Agricultural Technicians

Work with agricultural scientists in plant, fiber, and animal research, or assist with animal breeding and nutrition. Set up or maintain laboratory equipment and collect samples from crops or animals. Prepare specimens or record data to assist scientists in biology or related life science experiments. Conduct tests and experiments to improve yield and quality of crops or to increase the resistance of plants and animals to disease or insects.

The automation risk for the occupation "Agricultural Technicians" is moderately high at 50.2%, close to its base risk of 51.0%. This risk level is influenced by the prevalence of repetitive, process-driven tasks that are increasingly amenable to automation technologies. For instance, many agricultural operations now utilize advanced machinery capable of autonomously preparing land—such as plowing, discing, leveling, or contouring—with minimal human intervention. Similarly, tasks that require the operation of farm machinery, like tractors or combines, are being transformed by automation, as self-driving agricultural equipment becomes more common. Even administrative functions, such as recording data from experiments or animal care, can often be handled by software or Internet of Things (IoT) solutions. However, not every aspect of the agricultural technician’s job is equally susceptible to automation. The top three tasks that show strong resistance to automation are those involving nuanced judgment, interpersonal skills, or the need for contextual understanding. For example, accurately assessing comparative soil erosion across various planting and tillage systems demands in-depth expertise and environmental awareness that current technologies cannot fully replicate. Preparing and presenting agricultural demonstrations involves communication and adaptability, skills that are less easily automated. Additionally, responding to general inquiries from the public requires a degree of responsiveness and human connection that exceeds the capability of most artificial intelligence systems. A significant bottleneck to further automation in this field is the requirement for originality, though it only accounts for a small portion of the work (Originality 3.0%, repeated). Tasks that require creative, innovative thinking—such as devising solutions for unique agricultural challenges or developing novel processes—are much harder to automate. This need for originality is a persistent barrier, as machines and algorithms typically lack the ability to generate new ideas or approaches outside of established parameters. Nonetheless, because originality is not a dominant skill across all aspects of the job, it only slightly mitigates the overall risk. As a result, while many repetitive or routine technical activities are becoming more automated, substantial elements of the job that require human creativity and contextual decision-making remain resistant.