(Editor’s note: This is the second part of a two-part series. Click HERE to read the first part of the series.)
The work goes on. Explorations into AI are abundant to ensure evidence-based approaches and optimal results. There has been continued discussion about AI at the World Medical Innovation Forum (WMIF), a premier three-day global event, hosted by Mass General Brigham in Boston, that brings together global leaders to address the latest opportunities and challenges. Each year they create the Disruptive Dozen, a curated list of the 12 most transformative emerging healthcare technologies to highlight innovations that will have the highest potential impact within the next 18 months. And almost all of them apply to Veterinary healthcare.
The 2018 AI Disruptive Dozen were:
- Developing the next generation of radiology tools
- Creating more precise analytics for pathology images
- Bringing intelligence to medical devices and machines
- Monitoring health with wearables and personal devices
- Making smartphone selfies powerful diagnostic tools
- Revolutionizing bedside decision making with AI
- Unifying mind & machine-brain-computer interfaces
- Expanding access to care
- Reducing burdens of electronic health record use
- Turning the electronic health record into a reliable risk predictor
- Containing risks of antibiotic resistance
- Advancing the use of immunotherapy for cancer treatment
AI continues to appear in the WMIF Disruptive Dozen each year:
- 2019, AI focus with impacts on clinical care, patient interactions, and systems
- 2020, AI and Machine Learning driving advancements in diagnostic speed and accuracy
- 2023, harnessing the power of Large Language Models (LLMS) to improve healthcare
- 2024, leveraging generative AI in healthcare
As veterinarians, we have the ability to watch human healthcare and adopt what works for us. As a fun exercise, I asked ChatGPT 5 what veterinarians should know about AI in Veterinary healthcare. The response was that “Veterinarians should understand that AI is rapidly transforming Veterinary healthcare – not to replace them, but to augment clinical judgement, improve workflows, and enhance animal care.”
The ”low-hanging fruit” of AI in Veterinary medicine relates to the tools to boost operational efficiency by streamlining workflow and communications. AI automation can facilitate appointment scheduling, transcribe medical records, integrate with electronic medical records, assist with billing, and more, all with human oversight.
A word of caution is to ensure that clients are informed and provide consent when they are being recorded. I know of one lawsuit with the patient as the plaintiff and the physician and clinic as the defendants based upon lack of consent. A 2025 study by Austin Littrell showed that 57% of patients say yes to AI in the exam room if it means more time with their doctor, 83% of patients expect high standards for AI used for clinical care, and 72% want to know data sources. These human data provide excellent guidance for veterinarians as they incorporate more AI into their practices.
Regarding clinical care, AI tools can be used today to analyze images, interpret laboratory data, and monitor patient health. Its predictive analytics allow forecasting disease outbreaks, detecting patient deterioration or improvement, and monitoring treatment responses. Some key applications in Veterinary medicine include diagnostic imaging, pathology, cytology, predictive analysis, cancer diagnosis, and selection of optimal treatment for cancer. AI underpins digital health, wearables, and remote monitoring. The AI driven sensors track vitals, such as heart rate, temperature, activity, behavior, and even blood pressure, atrial fibrillation, and continuous glucose monitoring. AI allows veterinarians to follow vital signs in real time and offers insights and recommendations. Digital health also connects clients and veterinarians on a continual basis with enhanced ability to engage clients more in the healthcare of their animals.
Regulatory oversight for AI differs somewhat between human and Veterinary healthcare. Basically, the FDA oversees AI used for diagnosis and treatment in human healthcare. The FDA approves medical devices using AI and these devices are rapidly growing in number, now approaching 1,500. AI laws require that patients be informed when AI is being used, as stated above. There are also more detailed regulatory requirements that can be explored. In Veterinary medicine, primary oversight resides with the Veterinary state boards and veterinarians must comply with their respective jurisdictional Veterinary Practice Act.
What innovations are coming to further improve AI in healthcare? We know that AI uses algorithms trained by datasets to recognize patterns, make predictions, or support decisions and that these capabilities are evolving rapidly. A glimpse into what is coming shows just how rapidly AI is evolving.
Singularity University shares, “Far fewer are preparing for what happens when AI converges with quantum computing, biotechnology, spatial computing, and robotics–all at once. That convergence is already happening. And the window to get ahead of it is closing.”
AI-based tools to answer questions and support healthcare are already here and there are more to come. OpenAI launched ChatGPT Health to allow patients to connect their medical records and wellness apps to the chatbot. Google Health and Microsoft for Healthcare offer AI-powered solutions for healthcare. Anthropic joined the AI race by launching Claude for Healthcare. Amazon has just rolled out Health AI, an AI healthcare assistant for its One Medical members. Health AI uses large language models to answer questions and give advice based upon their medical records, laboratory results, and current medications, in addition to providing help booking appointments and managing medications.
Today quantum computing and AI are merging to create Quantum AI, a convergence that promises massive gains in efficiency, accuracy, and new AI capabilities. A supercomputer has already been designed to simulate the human brain’s neural networks at scale (International Centre for Neuromorphic Systems, Westen Sydney University, 2024). Additionally, an AI system, called Brainoware computers, has been built with living brain cells. It is a hybrid biocomputer that uses human neurons and technology hardware. These biocomputers are capable of recognizing different people’s voices, bringing us one step closer to merging man and machine.
While some of us are fully adopting AI, some are just getting started, and others are resisting, it is important to consider the words of Andrea Koncz, who in 2023 said, “There is no future of healthcare without AI.” I would follow that quote to say, “There is no future of Veterinary healthcare without AI.”
AI will not replace veterinarians but certainly will augment them. Is a time near when clients and veterinarians alike will trust veterinarians using AI appropriately more than veterinarians who don’t use AI? In the end, the focus of AI in Veterinary healthcare should not be the novelty of technology; rather, AI should be used to: (1) enhance the quality of patient care; (2) engage clients in the care of their animals; (3) make the lives of Veterinary healthcare team members and clients better: and (4) enhance business success.