8 Jul 2025
Thomas Westley gives an overview of the use of artificial intelligence within the sector, including its pros and cons.
Thomas Westley
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Image: Shutter2U / Adobe Stock
The use of artificial intelligence (AI) in veterinary medicine within the past couple of years has overgrown all expectations. Initially, AI was incorporated for basic data analysis, such as managing large databases of patient records, tracking health parameters and improving administrative efficiency.
However, with continuous improvement of technology, the role of AI has expanded significantly. Today, AI tools are being used not only for diagnostic purposes but also in various other areas, changing the way veterinarians approach their work.
Vet in your phone. It is just a matter of time before people from all over the world start using their mobile devices to check their pets’ health. Many trending applications are currently being released in Asian countries. They use picture-analysis technology to detect early signs of health issues in pets.
By simply taking a photo of a pet’s skin, eyes or other affected areas, the app can provide primary analysis and suggest whether a visit to the vet is needed. This tool, which also offers online consultation with specialists, helps reduce costs for both pet owners and veterinarians by minimising unnecessary visits. On the other hand, how can we be sure that such applications won’t harm our pets by misinterpreting results or even missing something potentially serious?
AI diagnostic scans. This valuable AI tool is used in the analysis of radiographs, ultrasounds and MRIs. It enhances patient safety by enabling specialists to spot the tiniest deviations at early stages, without waiting for interpretations from highly skilled specialists. This kind of equipment can predict the onset of chronic kidney disease (CKD) in feline patients up to two years before it occurs.
It uses a database containing thousands of images, allowing it to detect problems faster, easier and cheaper than traditional methods. However, can we truly rely on AI in such complex cases? Although it sounds very optimistic and promising, the use of such software is still in its infancy and requires constant, direct human supervision. As one clinician I saw states: “There is potential in diagnostics such as radiographs, but it is by no means fully developed or flawless.”
AI-powered animal health monitors. Pet accessories such as collars and trackers use advanced AI algorithms and sensors to monitor a range of vital parameters and biometric data, including activity levels, heart rate, respiratory rate and temperature, to detect the start of possible health problems.
AI in health records management. AI can assist with data management, allowing veterinarians to spend more time with patients rather than focusing on documentation. However, can it make mistakes when taking medical histories, especially given the industry-specific abbreviations unique to each practice?
AI in oncology. “AI is pioneering in oncology”, those are the future headlines of many news articles, as it is already possible to use AI-powered software to predict cancer treatment outcomes. By analysing cancer cells and using machine learning algorithms, AI can suggest the most effective chemotherapy treatments for dogs with lymphoma. This personalised approach is helping choose the best cancer treatment, reducing the trial-and-error process, and improving success rates. But, as we discussed earlier, significant work is being done to develop this technology, and great caution is necessary before entrusting many decisions to AI or relying on it entirely.
AI in drug development and laboratory tests interpretation. The use of AI in drug discovery and development is rapidly advancing. AI algorithms can analyse vast datasets of chemical compounds, biological interactions and clinical outcomes much faster than traditional methods.
This has led to more efficient drug development processes. In veterinary medicine, and AI technology is being applied to develop new treatments for a range of conditions, from parasitic infections to chronic diseases, as well as to enhance laboratory testing.
Senior lecturer from the University of Central Lancashire, Iain Richards, said: “One important point to bear in mind is that while AI can be inherently accurate when analysing pixels in scans, biological tests – especially biochemistry – have their own sensitivity and specificity cut-offs.
“Any AI utilising these tests will carry the same risk of error. For example, many lab profiles define a “normal” range as being within one or two standard deviations from the mean, yet any result outside that range is flagged as abnormal.
“A good example is ALT (alanine aminotransferase), which typically needs to be two to three times the upper limit to be considered clinically significant.”
Improved diagnostics. AI can analyse complex datasets to identify smallest deviations and make predictions that are often beyond human capability. This can allow us to detect early symptoms of potential disease and improve diagnostic accuracy in general.
