Three Practical Ways to Make Ag Technology Pay in 2027

By Marcus Bennett

Targeted spraying systems can reduce a sprayer from 10 sections to individual nozzle control, giving growers a direct route to lower input use as they assess technology purchases for the 2027 season.

As of 2026, hundreds of ag-tech products and services span precision irrigation sensors, drone imaging platforms, farm-management software, AI yield-prediction tools and robotics. New solutions launch constantly. Others are discontinued or folded into larger platforms.

Higher input costs and lower crop prices squeeze farm margins. Together, they make a new purchase harder to justify.

No product inventory or comparative performance set accompanies the 2026 market estimate. The 10-section example demonstrates a sprayer configuration, not a measured savings rate. Farmers still need to price each tool against their own acres, inputs and yields.

What should farmers fix before buying more?

Precision Planting's Bryce Baker says existing machinery deserves attention before another purchase. He said: “Make sure the base machine is in really good shape.” A machine also must work with the technology already on the farm.

Planter row units can wear out, Baker said. Technology attached to poorly maintained equipment will deliver little benefit. Farmers may be keeping equipment longer in the current buying cycle. That makes maintenance and compatibility central to return on investment.

Baker sees renewed promise in technologies that save inputs. His swath-control example moves a sprayer from 10 sections to individual nozzle control. Targeted spraying adds further savings by allowing applicators to treat only the areas within a field that require treatment.

Can current data produce a return?

Stephanie Cook, who farms near Davenport, North Dakota, has no plans to buy new technology. The money is not available. She wants to use existing tools more fully, including data collected over the past several seasons. Some of that information may simply sit unused on hard drives or in cloud accounts.

Cook plans to use yield maps to improve variable-rate fertilizer and seed-population strategies. She also plans to work closely with precision-farming specialists at equipment dealers. That partnership should reduce reliance on trial and error, she said.

Quentin Connealy, a fifth-generation farmer in eastern Nebraska, has been testing and refining the data he already collects. This year, he helped pilot AskMyFarm, an AI program that creates a digital memory of fields and projects yields.

Its yield output is a projection, not a harvested result. The information could still give Connealy useful guidance as he enters the 2027 season.

Connealy says return on individual products and practices matters more than chasing the largest yields. “Other than that, we try a few different products every year and try to pinpoint ones that work on our farm because every farm is different,” he said.

Customer support can determine whether technology works. Connealy said some vendors have good ideas but lack the people to teach farmers how to use them. He also said service technicians can be thousands of miles away.

Can farmers build their own tools?

Travis Senter Jr., a third-generation farmer in northeast Arkansas, has long used high-end farm technology. He still treats every new tool as another problem to learn. Senter said he had spent nights during the previous two or three weeks writing programs to give himself an edge.

Senter uses vibe coding, a method that uses AI to build software from plain-English instructions. A farmer can request an app that tracks soil moisture across fields and alerts the operator when irrigation is needed.

Senter combines yield data with planting dates, inputs, dew points, temperatures, rainfall and other records. That combination supports scenario planning for the current and next seasons while letting him create tools for his operation rather than wait for a vendor.

Senter argues that raw farm data has limited value until farmers can interpret it visually. AI now helps them answer questions they previously could frame but not solve. He starts with a desired outcome, explains it to the system and develops the tool through an extended conversation with the data.

Beginners can start with Google AI Studio, Claude Code or Base44. Each provides a beginner-friendly route to plain-language software development. Farmers write a prompt describing the app's function and features, test it through a live preview and revise it when needed. YouTube also offers multiple tutorials.

What does this change for farmers?

The practical change is the order of decisions: maintain, measure and then add. A maintained machine protects current capacity. Better-used yield maps can improve fertilizer and seed decisions. A targeted AI tool may improve planning while remaining tailored to the operation.

None of the cited examples supplies a measured farm-level return. Farmers should test tools against their own input costs, harvested yields and margins. Dealer support and vendor service also belong in the purchase decision.

For 2027, the stronger case may belong to tools that can document input savings or better decisions on a particular farm, rather than products selected for headline features alone.