Robotics Engineers
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Research, design, develop, or test robotic applications.
The occupation "Robotics Engineers" has been assessed with an automation risk of 50.0%, slightly below the base risk of 51.0%. This moderate risk level reflects an even split between tasks that are susceptible to automation and those that are resistant. Robotics engineering as a field combines highly technical work with creative and strategic thinking—while some routine aspects of the job can be automated, many core responsibilities still require human judgment and innovation. The base risk serves as a general benchmark, but the specific nature of robotics engineering tasks brings the actual risk closer to parity. Factors such as project variety, rapidly evolving technology, and the need for specialized knowledge all contribute to maintaining a sizable demand for human professionals in this occupation. Among the most automatable tasks for robotics engineers are "creating back-ups of robot programs or parameters," "providing technical support for robotic systems," and "designing end-of-arm tooling." These tasks are highly structured and rule-based, making them easier to delegate to automation software or AI systems. For instance, backing up data and providing standardized technical support can be streamlined through dedicated algorithms or self-diagnostic robotics platforms. Similarly, repetitive design work involving end-of-arm tooling can often be performed or even optimized by generative design software, reducing the need for direct human involvement in these areas. The high potential for automation in such tasks directly influences the overall risk percentage. However, significant aspects of the robotics engineering role remain resistant to automation. Tasks like "automating assays on laboratory robotics," "designing robotics applications for manufacturers of green products," and "planning mobile robot paths and teaching path plans to robots" rely heavily on creativity, domain-specific problem-solving, and adaptation to novel challenges. These activities frequently require the bottleneck skill of originality, which is measured at relatively low levels of automation (3.9% and 4.6%). Original thinking is key in developing new approaches for unique manufacturing or laboratory situations and in optimizing robots’ movement paths within dynamic environments. The continued need for human ingenuity and customization in these domains acts as a counterbalance to automatable elements of the job, ensuring that robotics engineers will remain vital contributors well into the automated future.