[Global “Ag Talk”] Why Did U.S. Agriculture Choose Robots?

[Global 'Ag Talk': Capturing the Future of Agriculture] Assistant Professor Choi Dae-eun, University of Florida, USA

At strawberry farms in Florida, the United States, annual profits are determined by more than just the weather. Being able to find workers to harvest on time is just as important. Crops such as strawberries and tomatoes, which I study, still rely heavily on human eyes and hands for harvesting and crop management. If farms cannot secure the labor they need during the period when crops ripen quickly, even high-quality produce can miss its harvest window and lose its market value. The problem is that this labor shortage is not a temporary phenomenon. Agricultural labor is becoming increasingly scarce, and labor costs are also steadily rising. According to a U.S. Department of Agriculture survey, the average wage for agricultural workers in April 2025 was $18.43 per hour, up 3% from the same period a year earlier[DC1] . On top of this, the aging of the existing workforce is changing the direction of agricultural technology development in the United States by raising the question, “Who will work on farms in the future?”.

The severity of this problem varies by crop. Crops such as corn and wheat, which have long been extensively mechanized, are relatively less affected. But fruit and vegetable crops such as strawberries, tomatoes, apples, and grapes are in a different situation. Tasks such as selecting and picking ripe fruit without bruising it, or detecting diseases and pests among densely tangled leaves and stems, still require delicate human judgment. It is precisely at this point that robotic harvesters, autonomous farm machinery, and AI-based scouting robots are rapidly moving from 'new technologies in the laboratory' to 'essential equipment in the field'.

From precision spraying to harvesting: automation technology enters the field
A notable recent change in U.S. agricultural technology is the rapid expansion of the commercialization of automation technologies. Autonomous tractors and precision weeding·spraying technologies have already been introduced on commercial farms, and fruit·vegetable harvesting robots are also advancing beyond research prototypes to the stage of commercial validation. Autonomous farm machines equipped with cameras and artificial intelligence move on their own, distinguish crops from weeds, and spray herbicides or pesticides only where needed. Unlike conventional methods that uniformly spray the same amount across an entire farm, these systems identify where treatment is needed and work with precision, reducing both pesticide use and worker exposure. If robots take on repetitive and physically demanding tasks, farms can assign their limited labor force to more complex judgment and management work.

Development of fruit·vegetable harvesting robots is also continuing. When cameras determine the location and ripeness of fruit, a robotic arm approaches the target, and a device designed not to damage the crop harvests the fruit. However, working as quickly and flexibly as a human is still not easy. Sometimes the robot fails to find fruit hidden by leaves, or cannot respond to the different shapes and positions of crops. Beyond harvest speed and success rates, there are also many practical challenges to solve, including purchase costs, maintenance, and breakdown response.

Robots evolving into farm decision-making platforms
At research and demonstration sites, autonomous robots and quadruped robots that patrol farms and record crop conditions are also being tested. These robots continuously collect data on crop growth conditions, fruit set volume, and signs of disease that would be difficult for people to check every day across large farms. The important point is that robots do not simply stop at taking pictures. By analyzing accumulated image and sensor data with artificial intelligence, it becomes possible to identify where problems have occurred on the farm and which areas should be prioritized for management. Robots are evolving not only as machines that replace labor, but also as information-gathering platforms that support farmers’ decision-making.

Movements in the agricultural machinery industry also show this change. Major agricultural machinery companies are rapidly incorporating autonomous driving and artificial intelligence technologies into their existing product lines, while agricultural robotics companies are moving beyond simply demonstrating new technologies and focusing on proving how much labor and farm inputs they can actually save. Farmers now ask not how advanced a robot is, but how long it will take to recover the investment cost, and how easily it can be applied to existing work methods. The standard of competition in automation technology is shifting from technical possibility to economic feasibility and field applicability.

Korean agriculture needs a phased adoption strategy
This trend is not entirely new to Korea. In Korea as well, autonomous farm machinery and spraying drones are being introduced into agricultural fields, and research and demonstration of fruit·vegetable harvesting robots and AI-based crop growth diagnosis technologies are actively under way. The awareness that farm work must be automated in response to rural population decline and aging is also not very different between Korea and the United States.

What Korea should pay attention to in U.S. agricultural automation is not the types of new robots, but the way the technology is introduced into the field. Even in the United States, commercialization is progressing first in tasks such as weeding, spraying, transport, and scouting, where the labor burden is high and the effects of automation can be relatively easily verified, rather than in robots that make all farm work unmanned at once. This is a method of solving the problems farmers are facing right now one by one and proving the effects in terms of labor hours and cost.

Korean-style agricultural automation: 'small-scale and modularization' and new business models
There are also clear differences between the agricultural environments of Korea and the United States. The United States, with relatively large farmland and high agricultural labor costs, can more easily secure the economic viability of large equipment. By contrast, Korea often has smaller and more complex farmland, making it difficult to apply large autonomous equipment from the United States as is. However, Korea has strengths in facility cultivation, high-density production, and information and communications infrastructure. Therefore, rather than imitating U.S. technology, Korea’s agricultural automation needs to focus on small robots that can work precisely even in narrow spaces, modular equipment that can be used for multiple crops and tasks, and automation technologies that can be combined with existing agricultural machinery.

Another challenge is narrowing the gap between technology development and farm adoption. Even if a robot shows high recognition accuracy and task success rates in research settings, it cannot lead to commercialization if farmers find it difficult to purchase and maintain. Along with technology development, business models must also be prepared, not only direct equipment sales, but also agricultural robot services that charge based on work area or usage time, shared use at the regional level, and rapid maintenance systems.

Let us change the future of agriculture with robots that stand guard over the fields together
Agricultural automation in both Korea and the United States faces the same challenge: redesigning production systems within a shrinking labor force. The reason U.S. agriculture chose robots is not because the technology is new, but because if people cannot be found, production itself cannot continue. The U.S. case also clearly shows the standard for automation. It is not a robot that shows high performance in a single demonstration, but a robot that can actually be deployed every harvest season, can be repaired quickly when it breaks down, and can recover its investment cost through saved labor expenses. Korean agriculture, too, must shift the goal of technology development from ‘more advanced robots’ to ‘robots that farmers can continue to use’. What will change the future of agriculture is not a robot that receives applause in a one-time demonstration, but a robot that stands guard over the fields alongside farmers during the busiest harvest season.