AI Unfiltered: Ag Tech Leaders Talk Strategies for Results

Artificial intelligence is already creating value in agriculture, but not in the sweeping, transformative ways often portrayed by technology vendors and industry headlines.

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That was the consensus from a Women in Ag Tech webinar on June 4, 2026, where panelists shared where AI is delivering results — and where expectations need to be recalibrated. The three speakers were Tami Craig Schilling, Founder of DeepRoots Strategy; Mara Jorgensen, Enterprise Product Leader at Strategic Consulting Corp. and Iowa farmer; and Trisha Rentschler, Software Product Manager at Kahler Automation.

“AI is not new to agriculture,” Schilling said. What has changed, she noted, is the arrival of large language models that have made AI accessible to nontechnical users.

ROI Comes First

The panelists agreed that AI is proving its value when it solves specific business problems.

At Bayer, Schilling helped develop E.L.Y. (Expert Learning for You), an internal AI tool used by hundreds of employees to access agronomic and business information more efficiently.

At Kahler Automation, Rentschler said AI is helping lean teams increase productivity without increasing headcount. The technology is assisting with software development, code debugging, and other repetitive tasks that can compress timelines from days to hours.

Jorgensen pointed to logistics and supply chain optimization as another area where AI excels.

“You cannot possibly, even as the best human, optimize those routes for the most efficient,” Jorgensen said.

Still, she offered a simple standard for evaluating AI investments: “If you can’t track the ROI, it’s not a real AI win.”

Agriculture’s Biggest Opportunity Is Data

While AI may be attracting the headlines, the panelists said agriculture’s larger challenge remains data.

“Agriculture has immense amounts of data,” Schilling said. “But maybe it doesn’t flow across your organization, or it isn’t all in one place.”

Across the industry, valuable information remains trapped in PDFs, spreadsheets, handwritten notes, and disconnected software systems. AI’s emerging value lies in its ability to surface, organize, and make that information usable.

“We haven’t had a way to take those little slips of paper and turn them into information,” Schilling said.

Jorgensen agreed, noting that AI can help unify information from multiple sources and formats into systems that are easier to search and analyze.

The opportunity is significant, but so is the limitation: AI can only work with the data available to it. Poor data quality and disconnected systems remain major barriers to adoption.

Human Judgment Still Matters

If there was one point on which all three panelists strongly agreed, it was that AI is not replacing people.

Jorgensen cautioned against replacing established enterprise software with AI-driven alternatives, particularly in regulated environments.

“I would not recommend those sorts of regulated software to be replaced with AI today,” she said.

Schilling was equally direct about the role of data management systems, “AI does not replace data collection and data management systems. It’s not possible.”

The panelists also emphasized that AI struggles with context, relationships and emotional intelligence—areas that remain critical in agriculture.

“I can tell when a farmer is ready to buy,” Schilling said. “An AI tool can never tell that.”

Rentschler echoed that sentiment.

“There’s still that human element,” she said. “Understanding how humans want to interact.”

The discussion repeatedly returned to a common theme: AI works best as a support tool, not a replacement for expertise.

Practical Adoption Over Hype

Looking ahead, the panelists advocated for a practical approach to adoption.

Rentschler described a future of “tool-tip intelligence” that helps users make better decisions without overwhelming them with automation.

Jorgensen encouraged organizations to focus on their most pressing business challenges rather than chasing every new tool entering the market.

“If you’re worried about what to focus on in AI, you’re certainly not alone,” Jorgensen said.

The conversation ultimately offered a reality check for an industry inundated with AI messaging. The most successful applications are not replacing systems, eliminating jobs, or making human expertise obsolete. Instead, they are helping organizations work faster, make better use of data, and remove friction from existing processes.

For agriculture, the future of AI may be less about disruption and more about integration—combining technological capabilities with the judgment, relationships and experience that continue to drive the industry.

AI is powerful. But agriculture is still fundamentally human.

The full webinar recording is available through Women in Ag Tech’s YouTube channel. The organization will host its next event in Des Moines on July 20, 2026, launching Tech Hub LIVE.