Does AI give veterinarians new superpowers?

Introduction

Who today can claim not to be directly or indirectly affected by the rise of artificial intelligence? Whether you are browsing the internet, watching television, or simply checking messages on your smartphone, AI is present everywhere. Technology giants tout remarkable benefits, assuring us that our professional lives will become simpler and more efficient thanks to AI. The reality is that we now have access – often for free – to an extraordinary tool that delivers impressive results in specialized fields, including veterinary medicine. AI stands as the fastest-ever adopted innovation: no other technology has generated such widespread and rapid enthusiasm in human history.

Naturally, some professionals perceive AI as a threat to their job; however, the real risk lies in resisting change at all costs. A wiser approach is to anticipate and embrace AI, viewing it as an additional resource for practitioners – much like the arrival of search engines such as Google was in its time. According to a 2023 survey conducted by the American Animal Hospital Association (AAHA), 84% of veterinary professionals reported familiarity with AI applications, and 70% indicated they use AI tools regularly in their daily work (1). The survey also revealed key concerns: 70% of respondents expressed questions about the reliability of AI tools, 54% were concerned about data privacy and security, and 43% cited a lack of knowledge in the field. Despite these apprehensions, many in the field are finding ways to integrate AI into their practices.

Respondents to this survey were clear that leveraging AI aims to boost confidence in decision-making and provide a valuable second opinion. It is also seen as a helpful assistant at the frontline with pet owners, providing early diagnostic insights and advice. Finally, AI also brings financial benefits, by saving time and costs or by increasing profit margins. So, in a sense, we all now have access to “superpowers” – and it would be unwise not to use them to their fullest potential.

The power of data in veterinary AI

Data is powering ChatGPT and indeed all AI models worldwide. No matter how advanced the architecture or how brilliant the engineers behind them, AI models cannot deliver meaningful support – such as assisting veterinarians – without access to large, diverse datasets. Data serves as the critical engine that enables sophisticated algorithms to become practical and impactful tools. Professionals in the veterinary field can take great pride in the wealth of valuable data the petcare industry owns, and this can be leveraged to develop state-of-the-art AI models for veterinarians and their patients. The difference in available data between human and veterinary medicine is substantial, with veterinary datasets often being ten times larger than those in human medicine (as discussed below). This significant data advantage means that AI models trained for veterinary use are exposed to a much broader and richer pool of medical content compared to their human medicine counterparts, thereby enhancing their diagnostic accuracy and reliability.

How might AI save pets’ lives?

In specialties such as radiology, the challenges are significant. General practitioners can face lengthy delays before a specialist is available to review radiographs, which may put a patient’s life at risk – especially if the practitioner is not fully confident in interpreting the images. Often the patient will need to be under anesthesia for imaging to be performed – but if a diagnosis or action plan is not immediately forthcoming from the radiographs, this can lead to situations where a second in-patient visit is required once the results are known, whereas all treatments could have been completed during the first visit if rapid results were available. Given these challenges, it is essential to have tools that provide fast and accurate results.

To provide broad coverage for different radiology needs, we have recently developed and released two highly effective and reliable AI tools that are uniquely positioned to advance veterinary care, namely Antech RapidRead ^TM Radiology and Antech RapidRead ^TM Dental. These two systems share the objective of delivering top-quality findings for the general practitioner within minutes of analyzing a set of radiographs.

Antech RapidRead ^TM Radiology 

This AI platform enables veterinarians to receive evaluations of radiographs in less than ten minutes, and covers more than 50 distinct diagnostic findings (2-4). As noted above, it is important to emphasize that the accuracy of AI predictions depends heavily on the amount and quality of data used for training; models that have seen many examples of a condition are more reliable at recognizing it in new cases. Therefore to ensure the quality and reliability of this model, we worked closely with a team of twenty board-certified veterinary radiologists and employed 16 million animal images, resulting in what is, to our knowledge, the world’s largest veterinary image library (Figure 1). This figure compares favorably to approximately 1.3 million images typically used for equivalent human radiology models, as reported in published medical imaging studies (5). To ensure that RapidRead ^TM meets the highest standards of accuracy and trustworthiness, each expert carefully reviewed and validated every diagnostic finding before it was made available to practitioners. The model is still evolving; our current focus is on cats and dogs with radiographs of the thorax, abdomen and limbs, and we only release further diagnostic findings once the model achieves expert consensus. Ongoing collaboration with specialists and rigorous validation is key, and helps ensure that such AI tools remain trustworthy, clinically relevant and aligned with expert standards.

