologies show the plateau most clearly. Precision planter equipment, despite wide adoption, appears to be nearing market saturation. VRT for custom fertiliser, long treated as an industry standard service, continues to draw overestimated demand forecasts at the service level. And UAV/drone imagery, despite sustained hype, has seen dealer imaging capacity dip rather than grow.

Narratives over data

The research concludes that agribusiness managers may be guided by overly optimistic narratives about continuous technology diffusion. Despite decades of historical data showing slower, irregular adoption, forecasts repeatedly assume linear growth.

"Optimism is likely driven by industry narratives," Fiechter said. "Farm operations are complex and often even those who serve farmers are not aware of how emerging technologies will actually solve a problem."

The commercial consequences are concrete. Persistent forecasting errors, the authors warn, can lead firms to overinvest in staff, equipment or digital service capacity, misjudge the commercial viability of new technologies, and delay course corrections when adoption stalls. The study frames these risks as symptoms of a deeper failure: not revising expectations when new data contradicts long-standing assumptions.

Skepticism as strategy

The study stops short of prescribing forecasting tools, but Fiechter urged agribusiness leaders to track realized demand against predictions continuously. "Use appropriate scepticism and don't get caught up in the hype cycle… If agribusinesses aren't tracking the demand for services and then incorporating or amending their predictions, they are omitting valuable information," he said.

He expects the next wave of technologies — autonomy, AI-driven scouting and robotics — to be similarly overestimated unless the industry confronts its blind spots. "Integrating new technology into modern cropping systems is difficult. Learning the true value takes time. These factors are frequently omitted when adoption trends are discussed," he said.

Still, adoption can match forecasts under specific conditions. "If a technology easily fits into modern cropping systems and the return on investment is well presented and consistent for many farm operations, I anticipate that adoption rates may be closer to the predictions," Fiechter said. Future research, potentially with new collaborators and funding, could extend the analysis beyond 2025 to test whether the overestimation trend persists.