Vol. 10, Issue 1, Part E (2026)

Artificial intelligence (AI) is transforming our everyday life at an unprecedented pace. The emergence of technological advancement in AI aimed to bring together transparent solutions to tackle various global health challenges, including broad scientific space in veterinary research and canine clinical practice.AI has elicited profound impact on real world applications in animal disease detection and diagnosis with unprecedented accuracy and efficiency. The basic tenets of AI encompasses various technical understanding, including three major knowledge applications in machine learning (ML), natural language processing (NLP), and computer vision (CV) to assist disease detection, image classification, predicting outcomes, and tailor personalized treatment plans in canine practice. Critical language texts gleaned from uncategorized medical records, clinical notes, and textual data are transformed using NLP algorithm for relevant disease diagnosis and improved treatment outcomes. Moreover, image comparisons and scientific interpretation of digital images employing CV applications have potential to accurately pinpoint the binary classification task (diseasedvs.healthy tissues). Here in this review, we explore the current knowledge of algorithms and networks that can offer numerous benefits to clinical decision-making in canine patient care, including highly precise treatment options and data-driven insights for veterinarians and pet owners. However, the legal and ethical risks, unavailability of resources and technological anxiety are some of the barriers towards implementing this high throughput AI technology in canine practice need to be addressed before integration. The exponential developments in current transformative AI research corroborate its potential to enable a paradigm shift over canine clinical practice and veterinary medicine.