Artificial Intelligence (AI) is transforming animal health and veterinary sciences by enhancing diagnostic accuracy, improving treatment strategies, and enabling proactive disease management. This study explores the current state and future potential of AI in these fields, highlighting its applications in disease diagnosis, treatment planning, continuous monitoring, and surgical procedures. AI's ability to analyze extensive datasets, identify trends, and make informed decisions has led to significant advancements in animal healthcare. For instance, machine learning algorithms are being used to detect subtle abnormalities in diagnostic imaging, improving the accuracy of disease diagnosis in companion animals and livestock. AI also accelerates drug discovery and enhances genetic research, contributing to the development of more effective treatments. In veterinary sciences, AI is reshaping surgical procedures through robotic assistance, improving precision and outcomes. However, ethical considerations such as data privacy, informed consent, and algorithmic bias must be addressed to ensure responsible AI integration. The study emphasizes the need for further research to overcome existing challenges and to develop ethical frameworks for AI applications in animal health. Overall, AI holds great promise for improving the welfare of animals and advancing veterinary care, but careful consideration of ethical and practical issues is essential for its successful implementation.Artificial Intelligence (AI) is transforming animal health and veterinary sciences by enhancing diagnostic accuracy, improving treatment strategies, and enabling proactive disease management. This study explores the current state and future potential of AI in these fields, highlighting its applications in disease diagnosis, treatment planning, continuous monitoring, and surgical procedures. AI's ability to analyze extensive datasets, identify trends, and make informed decisions has led to significant advancements in animal healthcare. For instance, machine learning algorithms are being used to detect subtle abnormalities in diagnostic imaging, improving the accuracy of disease diagnosis in companion animals and livestock. AI also accelerates drug discovery and enhances genetic research, contributing to the development of more effective treatments. In veterinary sciences, AI is reshaping surgical procedures through robotic assistance, improving precision and outcomes. However, ethical considerations such as data privacy, informed consent, and algorithmic bias must be addressed to ensure responsible AI integration. The study emphasizes the need for further research to overcome existing challenges and to develop ethical frameworks for AI applications in animal health. Overall, AI holds great promise for improving the welfare of animals and advancing veterinary care, but careful consideration of ethical and practical issues is essential for its successful implementation.