I recently had the opportunity to speak at Web Summit Vancouver about a topic I'm very passionate about: the application of AI in agriculture. It's a conversation that deserves a lot of attention because, while most people associate AI with chatbots or automation, one of its most meaningful applications in my opinion is happening much closer to the ground, literally!
When people think about agriculture, they often picture large equipment and physical labor. But modern farming systems already have technology deeply entrenched in it, and the next major transformation in food production will come from how we use data and AI to help make more profitable and sustainable food production decisions.
I didn't come from an agricultural background. When I first entered the industry more than 15 years ago, someone explained farming to me in a way I've never forgotten: imagine operating a factory where you don't control the cost of your inputs, you don't control the price of your product, and your factory doesn't have a roof. Adding to that, farmers also operate under constant pressure from external factors such as the weather, labor shortages, changing regulations and fluctuating international relations.
For decades, agriculture improved productivity largely through better inputs: stronger seed genetics, better fertilizers and new crop protection products. But I believe the next major leap forward will come from better use of data and the decisions we make by having this data available.
Farming is fundamentally a biological system, and biology is incredibly localized. Conditions can vary dramatically within the same field. One section may need water while another does not. A pest threat may emerge in one area but never develop into a broader problem because weather conditions change. Historically, farmers relied heavily on intuition developed over years of experience. That intuition is still incredibly valuable, but today's farms are larger and more complex than they were a generation ago.
That's where AI becomes powerful.
By combining hyper-local data from sensors, weather models, and field monitoring systems, growers can make far more precise decisions in real time. Instead of broadly applying inputs “just in case,” they can target exactly where action is needed, and equally important, where it isn't needed. This helps improve profit and supports more sustainable farming practices.
One thing I emphasized during my Web Summit discussion is that farmers are already some of the most sustainability-focused professionals around. They genuinely want to produce more with less. As caretakers of the land, they want healthier soil, smarter water use, and fewer unnecessary inputs. Technology helps support those goals.
At Semios Group, we think about agriculture as an ecosystem. Better visibility and predictive analytics help everyone throughout the supply chain operate more effectively, not just the farmers. AI is not replacing agriculture's human element. You still have to plant the seed, manage the crop, and harvest the food. But when critical decisions need to be made quickly, AI can augment decision-making by helping farmers process large amounts of complex data that would be otherwise difficult to do intuitively.
To me, that's where AI gets truly exciting. Its biggest impact may not happen online. It may happen on the ground; helping us grow food more intelligently, sustainably, and resiliently for the future.
