4 Ways to Start Using AI in Veterinary Medicine

Unless you’ve been living under a proverbial rock, there’s no escaping artificial intelligence (AI) in our modern world. The technology has gone from mythical to ubiquitous in only a few years and has made its way into the veterinary profession.

AI’s role in transforming the veterinary field is significant, revolutionizing diagnostics, research, and practice management by enhancing efficiency, accuracy, and outcomes. AI tools promise to make clinic life easier and more efficient, but getting started can feel overwhelming.

Within the broader veterinary field, AI is being integrated to streamline workflows, improve data accuracy, and support better clinical decision-making.

The integration of AI in veterinary medicine presents exciting opportunities to improve the quality of life for animals and their caregivers. This guide will walk you through helpful applications and provide suggestions about how to dip your toe into the AI pool. (Hint: You’re probably already knee-deep!)

What is AI? 

AI is a broad category of computer systems that try to simulate the human brain, including learning and reasoning. The development of AI relies heavily on knowledge databases and accumulated knowledge, which are essential for training AI algorithms and advancing both veterinary and human healthcare.

Instead of a brain, AI systems use algorithms, which are instructions that tell the AI how to “think” about data inputs to achieve specific goals. The training process for AI systems involves not only refining algorithms but also providing veterinary teams with comprehensive education through online modules, virtual scenarios, and live simulations to ensure seamless adoption of new practice management software and integrated AI functionalities.

Natural language processing is also a key AI technique, enabling the analysis of unstructured veterinary data and enhancing clinical information extraction in veterinary medicine. It’s important to remember that humans must train AI systems and develop algorithms to ensure consistent and reliable results.

AI applications in veterinary medicine

Responsible AI use in veterinary medicine involves integrating artificial intelligence into diagnosis, treatment, and epidemiological monitoring, while recognizing its limitations and the importance of data management. That said, AI has many versatile applications in our field, including:

• Veterinary medicine applications — AI technologies are used in diagnostic tools to improve clinical workflows, data analysis, and patient outcomes in veterinary practice.
• Diagnostic imaging — Imaging algorithms can analyze radiographs and CT or MRI scans to detect abnormalities. AI-powered digital cytology platforms can rapidly analyze cytology slides, providing instant insights that clinicians can use to support more accurate diagnoses.
• Research and analytics — AI can analyze large datasets to predict health issues and enable proactive interventions. AI plays an important role in identifying and understanding complex diseases through genomic research and data analysis, uncovering subtle genetic relationships and supporting phenotype-genotype mapping.
• Administrative efficiency — AI automation simplifies appointment scheduling, inventory management, client communication, and medical records management, resulting in increased efficiency. Generative AI tools can assist in any task that requires writing or creativity, including marketing and client education.
• Telemedicine and patient monitoring — AI systems support telemedicine by enabling continuous monitoring of patients. Wearable devices, such as smart collars, monitor vitals and behavior, alerting veterinarians to potential issues and identifying health changes before symptoms appear.
• Personalized medicine and oncology — AI models analyze a pet’s genetic profile and medical history to optimize treatment recommendations, enabling personalized treatment plans and improving patient outcomes in cancer research.
• Early disease detection — AI models can identify early warning signs of chronic diseases before clinical symptoms appear, facilitating early intervention and improved therapy.
• Resource management and zoonotic disease detection — AI can be leveraged to detect pathogens, prioritize samples, and assist in the early detection of zoonotic diseases, allowing for proactive management of at-risk patients and their owners.

AI’s ability to analyze complex data is essential to its important contribution to improving veterinary science, including genomic research, vaccine development, and diagnostic technologies. This helps improve patient outcomes and supports veterinarians’ evolving needs.

Veterinary research spotlight: AI in antimicrobial resistance and cancer studies

Most day-to-day AI conversations in clinics focus on workflow (i.e., notes, reminders, diagnostics). But behind the scenes, AI is also shaping veterinary research, especially in areas like antimicrobial resistance and oncology.

