In a risk analysis published in the journal Nature Machine Intelligence in 2022, researchers wrote that there could be huge risks to using new artificial-intelligence technologies at scale to meet the challenge of feeding our growing human population in sustainable ways.
“The idea of intelligent machines running farms is not science fiction,” Asaf Tzachor, from University of Cambridge’s Centre for the Study of Existential Risk and one of the paper’s authors, said in the report. “Large companies are already pioneering the next generation of autonomous ag-bots and decision support systems that will replace humans in the field,” he added.
He went on to point out, though, that “so far, no one seems to have asked the question, ‘are there any risks associated with a rapid deployment of agricultural AI?’”
So, why is there so much interest in using artificial intelligence in agriculture? Are people just carried away by new and shiny futuristic technologies, or does the farming world actually need AI?
The short answer is yes; we need it.
Agricultural growers are facing a labor shortage while the global population is rising. According to United Nations projections from 2022, today’s population of more than 8 billion is expected to hit 9.7 billion in 2050 and 10.4 billion in 2100, which means we’ll need to produce a great deal more food.
Meanwhile, we’re dealing with water shortages and global warming. Patrick Schnable, director of the Plant Sciences Institute at Iowa State University, told the BBC in March that all projections indicate climate change will cause major losses in crop yields.
On top of those challenges, fewer young people are going into agriculture.
The average age of U.S. farmers in 2022 was 58.1 years, up 0.6 years from 2017, according to the Department of Agriculture’s Census of Agriculture.
This rising average age is part of a long-term trend.
Jim Carroll, a futurist and innovations expert who regularly speaks to leading corporations about agriculture, is optimistic about using AI in the industry and thinks it could attract younger generations — such as those who spend their time playing video games, and who, he says, people may underestimate.
Take the social-network farmland management game FarmVille, he tells The Rooted Journal. The game teaches players “how to run a virtual, 24-hour environment,” he says, adding that it could be a model for how farming could look in real life with the implementation of AI technologies such as autonomous vehicles — an area he says is growing “faster with farming technology than with cars.”
He likens the integration of AI into agriculture as “a big, real-life virtual FarmVille,” adding that he thinks “that type of thing will draw that generation back to the farm.”
Feroz Sheikh, the chief information and digital officer of the agritechnical company Syngenta Group, also thinks AI could help the agricultural industry. He told the consulting firm Gartner in 2023 that “as the population continues to grow, as the world food crisis continues to become more and more severe,” the best way to feed the world’s population is “through the use of technology.”
He believes there are two main societal problems to solve. The first is to help create more sustainable farming practices, and the second is to ensure food safety for the world.
The smart use of AI by the agricultural industry may help us work toward those goals. And in the U.S., experts say the majority of agricultural businesses are already embracing AI.
By November 2021, 87% of all U.S. agricultural businesses were using some form of AI in their farming operations, according to a report from the analytical firm RELX and the agritech software company Proagrica.
Lindsay Suddon, chief strategy officer at Proagrica, has said that the findings show “that the ag sector is heading in the right direction in embracing technology to build in greater efficiencies.” He added that “this bodes well for the next generation of growers, who will expect technological literacy across the sector, which will only bring further success, and therefore more innovation.”
How the Future of AI in Agriculture Could Look
1. Data-driven Farming and Computer Vision Might Revolutionize Agriculture
Data-driven farming involves using data to improve agricultural decision-making and crop-yield outcomes. Experts believe it’s one way for farmers to achieve more sustainable farming practices and better food safety.
Computer vision, a branch of AI that processes an image or video from a camera, is one component of data-driven farming that could be particularly helpful in improving yields and sustainability. It uses machine learning and neural networks to see — and interpret — the world the way a person does. The data gleaned from computer vision may come from satellite images, drones, or stationary cameras, and the technology uses deep learning algorithms to analyze and understand the footage.
An example is Penn State’s Huck Institutes of Life Sciences app PlantVillage, which uses computer vision to diagnose crop diseases from photos uploaded by cell phone. After a farmer uploads a photo and enters the crop type, location, and planting date, PlantVillage sends advice via smartphone, SMS, or social network. The project aims to provide smallholder farmers worldwide with technology that offers them the knowledge to grow more food.
