Artificial intelligence in anesthesiology training: understanding preparedness and educational gaps among trainees in Canada

Advances in artificial intelligence are transforming perioperative health care. However, current anesthesiology trainees, who are the future generation of perioperative care providers, demonstrate significant variability in understanding and preparedness for AI integration. Without an evidence-based understanding of trainee needs, curriculum development risks becoming fragmented and inequitable.

To address this national gap, an evidence-based, bilingual survey was designed through a targeted literature search, a two-round Delphi consensus process, and pilot testing. A 26-question survey was distributed nationally across 18 Canadian anesthesiology training programs between June 1 and June 30, 2026. Out of an estimated eligible population, the study had an estimated population response rate of 52.6%.

The study revealed a substantial gap between technology adoption and formal preparation. While a significant majority of trainees reported current use of AI tools in practice, only a small percentage of trainees had received prior AI education. Despite low baseline familiarity, trainees demonstrated strong enthusiasm for integrating AI into residency training, and most expected AI to play a significant role in their future careers.

These findings provide a validated national baseline to guide the design of harmonized, Competency-Based Medical Education (CBME)-aligned AI curricula, faculty development programs, and national training standards across Canada.