Figure 1. The Antech RapidRead ^TM Radiology system – developed using millions of radiographic images meticulously annotated by a team of over 20 board-certified radiologists – enables the general practitioner to interpret radiographs within minutes; the original image is shown on the left, and the RapidRead ^TM detection of a mid-abdominal mass, is on the right.

 

Antech RapidRead ^TM dental

The power of data in veterinary AI is equally evident in dental radiology, with Antech RapidRead ^TM Dental employing one of the largest real‑world intraoral radiograph datasets in veterinary medicine. Using thousands of studies collected from in excess of 300 animal hospitals, and paired with expert reports from more than 50 board-certified veterinary dental radiologists, we developed a multi-stage deep learning system that can localize, identify, and assess each individual tooth. This rich, highly curated dataset enables the model to detect key pathologies such as bone loss and endodontic disease with high reliability, across a wide variety of views, positions, and patient anatomies (Figure 2), and returns a structured report in minutes. The platform transforms complex intraoral X-rays into clear, tooth-by-tooth insights while the patient remains under a single anesthetic event, enabling veterinarians to identify hidden lesions earlier (Table 1) and complete more necessary treatments during one shorter procedure. These insights support earlier diagnosis and intervention, faster pain relief, and improved long-term oral and systemic health outcomes for dogs and cats.

(Reasoning: The value of RapidRead Dental lies in helping avoid a second anesthesia event. Because completing treatment under a single anesthetic procedure is so important, veterinarians are unlikely to delay decision-making. Instead, they would make a clinical judgment and proceed with treatment rather than waking the pet without providing definitive therapy and then re-anesthetizing the patient later.)

 

Table 1. Examples of the pathologies the system can identify.

Identify teeth using the triadan tooth numbering system Non-diagnostic images (e.g., due to foreshortening, elongation or cone-cut) Pathologies for an individual tooth, e.g.: Non-vital tooth (incisors and canine teeth) Missing tooth Retained root Tooth resorption Periodontitis staging: No bone loss (stage 0 or stage 1 periodontitis) < 25% horizontal bone loss (stage 2 periodontitis) 25-50% horizontal bone loss (stage 3 periodontitis) > 50% horizontal bone loss (stage 4 periodontitis) Periapical lucency (apical periodontitis)

Figure 2. The Antech RapidRead ^TM Dental platform employed thousands of radiographs and more than 50 board-certified veterinary dental radiologists to develop a system that can localize, identify, and assess each individual tooth and reliably detect key pathologies, such as bone loss and endodontic disease. A color protocol is designed to indicate the degree of abnormality detected; red is for severe pathology, yellow is for moderate changes, and white indicates that no pathology is detected.

 

AI for pet owners

AI can be used directly by general practitioners in their daily routines, but it can also help owners monitor their pet’s wellbeing. There are many ways advanced AI can now help address common pet health concerns, and these solutions are easily accessible through simple smartphone apps. These mean that owners can detect health issues early, potentially preventing costly treatments and ensuring their pets stay healthy. For example, 80% of dogs suffer from gum disease (6); to help address this, we have released an AI tool focused on canine dental health, which was developed using 53,000 images of canine mouths (7). With just a picture taken on a smartphone (Figure 3), the model analyzes gums and teeth, detecting signs of tartar buildup and gum irritation within seconds. After analysis, pet owners receive an easy-to-understand report with recommendations for next steps – and if further guidance on the report is needed, users can consult a licensed veterinary technician. Known as the GREENIES™ Canine Dental Check (8), the tool is completely free to use, and available either via the website or by downloading the mobile application to get started.

