Survey of Physician Attitudes on Artificial Intelligence

Objective To better understand how physicians view the potential use of artificial intelligence (AI) in their practices. Method We conducted an online cross-sectional survey of 1,258 physicians (MD, DO, MBBS or equivalent) in the United States (US) and Canada from December 2023 through February 2026. The survey contained 34 questions focused on 6 areas: (1) demographics, (2) training, (3) clinical benefits, (4) clinical concerns, (5) clinical AI prediction tools, and (6) generative AI. Results A total of 130 completed surveys were received (response rate, 10%). Top specialties included psychiatry (46.2%), internal medicine (14.6%) and pediatrics (13.8%). A total of 16.9% had training in computer science or information technology and 40.8% in statistics. Nearly half (46.9%) had no formal training in AI and were self-taught. Those with training in AI received it through vendors or at work. Sixty to seventy percent thought AI would provide diagnostic aid or treatment recommendations, but half did not feel adequately trained to safely use AI in practice. Over 70% thought it could help with administrative tasks. More than 80% were worried about errors, misinformation, or biases in the data. Conclusion There is a growing sense that AI in medicine could be helpful with specific tasks. Ongoing training, education, and study are needed to determine how AI will best integrate into clinical practice.

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Publication Details

Journal
medRxiv
Published
2026-11-02
DOI
https://doi.org/10.64898/2026.11.01.26367027
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
preprint
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preprint

Survey of Physician Attitudes on Artificial Intelligence

Tasha Glenn, John Michael Kane, Nyla Hart, Claire Muckian et al.
medRxiv
Artificial Intelligence in Healthcare and Education
preprint

Survey of Physician Attitudes on Artificial Intelligence

Tasha Glenn, John Michael Kane, Nyla Hart, Claire Muckian, Joseph F. Goldberg, John Blake Torous, Kathryn E. Redinger, David Gratzer, Scott Monteith, Charlotte Blease, Daniel Tuinstra, Eric D. Achtyes, Heather Mayle, Lisa Leininger, Patricia Marcy, Elaine Yeung, Ilang M. Guiroy, Yagna Reddy, Paul Fu
preprint en

Abstract

Objective To better understand how physicians view the potential use of artificial intelligence (AI) in their practices. Method We conducted an online cross-sectional survey of 1,258 physicians (MD, DO, MBBS or equivalent) in the United States (US) and Canada from December 2023 through February 2026. The survey contained 34 questions focused on 6 areas: (1) demographics, (2) training, (3) clinical benefits, (4) clinical concerns, (5) clinical AI prediction tools, and (6) generative AI. Results A total of 130 completed surveys were received (response rate, 10%). Top specialties included psychiatry (46.2%), internal medicine (14.6%) and pediatrics (13.8%). A total of 16.9% had training in computer science or information technology and 40.8% in statistics. Nearly half (46.9%) had no formal training in AI and were self-taught. Those with training in AI received it through vendors or at work. Sixty to seventy percent thought AI would provide diagnostic aid or treatment recommendations, but half did not feel adequately trained to safely use AI in practice. Over 70% thought it could help with administrative tasks. More than 80% were worried about errors, misinformation, or biases in the data. Conclusion There is a growing sense that AI in medicine could be helpful with specific tasks. Ongoing training, education, and study are needed to determine how AI will best integrate into clinical practice.

medRxiv
Uppsala University (SE), Northwell Health (US), Beth Israel Deaconess Medical Center (US), University Health Network (CA), Bronson Methodist Hospital (US), Western Michigan University (US), Palo Alto University (US), University of Toronto (CA), Holland Hospital (US), Scarborough Health Network (CA), Michigan State University (US), Icahn School of Medicine at Mount Sinai (US)
Artificial Intelligence in Healthcare and Education
DOIOpen Access PDFOpenAlex
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