Abstract

Artificial Intelligence (AI) quickly evolves veterinary practice by enhancing diagnostic accuracy, treatment outcomes, workflow, and operational efficiency. Even though the benefits of AI integration in veterinary practice are well appreciated worldwide, the lack of awareness of the available AI applications in major domains of veterinary care is identified as a primary gap in the acceptance of these technologies by many veterinary practitioners. There are many available machine learning (ML) applications across various fields of veterinary care. These include applications that improve the accuracy of diagnostics, optimize operational efficiency, enhance workflow in practice settings, improve production animal health, sports medicine, wildlife and exotic animal health, and AI applications to augment one health implementation. Despite the advantages, these applications pose major limitations, including available data quality, ethical concerns, and challenges in accepting and integrating available AI tools in regular veterinary practice. This review article is intended to provide a snapshot of available applications for AI integration in veterinary practice with insights into the challenges and limitations. By exploring the available literature on the subject, the article seeks to augment the knowledge of the veterinary practitioner of how AI can be harnessed to their daily needs and ultimately enhance the productivity, improved animal health, and quality of life (QOL) of animals with due consideration to the challenges and limitations.

Keywords : Artificial Intelligence, Machine Learning, Veterinary Diagnostics, Treatment Optimization, One Health, Wildlife Health, Sports Medicine, Operational Efficiency