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Patterns and Predictors of Artificial Intelligence Use Among Healthcare Professionals in the United States and United Kingdom: A Cross-National Survey

Sezgin, E.; Lee, J. A.; Jadczyk, T.; Taxter, A. J.

2026-05-06 health informatics
10.64898/2026.05.01.26352171 medRxiv
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ObjectiveWe surveyed 524 healthcare professionals (HCPs) in the United States and United Kingdom to examine workplace generative AI use, access, and barriers in two high-maturity health settings. MethodsThis cross-sectional survey compared AI usage breadth, access modes, and barriers among HCPs, stratified by country and professional role. ResultsOverall, 75.8% of HCPs reported recent AI use, mainly for documentation, literature search, and clinical decision support. Usage breadth was similar by country, but role differences were pronounced. Physicians reported broader use and were significantly more likely to access AI via personal, non-employer-provided tools (60.4% vs. 31.0% for nurses; P<.01). Personal tools were the most common access mode overall (40.1%). ConclusionAI use is common, but institutional access lags adoption. Shifting use from personal accounts toward governed, approved systems is a key priority.

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