In the same spirit, we have launched IAMS^® Poopscan (9), an AI-powered tool designed to analyze a dog’s feces and monitor stool consistency. This can provide insights into a pet’s digestion and overall health. As with the Canine Dental Check, this project involved models which were trained on a large dataset of 12,000 human-labeled images, and is also available for free.

Our collaboration with leading petcare institutes ensures that these AI models are both accurate and reliable, giving pet owners confidence in the results. Both tools were built in partnership with Waltham Petcare Science Institute and Royal Canin.

Figure 3. The Canine Dental Check app. allows an owner to assess their pet’s dental health quickly and easily; by uploading a picture taken on a smartphone, the model can analyze gums and teeth, with the owner receiving an easy-to-understand report that includes recommendations for the next steps.

 

Ethical and practical considerations

While AI offers significant benefits, responsible use is essential. Systems must comply with data protection laws, and client and patient information should be anonymized, securely stored, and accessed only when necessary. Training data should be as diverse and representative as possible to limit bias and avoid systematic underperformance in specific breeds, species or disease presentations. AI should always support, not replace, clinical judgment, with final decisions remaining the responsibility of a qualified veterinarian. Employed as a second reader and “second set of eyes” within clear workflows, AI can also enhance client communication by providing annotated images and structured summaries that make complex findings and treatment recommendations easier for owners to understand.

Future opportunities

The integration of AI into veterinary practice is still in its early stages, and much more can be done to support a better world for pets and the professionals who care for them. As tools evolve to include additional imaging modalities, predictive analytics and multimodal data, they will increasingly support earlier detection, more personalized care, and stronger preventive medicine. The most successful applications, however, will be those that deliberately combine AI’s analytical power with the empathy, experience and contextual understanding of veterinary professionals, ensuring that technology amplifies the veterinarian’s central role in patient care.

Conclusion

AI does give veterinarians new “superpowers”, but not by turning machines into clinicians. Its real strength lies in amplifying what veterinarians already do best: integrating medical knowledge, pattern recognition, and compassion to make good decisions for individual patients. When AI is used as a second set of eyes, grounded in high‑quality veterinary data and interpreted within the clinical context, it can increase confidence, reduce uncertainty, and help clinicians act earlier and more decisively. These tools shift the focus of veterinary work away from repetitive, time‑consuming tasks and towards higher‑value activities such as case prioritization, personalized treatment planning, and clearer communication with pet owners.

 

Conflict of interest statement: The authors declare that they have no conflict of interest in writing this article.

 

References

1. American Animal Hospital Association 2023. AI in Veterinary Medicine Survey. Available at: https://www.avma.org/news/artificial-intelligence-poised-transform-veterinary-care Accessed 23^rd Feb 2026.

1. Fitzke M, Stack C, Dourson A, et al. RapidRead: Global deployment of state-of-the-art radiology AI for a large veterinary teleradiology practice. https://arxiv.org/abs/2111.08165 Accessed 23^rd Feb 2026

3. Antech RapidRead; https://www.antechdiagnostics.com/imaging-services/rapidread/ Accessed 23^rd Feb 2026
4. https://www.forbes.com/sites/randybean/2025/12/16/how-mars-is-embracing-ai-across-a-portfolio-of-legendary-brands/  Accessed 23^rd Feb 2026
5. Wang X, Peng Y, Lu L, et al. ChestX-ray8: Hospital-scale chest X-ray database and benchmarks on weakly-supervised classification and localization of common thorax diseases. IEEE CVPR. 2017;3462-3471.
6. Barnes C, Hiscox L, Bellows J. https://vcahospitals.com/know-your-pet/dental-disease-in-dogs  Accessed 23^rd Feb 2026
7. Toothscan; https://www.mars.com/toothscan  Accessed 23^rd Feb 2026
8. Greenies Canine Dental Check; https://www.greenies.com/pages/canine-dental-check Accessed 23^rd Feb 2026
9. Poopscan; https://www.iams.com/poopscan Accessed 23^rd Feb 2026