Computer vision can also count fruits and vegetables in the field, estimate yields, and identify diseases. This saves time and labor, gets crops to market faster, and lets farmers spend more time on the business side of their operation. Computer vision-enabled machines can also sort and grade a harvest, such as potatoes or apples, much more quickly than humans with the ability to sort produce by size, weight, color, and ripeness — and even determine which foods should be shipped from the farm first based on perishability.
Some livestock farmers already use computer vision to automatically monitor animals in real time as well. The technology can identify animals, track their locations, ensure they have access to food and water, and watch for injury, disease, or abnormal behavior.
Cameras with computer vision are also used for remote, real-time security monitoring and surveillance. For example, they can detect foxes breaking into a chicken coop or livestock damaging equipment or crops and use deep neural networks to perform facial recognition on human intruders.
2. Internet of Things Sensors Gather Information for Data-driven Farming
Internet of Things sensors are an integral part of data-driven farming. For instance, farmers can use IoT sensors to collect real-time data that computer vision algorithms then interpret to identify types of weeds, insects, and diseases; analyze soil moisture and nutrients; determine root health conditions; monitor soil erosion; conduct pH analyses; and make decisions regarding weather conditions.
Sensors can also optimize irrigation systems, analyze patterns to detect leaks and other damage, and notify farmers if there’s a problem.
3. More Robots are Doing Our Farm Work
While we may picture farmers driving tractors across fields for hours in the hot sun, that’s not always the case.
Autonomous tractors — many of which also use robot technology and precision positioning systems — can drive on farms without a human operator around the clock and in many weather conditions, boosting productivity and profits. On their own, they can mow, plow, plant crops, and spray for weeds and pests. The precise application of fertilizer, pesticides, and water could mean better yield, less need for manual labor, and less waste or negative environmental impact.
A number of companies have developed robots that can do farm work autonomously. One such company is Earthsense, which produces beagle-sized robots capable of pulling weeds, diagnosing crop infections, and gathering other data that could help farmers be far more efficient in caring for crops with fewer laborers.
While these types of systems aren’t yet in widespread use, Earthsense’s cofounder Girish Chowdhary and others hope this sort of precision agriculture leads to a different kind of sustainable farming that doesn’t just focus on growing more crops on the same amount of land, but instead prioritizes small farms growing a more diverse collection of high-value crops using fewer chemicals.
The market-research consultancy Grand View Research projects that the global agricultural robots market — which it valued at $12.94 billion in 2023 — will reach $48 billion by 2030.
Many farmers already rely on agricultural robots. For example, in 2022, milking made up 30% of the global agricultural robots market with dairy farmers opting to increase milk production by using the technology to feed their cows night and day.
There are also robots that can pollinate flowers, harvest lettuce, and pick delicate strawberries. And there are even “robot swarms,” or coordinated groups of autonomous robots that can collaborate on agricultural tasks on the ground or in the air like drones.
4. Robots May Operate Leaf by Leaf
In 2014, Blue River Technology launched the LettuceBot, a machine learning-powered robot that can roll through a field photographing 5,000 young lettuce plants per minute, using AI algorithms to note whether each sprout is a weed or lettuce.
It precisely sprays pesticides on each weed it comes across, and if it discovers a lettuce plant that isn’t growing well or is too close to another, it also sprays that. Willy Pell, now CEO of Blue River Technology, has said that the LettuceBot’s precision means much lower amounts of pesticides are used on a farm, reducing farmers’ use of chemicals by 90%.
5. Robot Tractors Offer Many Benefits
Robots take up less space than traditional farm equipment and work well for farmers with smaller acreage. They can result in higher yields because they can sometimes help farmers use land that’s otherwise difficult to reach, such as high on mountaintops or in tight spaces.
Because they use computer vision for precision, fewer herbicides are needed and applied. They can reduce pesticide use by up to 80% on some large U.S. corn farms, according to McKinsey & Company, resulting in less pesticide wastage, which also protects human workers from the effects of administering chemicals by hand.
The electric vehicles also don’t emit diesel fumes and run quietly, which negates the need for hearing protection as with traditional tractors.
Robot tractors have safety features such as 360-degree cameras that could prevent collisions as well.
6. How Farmers Are Using AI-powered Drones
AI-powered drones can monitor crop health, growth, and production; spray pesticides; keep an eye on irrigation; collect soil and water samples; account for the movement and count of livestock; and even serve as a security system.
