As you contemplate the introduction of artificial intelligence, you should articulate what mix of three approaches works best for you. Jeff Heepke knows where to plant corn on his 4,500-acre farm in Illinois because of artificial intelligence (AI). He uses a smartphone app called Climate Basic, which divides Heepke's farmland (and, in fact, the entire continental U.S.) into plots that are 10 meters square. The app draws on local temperature and erosion records, expected precipitation, soil quality and other agricultural data to determine how to maximize yields for each plot. If a rainy cold front is expected to pass by, Heepke knows which areas to avoid watering or irrigating that afternoon. As the U.S. Department of Agriculture noted, this use of artificial intelligence across the industry has produced the largest crops in the country's history. Climate Corp., the Silicon Valley–based developer of Climate Basic, also offers a more advanced AI app that operates autonomously. If a storm hits a region, or a drought occurs, it lowers local yield numbers.

You don't see self-driving cars taking over American cities yet, but robotic tractors already roar through our corn and soybean farms, helping to plant and spray crops. They also gather huge troves of data, measuring moisture levels in the soil and tracking unruly weeds. Combine that with customized weather forecasts and satellite imagery, and farmers can now make complex decisions like when to harvest--without ever stepping outside. These tools are part of a new trend, known as "precision agriculture," that is transforming how we grow crops. Using everything from sensors on combines to drones equipped with infrared cameras that monitor plant health, service providers--ranging from Monsanto and DuPont to startups--take data from the fields, upload it to the cloud, crunch it, and provide farmers with advice on how to run their operations.

During the 20th century, advances in fertilizers, irrigation, and mechanized farming technology helped make it possible to feed a dramatically growing world population. Now, advocates say, the next big advance in agricultural technology may come from the digital world, as modern computer vision, precision sensors, and machine-learning technology help farmers use last century's advances more efficiently and precisely to grow healthier and tastier food. "We're at the cusp of this next wave of innovation in agriculture, which we call digital agriculture," says Mike Stern, the president of The Climate Corporation. "It has to do with, over the past five to seven years, the farm really digitizing, not unlike how our society has changed in terms of the tools and types of things we can do." The Climate Corp., which was purchased by agriculture giant Monsanto for roughly 1 billion in 2013, is one of several companies working to build a digital analytics hub for farmers, merging images from satellites, drones, and cameras, as well as readings for everything from soil thermometers to tractors' on-board computers.

A self-driving John Deere tractor rumbles through Ian Pigott's 2,000-acre farm every week or so to spray fertilizer, guided by satellite imagery and each plot's harvesting history. The 11-ton behemoth, loaded with so many screens it looks like an airplane cockpit, relays the nutrient information to the farmer's computer system. With weather forecasts and data on pesticide use, soil readings, and plant tissue tests pulled by various pieces of software, Pigott can keep tabs on the farm down to the square meter in real time without ever leaving his carpeted office. "This is becoming more standard," says Pigott, who grows a rotation of wheat, oilseed, oats, and barley on his farm in the rolling Hertfordshire countryside an hour north of London. German chemical company Bayer cited the growth in such digitally assisted farming as a key reason for its 62 billion bid for Monsanto, which has become a leading provider of analytics used by growers.