Exploring the potential and limitations of artificial intelligence in animal anatomy

Background: Artificial intelligence (AI) is revolutionizing veterinary medicine, particularly in the domain of veterinary anatomy. At present, there is no existing review article in the literature that examines the prospects and challenges associated with the use of AI in animal anatomy education. Study design: Narrative review. Objective: This review article explores the prospects and drawbacks of AI applications in veterinary anatomy. Anatomy and AI-powered diagnostic systems enhance clinical examination, diagnosis, and treatment by analyzing vast datasets, improving accuracy, and detecting subtle anomalies. Methods: We reviewed and analyzed recent literature on AI applications in veterinary anatomy education, emphasizing their potential, limitations, and future directions.. Conclusion: In veterinary anatomy education, AI integrates advanced tools like three-dimensional (3D) models, virtual reality (VR), and augmented reality (AR), offering dynamic and interactive learning experiences to students as well as the faculty of veterinary institutions across the globe. Despite these advantages, AI faces challenges such as the need for extensive, high-quality data, potential biases, and issues with algorithmic transparency. Additionally, virtual dissection and educational tools may impact hands-on learning and ethical and legal concerns regarding data privacy must be addressed. Balancing AI integration with traditional skills and addressing these challenges will maximize AI's benefits in veterinary anatomy and ensure comprehensive veterinary care.