Laying the Groundwork for Autonomous Decision-Making in Agriculture

A conversation with Bayer on preparing for agentic AI in complex operations

Agentic AI in Agriculture: Beyond the Hype

AI agents are moving fast. But for most enterprises, the real question is not what agents can do, it is whether the organization is actually ready to let them act.

In agriculture, that question is even harder.

Decisions are shaped by biology, weather, regulation, and risk. Data is fragmented across systems. Every growing season is effectively a once-a-year experiment. And the cost of getting a decision wrong can ripple across an entire value chain.

In the latest episode of The Agent Effect, Paul Jarratt speaks with Patricio Salvatore La Rosa, Head of End-to-End Decision Science for Seed Production Innovation at Bayer, about what it really takes to introduce agentic AI in an environment where autonomy must be earned, not assumed. Rather than focusing on hype or futuristic demos, the conversation zeroes in on the fundamentals. What must be true about your data before agents can be trusted? How do you connect decisions across silos without creating new risk? Where should humans stay firmly in control, and where does autonomy actually create value?

Patricio also challenges a common assumption. Agentic AI is not a single leap forward. It is a progression, shaped as much by governance, culture, and accountability as by technology itself. Organizations that rush ahead without addressing those foundations may end up with impressive pilots that never make it into real operations.

Tune in: The Agent Effect

If you are a CIO, CTO, or business leader exploring how AI agents could support decision-making, automation, or operational resilience, this episode offers a grounded perspective from someone doing the work inside a global enterprise today.