Computer, Automated Teller, and Office Machine Repairers
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Repair, maintain, or install computers, word processing systems, automated teller machines, and electronic office machines, such as duplicating and fax machines.
The occupation "Computer, Automated Teller, and Office Machine Repairers" has an automation risk of 45.4%, closely aligning with its base risk of 46.0%. This moderate level of risk is due to the hands-on and technical nature of repair work, which includes tasks that are becoming more susceptible to automation, especially as diagnostic and assembly-related roles are increasingly performed by machines. Many components of this job are routine and follow standardized procedures, making them ideal candidates for robotic or automated solutions. However, the risk is not overwhelmingly high because the position retains a number of tasks that require human judgment and nuanced problem-solving. Additionally, customer interaction and decision-making elements remain difficult for machines to replicate accurately. The most automatable tasks within this occupation include reassembling machines after repairs or part replacements, conversing with customers to determine equipment problems, and disassembling machines to examine worn or defective parts using tools and measuring devices. These processes are either highly repetitive, measurable, or can be executed through clear procedural steps, making them attractive for automation. Modern advances have enabled machines to perform physical assembly and disassembly with increasing dexterity, and AI-powered chatbots can be deployed for basic troubleshooting and customer communication. Automated diagnostic tools can also scan and identify issues within hardware, reducing the demand for human intervention in the initial stages of repair. Despite these advances, some tasks remain highly resistant to automation, such as calibrating testing instruments, training new repairers, and filling machines with specific fluids like toners or inks. These activities often require a combination of nuanced judgment, dexterity, and adaptability, which are hard for machines to replicate. The need for originality, while present at only 2.8% to 2.9% according to bottleneck skill data, still plays a crucial role, especially in troubleshooting unexpected problems or teaching others. These resistant factors help maintain significant human involvement in the field, ensuring that automation cannot fully displace the occupation in the foreseeable future.