Getting more done quicker, more thoroughly and more accurately seems like quite a feat, but many industry pros give real-world examples of how artificial intelligence (AI) is helping ag retailers do just that every day.
“I don’t think there’s any task that’s too small that you can’t take AI and apply it within agriculture,” says Ryan Raguse, co-founder of Bushel, whose software powers more than 3,500 grain and ag retail facilities and reaches over 100,000 farmers across the U.S. and Canada.
Raguse says when it comes to the adoption and use of AI, business leaders have three options:
- Do nothing
- Wait for your competitor to get the tools and then follow them closely
- Lead the industry and get in front of the trends
For the past six years, Glen Franzluebbers and the team at Central Valley Ag (CVA) have been using Taranis technology to explore how AI fits into their programs.
“When I think about the challenges for our team — it’s labor, time and information overload,” Franzluebbers says. “Our No. 1 priority is doing right by the grower, and that means we need to be accurate in our recommendation but also efficient.”
Using Taranis Ag Assistant, they are able to take their local expertise and pair it with the technology. Six in-season missions include: stand count, weed detection, insect or disease damage assessments, nutrient deficiencies as well as other analytics.
Trevor Cox, CVA regional manager, notes the technology is a great tool, but won’t replace agronomists.
“With weed management, there is nothing like seeing the whole field all at once. It’s incredibly valuable,” he says. “With stand count, it only tells you if the stand count is low. It could be dry conditions or planter setup. You still need an agronomist who can troubleshoot why the stand count is low. But there is a value in being alerted there is a problem, and then it’s up to us to find out why.”
Franzluebbers says its additional benefit is the year-end analysis.
“It’s like a report card, and it’s all in one file rather than a big binder of reports,” he says.
Chief commercial officer for Taranis, Jason Minton, says this is an example of how AI is taking big data and analytics and helping turn them into decision-making tools.
“Our drones fly a field and take pictures of every single acre down to the leaf level at three tenths of a millimeter,” he says. “It is an immense amount of data, but AI makes it manageable and actionable to drive that efficiency that you need for your people who are overwhelmed with 17 things to do every day.”
Minton also highlights the importance of having human experts continue to refine the AI’s accuracy.
“The AI is constantly being retrained, and it’s being done by agronomic experts who can help direct where it’s correct and where it’s wrong,” he says.
Earlier this year, AgVend announced Goose, which is an AI co-pilot designed for ag retail.
“Goose empowers every team member with a personalized assistant capable of delivering instant answers to complex questions, such as who booked urea last fall but has not booked this season,” says Eli Rosenberg, co-founder and chief product officer at AgVend. “It automates time-consuming tasks, like recording meeting notes, and uncovers valuable customer and business insights in seconds, such as determining which customers have contracted less grain this season.”
The future of AI in ag retail continues to be unveiled. While automation unlocks new efficiencies for ag retailers, it’s up to the team to reallocate the time and talent for it.
