A new study has concluded that the agri-tech sector has spent more than two decades overestimating how quickly farmers adopt precision agriculture technologies, raising serious questions about investment assumptions, market forecasts and industry narratives.
Dealers’ forecasts missed the mark across 26 technologies
The study, “Is Precision Agriculture Technology Adoption Persistently Overestimated?” analysed 21 waves of the CropLife–Purdue Precision Agriculture Dealership Survey (2000-2025). It found that input dealers consistently predicted higher adoption levels than were ever realised across nearly all of the 26 precision agriculture technologies studied.
The pattern held across technologies, time periods and market cycles, suggesting a structural forecasting problem rather than isolated misjudgements.
Notably, the researchers found no clear pattern explaining why some technologies were overestimated more than others. Speaking to AgTechNavigator, study co‑author Chad Fiechter, Assistant Professor of Agricultural Economics at Purdue University, said: “Beyond the persistent overestimation, there doesn’t appear to be a strong pattern among the technologies. 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.”
Forecast errors widened sharply in the 2020s
The overestimation gap grew even larger in the early 2020s, a period when adoption of several PA tools flattened or declined, yet dealers continued to expect steady growth.
Fiechter suggests this 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 pointed to three technologies where the plateau was particularly striking:
- Precision planter equipment – despite being widely touted and widely adopted, the leveling‑off suggests the market may be reaching saturation.
- Variable Rate Technology (VRT) for custom fertiliser – long considered industry standard, but dealers continue to overestimate service‑level demand.
- UAV/drone imagery – despite intense hype, dealer capacity for drone‑based imaging services has dipped rather than grown.
Industry optimism, not data, driving expectations?
The research concludes that agribusiness managers may be guided by overly optimistic narratives about continuous technology diffusion. Despite extensive historical data demonstrating slower and more irregular adoption patterns, forecasts repeatedly assume linear growth.
As Fiechter puts it: “Optimism is likely driven by industry narratives. Farm operations are complex and often even those who serve farmers are not aware of how emerging technologies will actually solve a problem.”
Such misplaced optimism, the authors warn, has real commercial consequences. Persistent forecasting errors can lead firms to:
- Overinvest in staff, equipment or digital service capacity
- Misjudge the commercial viability of new technologies
- Delay course‑corrections when adoption stalls
The study presents these risks as symptoms of a deeper problem: a failure to revise expectations when new data contradicts long‑standing assumptions.
How agribusinesses can avoid the ‘hype trap’
While the study does not prescribe specific forecasting tools, Fiechter urged agribusiness leaders to adopt greater scepticism and continuously update their models:
“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 added that future research, potentially with new collaborators and funding, could extend the analysis beyond 2025 to monitor whether the overestimation trend continues.
Looking ahead, Fiechter expects emerging technologies such as autonomy, AI‑driven scouting, and robotics to be similarly overestimated unless the industry confronts its forecasting 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.”
What this means for the agtech sector
The findings offer a clear warning for investors, suppliers and tech developers: the market for precision agriculture evolves more slowly and unpredictably than industry expectations suggest.
If the sector wants more accurate predictions, and better investment decisions, Fiechter points out it must ground its assumptions in realistic adoption dynamics: “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.”
The full study is available at: DOI:10.1002/agr.70085
