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Before the sun rises over the fields of Philo, Casey Hettinger is already behind the wheel of his tractor. It's planting season. Fifteen-hour days are routine, and every pass through the soil matters.
But Casey isn't just driving. He's operating a system of sensors and software that track soil moisture, adjust seed depth and calibrate fertilizer output in real time. These interventions, enabled by artificial intelligence, improve yields, reduce input waste and give farmers more time to focus on key decisions.
These tools already shape how large, well-resourced farms make decisions. With the capital to invest, these operations can plan ahead and take calculated risks. For many others, especially smaller farms, the focus remains on getting through each season. That gap influences who can grow, who stays in farming and who begins to wonder whether the work is still sustainable.
I visited Philo not as a technologist or policymaker, but as someone who grew up in central Illinois and now works to ensure that emerging technologies serve the public good. What I saw on that visit was adaptation, with innovative farmers applying new tools to the same work: growing good crops, caring for the land and keeping their operations viable.
At Parkland College, I met students preparing for careers in agriculture. Many came from farming families. Some planned to return home and take over the business. They explained how AI systems help formalize knowledge passed down through generations, but also raised concerns about affordability and whether farms like theirs will have a place in the future.
Many farmers still see AI as something built without them in mind. The tools are complex, and training opportunities can be hard to find. If these systems are going to work, they need to earn trust in real-world conditions and reflect the judgment of people who know how farms actually operate. That starts with involving farmers directly and respecting their need to stay in control of their land and decisions.
Cost adds another barrier, especially for smaller farms working with tight margins, older equipment and few safety nets. Large operations can often invest in machinery with AI built in. They can afford to take risks and absorb setbacks. For everyone else, one season of bad weather or market volatility can upend everything. In that kind of environment, even modest upgrades can feel out of reach.
Hettinger's farm offers another path. Instead of buying new equipment, he has retrofitted what he already owns with modular AI tools. That approach helps him farm more precisely, cut waste and stay competitive. It's a model worth supporting, especially for farms that can't afford to start over.
Illinois has taken steps to strengthen food systems and support smaller producers, including recent state-level initiatives. But ensuring that AI serves all farmers requires more focused action. Public policy should support adoption in ways that reflect how real farms operate: practical, grounded in local realities and built on systems that already work.
Shared equipment programs, low-interest loans, demonstration projects and training through trusted institutions can expand participation. These investments not only improve resource use and community resilience but also help ensure that the benefits of AI are broadly distributed and accessible to the next generation of farmers.
The future of farming will include advanced AI tools, but whether they work for everyone depends on choices we make now. Every farmer should have a fair shot at using them and staying in the work they know best.