Are X Ray Technicians at Risk Due to AI?

All engineering technologists and technicians, except drafters, not listed separately.

The occupation "Engineering Technologists and Technicians, Except Drafters, All Other" currently has a base automation risk of 0.0%. This exceptionally low automation risk highlights that the core responsibilities in this role are either not easily replicable by current technology or require a level of human oversight, adaptability, and problem-solving that automation technologies cannot yet match. Engineering technologists and technicians are responsible for applying engineering theory and technical skills to solve complex problems, collaborate with interdisciplinary teams, and adapt solutions to real-world constraints, all of which demand nuanced human judgment and context-specific thinking. Among the tasks performed by this occupational group, the three most automatable typically include: data collection and routine measurements, assembling standardized reports, and maintaining records of technical workflows. These tasks are relatively repetitive or rule-based, making them more susceptible to partial automation through digital tools or data management systems. However, while such routine activities can be streamlined, they comprise only a minor part of the overall workflow, and full automation is impractical, as these tasks often intersect with higher-level diagnostic or evaluative work. Conversely, the top three most resistant tasks are: troubleshooting complex, ambiguous technical issues; collaborating with engineers and various stakeholders to innovate or resolve project-specific problems; and adapting methodologies on-the-fly to unique project challenges. Performing these duties requires advanced bottleneck skills such as problem-solving (advanced), critical thinking (advanced), communication (advanced), and adaptability (advanced). These skills are inherently human-centric; they involve synthesizing information, exercising professional judgment, and adapting to unforeseen variables—all domains where automation continues to lag far behind human proficiency. As a result, the role remains resilient against current and foreseeable advances in automation.