Farmers use drones to plan their planting and pest management better and achieve the best possible yields. In March 2024, the Federal Aviation Administration granted an exemption to its drone regulations that allows a two-person team to fly “drone swarms,” or fleets of drones weighing 55 pounds or more. These can work with great precision and efficiency; a swarm of three may be able to spray 150 acres per hour, according to Hylio, a Texas company that makes autonomous drones for precision crop spraying.
Drones can also monitor conditions remotely, for example, after a storm when roads are impassable. With this technology, a farmer can “fly” over their farm to check for any issues caused by a storm, find accessible roads, and organize any repairs and emergency harvests that may be necessary.
7. Experts See the Benefits of Using AI in Farming
Many experts in the industry believe the benefits of using AI in farming outweigh the risks.
They agree that AI use can reduce environmental impacts on land, and complete tasks faster and often more precisely. Better efficiency means farmers require less land than in the past, and robots, unlike humans, can work 24/7 to get more done.
Using AI for farming also means farmers can operate remotely when needed and use data-driven insights for better-informed decision-making, resulting in more efficient farming and food production, an improved supply chain, and greater financial sustainability.
AI technologies like Headwall’s Hyperspectral Imaging Systems have enabled the widespread adoption of precision agriculture techniques. This involves using sensors, drones, and AI algorithms to collect and analyze data on crop health, soil conditions, and weather patterns. Farmers can use this information to optimize water usage, reduce pesticide application, and increase overall crop yields.
Advances in AI have led to the development of autonomous farming equipment. This includes self-driving tractors like John Deere’s 8R and other robotic systems capable of planting, irrigating, and harvesting crops. These technologies can operate with high precision, reducing labor costs and increasing efficiency on the farm.
AI-powered systems like the ones developed by Fermata are increasingly being used to detect and diagnose crop diseases. By analyzing images of leaves or plants, AI algorithms can identify signs of disease or nutrient deficiencies early on, allowing farmers to take proactive measures to prevent crop loss and optimize plant health.
8. The Potential Risks Involved
While incorporating AI in agriculture can be beneficial in a number of ways, experts agree that there are also potential negatives.
Some farmers don’t want to embrace new technologies. Others operate in rural farming communities where broadband internet is unavailable and may be left behind.
A serious concern is that AI and machine learning will handle some low-skilled jobs usually held by seasonal and migrant workers, who may have trouble finding other work.
The initial costs of adopting AI are high and can be difficult for small-scale farmers. Integrating computer vision, robotics, sensors, and other AI technology with one’s existing farm practices and equipment can be complex.
Reliance on new tech could also make farmers vulnerable to power outages, technical malfunctions, and other disruptions.
Data security is another critical concern. The more data you collect and store in the cloud, the more vulnerable you are to data leaks and cyberattacks. There’s even the danger of hackers interrupting the management of entire fields of crops, which could put farmers at risk and interrupt food supplies.
Also, there are ethical concerns that AI could be programmed to increase yields and ignore any negative environmental impacts.
9. AI and Getting Food on the Table
Consumer perceptions may play a significant role in how AI impacts farming in the future. For instance, if consumers start demanding more food be produced without as many chemicals, that may encourage and support the adoption of more agricultural AI.
AI is not only poised to substantially impact how we produce food, but also how it moves through the supply chain, and from the grocery store to consumers’ refrigerators at home. For example, by using sensors, decreasing the use of herbicides, and increasing yields, AI tech can positively impact supply and demand, stabilizing costs, analyzing sales data and customer preferences over time, and improving the shopping experience.
As for how the agricultural industry will receive the integration of AI, that depends on the farmer, Carroll says. He points out that Syngenta once identified two types of farmers. One, he says, is the apathetic minority — those who “march to Washington and seek out the same old people, the same old advice and keep doing the same things,” and who are “not going to try new ideas.” The second is the type that focuses on the future, regardless of their age. “They’re positive, and they’re willing to try new ideas,” he says of this group. “They ingest new technology.”
The latter group who are already embracing certain AI technologies, paired with advances in the field, give Carroll hope. “What is happening right now is that the pace of research development and implementation is accelerating,” he says.
“At the same time, we are getting this new younger generation taking over the family farm or the factory farm,” he continues. “Kids today, they’ve never known a world without technology. And if you take the typical young farmer, their mindset with precision and all these other things, their attitude is, ‘Bring it on, I want to use that stuff.’”
“When you combine those different trends,” he adds, “that’s the root of my optimism.”
