Phil Franz-Warkentin May 22, 2026
https://www.producer.com/agriweek/agriweek-may-22-2026
As agriculture technology moves toward more ‘agentic’ systems, agronomists say the farmer still holds the reins.
At last month’s World Agri-Tech summit in San Francisco, speakers framed the next phase of artificial intelligence in agriculture as something new: systems that don’t just offer advice but begin acting on it, also known as agentic AI, wrote Glacier FarmMedia’s Don Norman.
“Agentic” refers to systems that move beyond analyzing information or making recommendations and begin taking on tasks and acting more like digital agents.
“What does it mean for farmers to have a digital assistant or be managing a set of agents that are doing work for them?” asked Ranveer Chandra, chief technology officer of agri-food at Microsoft, who hosted the opening session at the summit.
It’s easy to see how AI is working in corporate settings. During the same session, Reza Rasourpour, a vice-president with Corteva Agriscience, pointed to how artificial intelligence is massively speeding up product development. Those advances are making their way to the farm, with examples such as field data being set to optimize fungicide applications.
But beyond examples such as fungicide timing, the panel discussion stopped short of exploring what a fully “agentic” system would look like in day-to-day farm management. That’s where the question shifts from the conference stage to the field.
On Prairie farms, where decisions are shaped by weather, field variability and farmer risk tolerance, agronomists say there is still a clear line between a recommendation and a final call.
Even when farmers work closely with trusted advisers, they generally keep control over decisions that affect input costs, crop risk and yield potential. That is unlikely to change quickly just because the recommendation is coming from software instead of a person.
Rob Warkentin, a Saskatchewan-based private agronomist, said some AI applications already look realistic, especially in areas such as disease forecasting. “AI is a great fit when it comes to things like disease,” he said. “But maybe not so much on fertility recommendations.”
That distinction is important. Disease risk, insect movement and weather-driven threats are all areas where more data, better pattern recognition and faster analysis could improve timing. In those cases, AI may help narrow down a decision faster than an agronomist or farmer working alone.
However, that is not the same as handing over control, as farmers still want the final say.
Warkentin was uncertain computer models will ever gain that same level of trust with farmers as a human advisor.
Brunel Sabourin, co-owner of Antara Agronomy in St. Jean Baptiste, Man. said AI will be disruptive and already has obvious uses in helping agronomists and farmers process more information faster. However, he also sees hard limits in a business where no two seasons are the same.
“The biggest overarching challenge that I see is being able to capture all of the variability in a field and being able to make proper decisions with that,” he said.
For Sabourin, that variability is the reason agronomy still resists full automation. Soil, weather, moisture, field history and management all interact. A small change early in the season can ripple through everything that follows.
That does not mean AI has no role. In fact, both agronomists see it becoming more useful, not less.
Sabourin said his own business was already using AI heavily for lower-level tasks such as reports and analysis, and increasingly to dig through large agronomic datasets more quickly.
He described using it to sort through benchmarking data and test relationships between variables that would have taken far longer to examine manually. That’s valuable. But even there, Sabourin cautioned against assuming more data automatically leads to clean, scalable answers.
While the push is on for integrating AI into agriculture, the collective wisdom and knowledge in the farming world is astounding, wrote Glacier FarmMedia editor John Grieg in a recent op-ed.
It’s been there for a long time. In the past surfacing through coffee shop conversations, chats through the windows of two pickup trucks stopped beside each other on a side road, and in phone calls. Those still happen, but the internet has brought the hive mind of the agriculture community into the open, “and it’s pretty awesome,” said Grieg.
He questioned how many more generations it will continue, as more people are further removed from the farm. Some of it is nostalgia, but there are still serious problems being solved quickly and inexpensively without AI every day.