Abstract

Artificial intelligence (AI) is increasingly embedded in clinical decision support, documentation, imaging, predictive analytics, and workflow management. However, the educational systems responsible for preparing practicing physicians to use AI have not fully addressed the interpretive, ethical, and organizational demands of AI-supported care. This qualitative case study examined how continuing medical education (CME) shapes physicians’ readiness to integrate AI into clinical practice. Guided by the Unified Theory of Acceptance and Use of Technology (UTAUT) and human resource development (HRD), the study analyzed semi-structured interviews with 14 physicians from diverse specialties within a large academic health system. Organizational artifacts, including CME announcements, internal communications, and evaluation materials, were also examined to support triangulation. Findings indicate that CME was most influential when it framed AI as support for clinical attention rather than as decision authority, developed interpretive judgment, reinforced physician accountability, connected formal instruction to informal workplace learning, aligned with clinical workflow, and supported trust calibration over time. The study argues that AI-focused CME should be designed as a longitudinal organizational learning system rather than a discrete instructional event. Implications are offered for technology integration, faculty development, and organizational learning in clinical education.

Description

For all papers published in AIRCC journals, the copyright of the paper is retained by the author under Creative Commons (CC) Attribution license. This license authorizes unrestricted circulation and reproduction of the publication by anybody, as long as the original work is properly cited.

Publisher

AIRCC

Date of publication

Summer 6-23-2026

Language

english

Persistent identifier

http://hdl.handle.net/10950/5081

Document Type

Article

Publisher Citation

Murphy, T., & Carpenter, R. E. (2026). Continuing medical education as a workforce learning system for artificial intelligence in clinical practice. International Journal on Integrating Technology in Education, 15(2), 29–43. https://doi.org/10.5121/ijite.2026.15203

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