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Peer-reviewedCC BYInternational Journal of Emergency Medicine

The inflection point: embracing responsible artificial intelligence in medical education

  1. 1AdventHealth East Orlando
  2. 2University at Buffalo

Abstract

Artificial intelligence (AI) adoption in medicine has substantially outpaced its formal integration into medical training programs. This editorial synthesizes the evidence on AI in medical education, examining rapid growth alongside thin long-term outcomes data and structural tensions across curriculum, assessment, and global equity. Technology dependence, institutional inequity, and the mismatch between AI-enabled training and AI-free board examinations emerge as under-addressed challenges. We propose a four-tier disclosure framework to standardize transparency in AI-assisted scholarship and argue that AI literacy now constitutes a core clinical competency. Governance scholarship must match the pace of capability research if the field is to advance responsibly.

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BibTeX
@article{mclean2026inflection,
  title = {{The inflection point: embracing responsible artificial intelligence in medical education}},
  author = {Mary McLean and Jesus Montiel},
  journal = {International Journal of Emergency Medicine},
  year = {2026},
  month = nov,
  doi = {10.1186/s12245-026-01418-4},
  url = {https://doi.org/10.1186/s12245-026-01418-4},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - The inflection point: embracing responsible artificial intelligence in medical education
AU  - Mary McLean
AU  - Jesus Montiel
PY  - 2026
DA  - 2026/11/15
JO  - International Journal of Emergency Medicine
DO  - 10.1186/s12245-026-01418-4
UR  - https://doi.org/10.1186/s12245-026-01418-4
AB  - Artificial intelligence (AI) adoption in medicine has substantially outpaced its formal integration into medical training programs. This editorial synthesizes the evidence on AI in medical education, examining rapid growth alongside thin long-term outcomes data and structural tensions across curriculum, assessment, and global equity. Technology dependence, institutional inequity, and the mismatch between AI-enabled training and AI-free board examinations emerge as under-addressed challenges. We propose a four-tier disclosure framework to standardize transparency in AI-assisted scholarship and argue that AI literacy now constitutes a core clinical competency. Governance scholarship must match the pace of capability research if the field is to advance responsibly.
SN  - 1865-1380
SN  - 1865-1372
ER  -