Global physician perspectives on artificial intelligence in healthcare across 50 countries and territories

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Authors: Bayarbaatar Bold, Oguzhan Serin, Lukitaningrum Tantri Adhiatma, Suvd-Erdene Demberel, Choni Wangmo, Ristania Ellya John, Luis Daniel Gatti Pineda, Chitsanupong Ratarat, Nisachon Tongtip, Mohammed Shakeebuddin Kashif, Nicole Kessa Wee, Farhana Fadzli
+8 more Urooj Kanwal, Trang Ngoc Nguyen, Bunta Tokuda, Weiyi Li, Phathayphout Phetvilay, Naw Paw Say Wah, Ravinath Kannangara, Priscilla Akyaa Kyei-Baffour
Cited by: 1
References: 26

Abstract

Despite rapid advances in artificial intelligence (AI) capabilities, clinical integration remains limited, partly due to an incomplete understanding of physicians' real-world engagement and determinants of adoption. We conducted an international cross-sectional survey between June and September 2024 using a 30-item questionnaire translated into 13 languages, analysing 1049 complete responses from 50 countries and territories. Most respondents reported fundamental to advanced understanding of AI (86.5%) and believed it would improve clinical practice (80.2%), particularly in efficiency (53.5%), timeliness (52.0%), and effectiveness (44.0%). However, only 27.8% had used AI in practice, and 17.7% had received formal training. Mann-Whitney analyses showed that positive attitudes and formal training were associated with greater AI understanding, familiarity and usage (all p ≤ 0.008). In multivariable regression, physicians with formal training were more than three times as likely to use AI (adjusted OR 3.40; 95% CI 2.31-5.01; p < 0.001), and those working in institutions with AI technologies were more than eight times as likely (adjusted OR 8.43; 95% CI 5.74-12.34; p < 0.001). These findings indicate a persistent gap between awareness and adoption driven primarily by structural factors, particularly the absence of formal AI training and limited institutional investment in AI technologies.

Fields of Study & Subjects

Artificial Intelligence in Healthcare and Education Global Health and Surgery Machine Learning in Healthcare

Publication details

Journal / source
npj Digital Medicine
Publisher
Springer Science and Business Media LLC
Volume
9
Issue
1
Publication date
13 May 2026
Language
EN