Abstract
Artificial intelligence (AI) is reshaping veterinary medicine, offering unprecedented opportunities to enhance diagnostics, treatment precision, and overall animal care, yet the field still faces unresolved challenges. Current research highlights major gains in telemedicine, imaging, robotic surgery, disease prediction, and rehabilitation, with comparative studies showing that AI tools often match or exceed veterinarians’ accuracy in specific tasks, while sometimes underperforming in academic or contextual settings. These contradictions underscore a key gap: AI excels in targeted applications but struggles with adaptability, ethical transparency, and integration into complex clinical decision-making. This review aims to map the evolving landscape of AI in veterinary sciences, drawing on both quantitative outcomes, such as improved diagnostic speed and reduced imaging errors, and qualitative insights from veterinarians, students, and ethicists regarding usability and trust. By synthesizing findings across imaging, cardiology, ophthalmology, and rehabilitation, the study identifies not only practical benefits but also persistent concerns about cost, training, data quality, and the risk of over-reliance on algorithms. Novel contributions include a comparative analysis of emerging trends across subfields, the human dimensions of adoption, and the ethical imperatives shaping responsible implementation. While the review affirms AI’s potential to elevate veterinary care, it emphasizes the need for longitudinal validation, cross-species adaptability, and frameworks that balance innovation with professional oversight. Future research should explore interdisciplinary integration, equitable access, and scalable models to ensure that the AI revolution in veterinary medicine genuinely enhances animal welfare worldwide.

Key words: Veterinary telemedicine; animal welfare; telehealth in veterinary care; AI in animal health; veterinary technology