Data input efficiency. Automated systems can handle routine tasks, allowing veterinarians to focus more on patients and client communication.
Individualised medicine. AI enables more personalised treatment plans by analysing thousands of patients’ disease histories, allowing to predict the most efficient drugs set for a specific case.
Cost minimisation. Using AI as a triage tool (telemedicine) will allow provision of easier access to veterinary consultation services, reducing costs for things like transportation, sedation for highly anxious patients. AI online triaging can be beneficial for stress management for both patients, owners and consultants.
High initial cost. Implementing AI technology can be expensive, which may be a cost-related problem for small practices.
Data privacy concerns: Digitalisation of patients’ records, and confidentiality will cause concerns about data security and privacy.
Dependence on technology. Over-reliance on AI could result in a decline in hands-on diagnostic skills among new veterinarians and may even lead to the potential replacement of humans in certain workplaces.
Ethical issues. The use of AI in veterinary care raises ethical questions, such as how to handle errors made by AI systems and the implications of reduced human oversight.
Lack of regulation. There are currently few regulations governing the use of AI in veterinary medicine, raising concerns about safety standards, fair competition and the spread of misinformation.
Laura Catherine Jenkinson, veterinary coach and mentor (teaching and learning), says: “AI technology is rapidly advancing and will soon become commonly used in everyday life. AI has been around for several years in scientific technology, we are just beginning to be able to harness the abilities for everyday tasks.
“When used appropriately it will be a fantastic way to streamline research and get resources refined quickly. The key element is using it appropriately and correctly. It would be hugely beneficial to have free CPD that educates users on how to use AI technology safely sourcing accurate information.”
Adrian Nelson-Pratt, from VSGD, shared some important questions to consider before fully relying on AI technology: “Here’s what I’d add or ask to explore. What will it mean to be a veterinarian if AI becomes fully integrated into the profession? What roles will support staff play – specifically, what jobs might be eliminated, and how will we train the next generation to work alongside AI?
“What does it mean to operate a veterinary business when AI, automation, and integrations are everyday components? Where will the value proposition lie, what staff will be necessary and what will the nature of the work look like? How will this impact financial sustainability and overall viability?
“How will consumers, who inevitably adapt faster than the veterinary industry, expect us to engage with these opportunities? What new or altered expectations will arise? What will be the regulatory burden associated with AI in veterinary medicine? Drawing comparisons with human medicine may be beneficial.
“How will AI affect the health and well-being of the veterinary profession, considering changes in work patterns, stress levels and expectations?
“Lastly, what will be the evolving role of animals in society?”
As a second-year veterinary student, I’ve witnessed how AI is being integrated into my studies. My personal experience using AI has shown an increase in academic performance, allowing me to diversify my revision through the generation of useful quizzes, revision material, and infographics.
Virtual simulations powered by AI will allow students to practice surgical and diagnostic procedures in a safe environment, enhancing our skills and confidence before working with live animals. AI-based platforms are also being used to analyse student performance, offering personalised feedback and resources to improve learning outcomes. This not only prepares us better for real-world scenarios, but also nurtures a more adaptive and informed future generation of veterinarians.
The integration of AI in veterinary medicine is a game-changer, offering new possibilities in diagnostics, treatment, education and overall animal care. It is, therefore, inevitable that multiple challenges will arise; however, the benefits of using AI technology are undeniable. From predicting diseases and optimising treatment plans to enhancing veterinary education, AI is set to play an increasingly vital role in the field.
However, although AI excels in summarising information, even in those applications, human oversight is crucial. Our veterinary colleagues expose themselves to errors and potential litigation if they fail to carefully read and edit everything produced by the AI summariser.
Finally, AI still has a long path of development ahead, and hopefully, we will achieve new scientific breakthroughs by working together, combining the strengths of both human and artificial intelligence.
