Ag Tech Talk Podcast: Inside One of America’s Largest Ag Co-Op’s Practical Approach to AI
11 June 2026 AI has long dominated ag industry headlines—but turning it from concept into day-to-day agronomic practice requires far more than a product launch. In this episode of Ag Tech Talk, FS Agronomy Director Brendan Bachman of GROWMARK breaks down the operational reality behind scaling AI across one of North America’s largest cooperative systems, from building data infrastructure to navigating the complexities of a federated organization.
Rather than positioning AI as a disruption, Bachman describes it as a practical layer within existing workflows – one aimed at reducing friction and helping crop specialists make faster, more informed in-season decisions. The discussion highlights the less visible work of adoption: aligning systems, earning grower trust, and driving buy-in across FS locations, while tools like MyFS Agronomy increasingly reshape – not replace – the agronomist’s role in the field.
Podcast Transcript:
*This is an edited and partial transcript.
AgriBusiness Global: As you evaluate success, what metrics matter most right now, and how do you see AI shaping agronomic decision-making and retailer value over the next several seasons?
Brendan Bachman: It’s going to get interesting—and in many ways, it already is. What stands out most is that context and content really matter. AI on the open web is one thing, but AI layered on top of a highly curated, agronomy-specific dataset is where you start to see real value emerge.
In terms of measuring success, it comes down to engagement. We’re never going to have 100% adoption, so the key is understanding who is using the tools versus who isn’t—and then digging into what that means. Are we seeing sustained usage growth? Are engaged users making better decisions or seeing stronger outcomes, like higher yield performance compared to non-users? That’s where this gets meaningful.
AI isn’t a silver bullet; it’s a synthesis tool. It helps bring together the complexity of agronomic decision-making in a way that supports, rather than replaces, human judgment. Over the next few seasons, the real question is whether we begin to see a performance gap emerge between those who are actively using these tools and those who aren’t. If that happens, it becomes less of a technology story and more of a competitiveness story—for both farmers and retailers.
ABG: As AI becomes more embedded in agronomic decision-making, do you expect it to influence how growers purchase or use crop inputs—and could it reshape the role of ag retailers and manufacturers?
BB: Yes, I do think AI will ultimately influence purchasing decisions and product use. But it’s important to recognize that AI has been evolving in the background for years—through tools like computer vision and automation. What’s changed is the rise of large language models that make these systems far more accessible and interactive.
That accessibility is lowering the barrier to entry across ag tech and beyond. We’re seeing entirely new verticals open up faster than ever before, which will likely accelerate innovation—but also drive consolidation. Fewer players will be able to build and sustain differentiated value at scale.
In the end, the organizations that succeed will be the ones that use AI effectively to improve decision-making and customer impact. That will directly influence farmer decisions, product selection, and how value flows through the ag retail system.
ABG: Any closing thoughts?
BB: This isn’t the end of something—it’s the beginning of a new phase. The pace of change is unlike anything I’ve seen in 20 years.
But even as we lean into AI, we still must ground it in strong agronomy and sound decision-making. And we also must be willing to challenge our assumptions. One of the biggest lessons here is the need to forget what we think we already know to see what’s actually possible.
Get The Newsletter Today!
