Will Artificial Intelligence Replace Me? Automation Susceptibility of Emergency Physician Tasks.

Authors

Christian Rose, Emily Molins, Austin Schoeffler, Rana Kabeer, Morgan R Frank, Carl Preiksaitis

Published in

Annals of emergency medicine. Sep 02, 2026. Epub Sep 02, 2026.

Abstract

To apply Autor's labor economics task framework to classify emergency physician tasks by automation susceptibility and map current artificial intelligence (AI) capabilities to each category.
We synthesized 6 published time-motion studies, ACGME Core Entrustable Professional Activities, and the O∗NET emergency physician task inventory into a unified list of 14 task categories. Two board-certified emergency physicians independently classified each task using Autor's 4-category framework. Current AI capabilities were mapped to each task using a 3-tier schema: Replace, Augment, or No Current Application.
Nine tasks (64.3%) were classified as nonroutine abstract, 3 (21.4%) as routine cognitive, and 2 (14.3%) as nonroutine manual. No tasks were Routine Manual. AI replacement is concentrated in routine cognitive tasks (documentation, medical records review, emergency department operations management), which consume 20% to 40% of physician shift time. Augmentation dominates in nonroutine abstract domains. Nonroutine manual tasks show minimal AI penetration.
Routine cognitive tasks consume a disproportionate share of emergency physician shift time, making them the immediate target for AI-driven workflow restructuring. Beyond this, augmentation of nonroutine abstract tasks is accelerating, warranting ongoing reassessment of automation boundaries across all task categories. As AI capabilities continue to expand, structured task-level analyses of this kind will be essential for anticipating workforce needs and informing AI implementation strategy, residency training design, and physician preparation in emergency medicine.

PMID:
42687470
Bibliographic data and abstract were imported from PubMed on 03 Sep 2026.

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