Global perspectives of ophthalmologists on artificial intelligence adoption in clinical practice
Artificial intelligence (AI) is rapidly expanding in ophthalmology, yet its adoption in daily practice remains limited. Understanding clinicians’ perspectives is essential to address barriers and guide targeted education. We conducted a cross-sectional international survey of licensed ophthalmologists from 45 countries across all continents between October 2024 and February 2025. The questionnaire evaluated AI familiarity and use as primary outcomes, as well as perceived clinical impact, ethical concerns, and training preferences of participants. Descriptive and comparative analyses were conducted across world region, practice type, and professional seniority. A total of 622 ophthalmologists completed the survey. While 69.5% anticipated a moderate-to-very potential for AI to improve clinical outcomes, only 7.2% reported regular use. Familiarity with AI was significantly higher among academic clinicians (p = 0.0011), whereas 49.6% reported no knowledge of specific AI tools. Key barriers included lack of training (20.5%), implementation costs (16.5%), and reliability concerns (12.9%). Ethical issues most frequently cited were algorithmic bias (44.2%), liability (36.7%), and reduced physician–patient interaction (19.9%). Ophthalmologists with > 20 years of experience were more likely to support AI adoption (OR 1.5). Interest in AI education was high (75.1%), with a preference for online and structured formats and calls for earlier integration into medical curricula. Despite broad recognition of AI’s potential in ophthalmology, adoption remains low and familiarity limited. Lack of training, cost, and ethical concerns represent key barriers. Tailored, accessible education and institutional support are urgently needed to facilitate safe and effective AI integration into clinical practice.
Authors
- Jose Carlo M. Artiaga (ORCID: https://orcid.org/0000-0003-4632-7968)
- Rodrigo Anguita (ORCID: https://orcid.org/0000-0003-2382-1111)
- Edmund Yik Kong Tsui (ORCID: https://orcid.org/0000-0001-7532-9191)
- Enrico Bernardi (ORCID: https://orcid.org/0000-0002-8082-4813)
- Gustavo Barreto Melo (ORCID: https://orcid.org/0000-0001-5765-2008)
- Ogugua Ndubuisi Okonkwo (ORCID: https://orcid.org/0000-0002-6805-2427)
- Martin Sebastian Zinkernagel (ORCID: https://orcid.org/0000-0003-3447-2359)
- Yousif Subhi (ORCID: https://orcid.org/0000-0001-6620-5365)
- Charles C. Wykoff (ORCID: https://orcid.org/0000-0001-7756-5091)
- Lorenzo Ferro Desideri (ORCID: https://orcid.org/0000-0003-0715-6369)
- Pierre‐Henry Gabrielle (ORCID: https://orcid.org/0000-0002-9688-4845)
- Adrian T. Fung (ORCID: https://orcid.org/0000-0002-1117-3893)
- Hasenin Al-khersan (ORCID: https://orcid.org/0000-0001-6114-0996)
- Hung‐Da Chou (ORCID: https://orcid.org/0000-0002-1561-3059)
- Janice Roth
- Nicola Sagurski (ORCID: https://orcid.org/0000-0001-8892-2218)
Institutions
- University of Bern (CH)
- University of Copenhagen (DK)
- The University of Sydney (AU)
- Bern University of Applied Sciences (CH)
- Moorfields Eye Hospital NHS Foundation Trust (GB)
- Sun Yat-sen University (CN)
- University of Pittsburgh (US)
- University of Southern Denmark (DK)
- Universidade Federal de Sergipe (BR)
- University Hospital of Bern (CH)
- Rigshospitalet (DK)
- Westmead Hospital (AU)
- ACT Foundation (US)
- Retina Consultants of Texas (US)
- Doheny Eye Institute (US)
- Linkou Chang Gung Memorial Hospital (TW)
- Maison des Sciences sociales et des Humanités de Dijon (FR)
- Moorfields Eye Hospital (GB)
- University College London (GB)
- University of the Philippines Manila (PH)
- Universidade Federal de São Paulo (BR)
- Macquarie University (AU)
Publication Details
- Journal
- International Journal of Retina and Vitreous
- Published
- 2025-11-25
- DOI
- https://doi.org/10.1186/s40942-025-00764-4
- Citations
- 1
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.65