Perceptions of AI in veterinary medicine: insights from students, faculty, and practicing veterinarians in Hong Kong

Introduction As artificial intelligence (AI) transforms veterinary medicine, understanding stakeholder perceptions is crucial for its effective and responsible integration. To support the development of targeted educational and policy initiatives, this study aimed to evaluate the knowledge, attitudes, and practices regarding AI among Bachelor of Veterinary Medicine (BVM) students, PhD students, faculty, and practicing veterinarians in Hong Kong. Methods A cross-sectional online survey was conducted between December 2023 and March 2024 among BVM students, PhD students, and faculty members at City University of Hong Kong, and practicing veterinarians in Hong Kong who are members of the Hong Kong Veterinary Association. The survey assessed participants’ familiarity with AI, prior training, perceived benefits, concerns, and willingness to adopt AI in education and clinical practice. Descriptive and comparative analyses were performed to examine differences across stakeholder groups. Results Of 79 complete responses, nearly half (46.8%) reported unfamiliarity with AI concepts. Only 17.7% had received formal AI training, although 78.5% expressed interest in future AI education. Most respondents agreed that AI could enhance veterinary teaching and practice (83.5%) and 81.0% indicated they would likely incorporate AI tools into their work. Key perceived benefits included support for case-based learning (83.5%), virtual animal models for teaching (77.2%), and improved diagnostic accuracy (74.7%). However, 41.8% felt inadequately prepared to use AI. Major concerns included veterinarian accountability for AI-related harms (79.7%), lack of system flexibility (75.9%), and potential clinical inaccuracies (70.9%). Descriptively, practicing veterinarians reported the lowest AI tool use (66.7% had never used AI tools), the lowest preparedness (66.7% felt unprepared), and lower agreement with AI’s clinical benefits, although attitude differences were not statistically significant. Conclusion These exploratory findings suggest gaps in self-reported AI knowledge and differing perceptions of AI across veterinary stakeholder groups in Hong Kong, with AI use already widespread at the time of the survey despite limited formal training. While enthusiasm for AI integration is high, concerns about preparedness, accuracy, and ethical responsibility remain. Larger, multi-institutional studies are needed to confirm these patterns and to inform targeted training programs and ethical frameworks for safe and effective AI adoption in veterinary medicine.