Medical Scientists, Except Epidemiologists

Conduct research dealing with the understanding of human diseases and the improvement of human health. Engage in clinical investigation, research and development, or other related activities.

The occupation "Medical Scientists, Except Epidemiologists" has an automation risk of 45.6%, which is close to the base risk of 46.4%. This moderate risk level reflects both the technical and intellectual demands of the role, as well as the degree to which routine laboratory activities and analytical processes can be automated. Many procedures in research settings can be streamlined through robotics and AI tools, especially tasks that require following strict protocols or analyzing data from controlled experiments. Automation technologies are increasingly capable of performing repetitive tasks with high precision, thus posing a certain risk to aspects of this profession that are process-driven and rule-based. Among the most automatable tasks for medical scientists are "following strict safety procedures when handling toxic materials to avoid contamination," "evaluating effects of drugs, gases, pesticides, parasites, and microorganisms at various levels," and "planning and directing studies to investigate human or animal disease, preventive methods, and treatments for disease." These responsibilities often involve structured, repeatable activities, such as monitoring experiments, processing samples, and conducting standardized tests—activities robots and AI can efficiently handle. For routine experimental setups or data collection, automation offers significant improvements in consistency and scale, minimizing human error and freeing up time for more complex investigative work. In contrast, the tasks most resistant to automation are heavily reliant on human judgment, creativity, and collaborative skills. These include "consulting with and advising physicians, educators, researchers, and others regarding medical applications," "conferring with health departments, industry personnel, and others to develop public health programs," and "using advanced, specialized equipment where hands-on expertise and adaptability are needed." The bottleneck skills identified, such as originality (noted at levels of 3.3% and 4.0%), further underscore this resistance, as the role often requires generating novel hypotheses, designing new experiments, and interpreting nuanced results that current AI cannot replicate. Thus, while routine aspects of the job are increasingly automatable, leadership, advisory, and innovative functions keep the overall risk of full automation moderate rather than high.