On a farm in Phoenix, one person with an iPad can weed a field of vegetables that once required 20 workers on their hands and knees under a hot sun.
The Duncan Family Farms employee controls the LaserWeeder, an AI-powered machine created by tech start-up Carbon Robotics, that attaches to the back of a tractor. It identifies and eliminates unwanted weeds with a laser, illuminating the ground like a flickering Xerox machine as it crawls over carefully planted fields.
“Like Star Wars,” says Courtney Boyer, the supply chain manager for Duncan Family Farms.
Technology is fundamentally changing the job description of the American farmer, making certain types of labor obsolete while creating new opportunities. Advancements in AI have enabled more efficient, sustainable and cost-effective farming techniques by reducing water consumption and allowing more precise application of pesticides and fertilizers. Its use also promises to solve the decades-long problem of trying to make farming cool again for young workers.
“AI will create new types of jobs, different types of jobs,” says Madhu Khanna, a distinguished professor in environmental economics and director at the Center for Economics of Sustainability at the University of Illinois at Urbana-Champaign. Farm work will evolve from “labor-intensive, backbreaking manual labor,” says Khanna, to “managing a swarm of robots.”
Precision agriculture was the precursor to AI
During the early 1990s, the precision agriculture movement focused on eliminating uncertainties in agriculture to maximize farm output. The practice leverages a combination of technologies — including GPS, automation, remote sensing and yield monitoring — to provide crops and soil exactly what they need when they need it.
These same tools have evolved rapidly with advancements in robotics, automation and AI — software that can learn from and mimic human intelligence. Farmonaut, an agricultural technology company, reports that 60 percent of U.S. farms now employ AI, requiring agricultural drone operators and automation engineers, among other technical jobs.
“Labor is a huge problem for producers,” says Jordan Jobe, manager of the AgAID Institute, a research initiative working to build partnerships between agricultural communities and AI companies such as Innov8.ag. “It’s the biggest complaint we have for sure.”
New technology could play a crucial role in bringing young people back into America’s oldest workforce where the average age of a farmer is 58, according to the 2022 Census of Agriculture conducted by the Agriculture Department. Jobe partners with Washington State’s Future Farmers of America Program to get students excited about agricultural technology.
“That audience is stoked,” Jobe says. “Kids in high school recognize immediately the impacts that drones, machine learning tools, and robotics can have. They are excited to get involved, where their grandparents or parents might feel less comfortable.”
Cody Wadsworth, 35, is part of the emerging agricultural workforce. An operations specialist at AirField Ag, he provides aerial spraying services to farms in the mountainous West. The main benefit, he says, is precision, because drones can fly slowly at an average height of 10 to 12 feet, their rotor blades creating a vortex that pushes the chemicals down into the canopy.
More conventional crop dusters and helicopters can also fly low but they have to fly at faster speeds — 60 to 145 mph, approximately — to apply fertilizers and pesticides, and they are less accurate. The planes are also more expensive to buy and maintain, and the job can be dangerous for pilots.
“We can go out and gather imagery of crop health, then provide maps and custom prescriptions to enable variable-rate applications,” says Wadsworth, who nicknamed his 300-pound drone “the grunt laborer.”
Soil analyses once required a team of people to take samples and an off-site lab to send back results days later. A smaller drone used by AirField Ag surveys the land, capturing field data the AI analyzes.
“Day to day, it’s about making the farmer more productive and more efficient,” says Jorge Heraud, 55, CEO of TerraBlaster, a tech start-up that employs AI, machine learning and NASA-derived laser technology to analyze soil nutrients from an attachment on a tractor.
Previously, Heraud co-founded a company called Blue River Technology that revolutionized the application of herbicides. The company’s “See and Spray” system — first used on vegetables in 2012 and in cotton and other larger row crops in 2015 — uses high-tech cameras, AI and robotics to detect and precisely eliminate weeds. “Similar to your iPhone that detects your face to unlock it,” Heraud says.
The result is a three- to fivefold reduction in pesticide use. For Heraud, these kinds of technological advancements, which increase efficiency and productivity on farms, will be critical to feeding a growing population and addressing continued labor shortages.
“With the same amount of time with the same amount of capital, farmers can be more productive and efficient,” Heraud says. “Technology allows farmers to do more.”
AI is not a panacea
This AI-enabled precision can help reduce ecological damage. By reducing the number of pesticides and fertilizers, there is a chance to reverse the health of altered ecosystems, contaminated water sources and degraded soils worldwide.
Different environmental concerns remain, however. The computing infrastructure supporting AI, for agriculture or otherwise, consumes an enormous amount of power and water. According to the Penn State Institute of Energy and the Environment, data centers could account for 20 percent of global electricity use by 2030 to 2035. As AI grows in importance, it could add to the already hefty carbon footprint of global agriculture.The expansion of AI in agriculture also raises a range of ethical concerns over job displacement, corporate consolidation and data ownership and privacy.
“We do need ethics to govern how we use it, but I do also think it’s inevitable,” Jobe says. “For agriculture, the efficiencies to be gained probably outweigh the dangers.”
Yet many argue that the increased efficiency fueled by AI will be key to feeding a growing global population projected to reach almost 10 billionby 2050. The Food and Agriculture Organization estimates that food production needs to increase 70 percent at the same time amid shrinking farmland, dwindling resources and the adverse effects of climate change.
“The way we farmed 20 years ago was not that different from 150 years ago, just tractors instead of horses,” Wadsworth says. “I think the mindset is shifting. We have a limited quantity of land. The question is how to make it the most efficient and productive?”
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