Towards AI-Enhanced Day One Competencies: Development and Validation of an International Veterinary Human–AI Collaboration Framework

Artificial intelligence (AI) is rapidly transforming veterinary medicine through applications in clinical decision support, diagnostics, communication, information management, and knowledge synthesis. Despite these developments, current veterinary accreditation frameworks, including the Royal College of Veterinary Surgeons (RCVS) Day One Competences, the Australasian Veterinary Boards Council (AVBC) Day One Competencies, the American Association of Veterinary Medical Colleges (AAVMC) Competency-Based Veterinary Education (CBVE) framework, and the European Association of Establishments for Veterinary Education (EAEVE) Day One Competences, were largely developed before widespread adoption of AI technologies and do not explicitly define the competencies required for effective human-AI collaboration.This project aims to develop and validate the first International Veterinary Human-AI Collaboration Framework (VHAC). Through a systematic review of existing competency frameworks, competency gap analysis, and international Delphi consensus methodology, the project will identify the competencies, professional behaviours, and performance indicators required for future veterinary graduates to work safely, ethically, and effectively in AI-enhanced environments.The framework will provide a foundation for future curriculum development, outcomes-based education, accreditation review, and competency assessment within veterinary education internationally. The project will position City University of Hong Kong as a global leader in AI-enhanced veterinary education and generate high-impact scholarly outputs with direct implications for teaching and learning.