Artificial intelligence (AI) is rapidly transforming veterinary pathology by enhancing the accuracy, speed, and efficiency of disease diagnosis in animals. By applying advanced computational algorithms to histopathological images, laboratory data, and molecular information, AI supports pathologists in identifying subtle disease patterns and making more reliable diagnostic decisions. The integration of AI with digital pathology has improved standardization, reduced inter-observer variability, and enabled large-scale data analysis for disease surveillance and research. Additionally, AI contributes to personalized veterinary medicine by combining multiple data sources to guide targeted treatment strategies. Despite its promising potential, challenges such as high implementation costs, limited availability of quality datasets, the need for validation, and integration into routine workflows must be addressed. Importantly, AI serves as a supportive tool that complements human expertise rather than replacing it. Overall, the responsible adoption of AI in veterinary pathology holds significant promise for improving animal health, welfare, and disease management.