Anesthesiologists
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Administer anesthetics and analgesics for pain management prior to, during, or after surgery.
The occupation "Anesthesiologists" has an automation risk of 38.3%, which is slightly below its base risk estimate of 38.9%. This moderate level of risk reflects the dual nature of anesthesiology: while many tasks are procedural or data-driven, the job also requires complex judgment and rapid adaptation. Notably, the top three most automatable tasks include: monitoring patients before, during, and after anesthesia and counteracting adverse reactions or complications; recording the type and amount of anesthesia administered and the patient’s condition throughout the procedure; and providing and maintaining life support as well as airway management, especially when preparing patients for emergency surgery. These activities have a significant procedural element, involve routine monitoring, data collection, or repetitive documentation, all of which are increasingly amenable to automation by advanced technologies. However, several essential responsibilities within anesthesiology are far more resistant to automation, which tempers the overall risk score. The most resistant tasks are conducting medical research to control or cure diseases, investigating new medications, and developing and testing novel medical techniques. Other resistant tasks include scheduling and maintaining surgical suite resources and equipment, and especially instructing individuals and groups on ways to preserve health and prevent disease. These activities require higher-level critical thinking, interpersonal skills, and creativity—qualities that are difficult for AI and automation technologies to fully replicate. Research and instruction, in particular, necessitate an ability to synthesize new information, communicate clearly, and adapt content to diverse audiences. The bottleneck skills that protect anesthesiologists from total automation are closely linked to originality, with measures at 2.9% and 3.0% respectively. While these percentages might seem low, they reflect the specific importance of creative problem-solving and novel thinking in anesthesiology—especially when individual patient reactions to anesthesia can vary widely, or when new medical challenges arise. The need to design custom solutions on the fly, develop new medical protocols, and train others in their use ensures that human oversight remains vital. As such, while portions of the anesthesiology workflow may be delegated to automation, the profession will continue to require uniquely human skills for the foreseeable future.