Data Solutions for Tailoring Agronomic Support to Meet Regional Needs - with Tami Craig Schilling of Bayer Crop Science

The episode opens by framing agriculture as a universal four‑step cycle—plan, plant, grow, harvest—yet each field is uniquely shaped by soil history, tillage practices, weather, and pest pressures. Tammy Craig Schilling emphasizes that localized data is the linchpin for delivering agronomic advice that truly fits a farmer’s micro‑environment. By marrying field‑level observations with Bayer’s deep product knowledge, the company can move beyond generic recommendations and address the specific genetics‑by‑environment (GxE) dynamics that dictate crop success.

Schilling details Bayer’s digital innovation strategy, centering on generative AI and the ELY (E‑L‑Y) platform. ELY starts with a simple zip‑code prompt, then drills down to precise field conditions, genetics, and pest threats, generating tailored product suggestions in real time. This AI‑driven workflow transforms massive datasets—soil maps, weather forecasts, and historical yields—into actionable insights that augment, rather than replace, the farmer’s expertise. The approach showcases how precision agriculture and AI‑powered recommendations can reduce input costs while boosting yields across diverse regions.

Finally, the conversation highlights the farmer’s role as an active data partner. Bayer’s sales reps gather detailed prompts from growers, feeding the AI loop with real‑world challenges and successes. This collaborative model builds trust, accelerates adoption, and ensures that AI tools remain grounded in practical field realities. As the industry balances hype around autonomous machinery with the need for reliable information, Schilling’s insights illustrate a scalable path for AI integration that respects farmer autonomy and drives measurable ROI for agribusiness leaders.