This is where pattern recognition at scale becomes genuinely useful.

Artificial intelligence is ushering in a new era for veterinary medicine research, offering veterinary professionals powerful tools to tackle some of the field’s most complex challenges.

In particular, AI systems and machine learning techniques are transforming how we approach antimicrobial resistance and cancer studies, enabling more thorough analysis of large data sets and improving patient outcomes across the veterinary industry.

AI and antimicrobial resistance

Antimicrobial resistance (AMR) is a data problem as much as it is a medical one.

Researchers are using AI models to analyze:

• Large sets of clinical records
• Culture and sensitivity results
• White blood cell patterns and CBC data
• Regional prescribing trends

The goal isn’t to replace clinical judgment. It’s to identify patterns humans would struggle to see across thousands (or millions) of data points.

For example, AI systems can:

• Detect emerging resistance trends earlier
• Flag high-risk populations
• Model how prescribing changes affect resistance patterns over time

At the practice level, this kind of research supports more informed antibiotic stewardship and better long-term decision-making — especially as resistance patterns continue to evolve.

AI in veterinary oncology research

Cancer research is another area where AI is proving useful — not because it “outperforms doctors,” but because it handles scale well.

AI-powered computer vision models can:

• Analyze imaging datasets to identify subtle radiographic patterns
• Standardize image interpretation across large research groups

Machine learning models can also evaluate genomic datasets to:

• Identify mutations associated with certain tumor types
• Map phenotype-genotype relationships
• Help researchers stratify cases for clinical trials

The benefit is not instant answers.

It’s improved consistency, faster hypothesis testing, and better prioritization of what deserves closer clinical investigation.

Beyond AMR and oncology

AI is also being applied in:

• Zoonotic disease surveillance
• Vaccine modeling
• Drug discovery and candidate screening
• Epidemiologic pattern tracking

In each case, the mechanism is similar: Large, complex datasets → pattern detection → refined research questions.

The clinical impact may not be immediate in your exam room, but over time, these insights shape the tools, protocols, and standards you rely on.

Why this matters for practicing veterinarians

You may not be running AI models in your hospital. But the diagnostics, decision-support tools, and guidelines entering your workflow are increasingly informed by AI-assisted research.

The key distinction: Research-level AI analyzes at scale. Clinical AI should support your workflow without disrupting it.

And as these technologies mature, the practices that benefit most will be the ones that:

• Stay curious
• Adopt thoughtfully
• Keep clinical judgment central

AI in research isn’t about hype. It’s about better questions, clearer patterns, and more consistent analysis. And that’s something every veterinarian can get behind.

Getting started with AI

AI can assist you in almost any task, so where should you begin? Here are a few practical ideas on how to get started.

1. AI-powered scribing software — AI scribe tools record conversations during veterinary exams and consultations, then transcribe the interaction into structured medical record SOAPs and communication logs, reducing the need for manual note-taking.
   
   AI algorithms help veterinarians make faster, more accurate diagnoses and treatment decisions, sometimes within the allotted appointment time. AI can also provide instant insights during patient visits, leading to quicker treatment decisions and higher client satisfaction.
2. Practice management software — Many newer practice management systems, like Shepherd, incorporate AI features to streamline operations in the veterinary practice, transforming standard procedures and supporting a more positive workplace culture by reducing staff stress and burnout.
   
   Choosing the best technology means selecting a single platform that integrates various tools and workflows, enhancing client engagement and streamlining operations. Once you’re comfortable with built-in AI, you can compare AI-powered veterinary practice management software platforms. Comprehensive training is essential for veterinary teams to ensure a smooth transition and effective use of new AI-powered systems.
3. Administrative efficiency and client engagement — AI tools can automate appointment scheduling, reminders, and follow-ups, improving communication between veterinary teams and clients. This leads to better client engagement and experience, as well as improved compliance and satisfaction.
4. Diagnostic support — Diagnostic platforms with AI analysis provide rapid radiograph interpretation and support in minutes instead of hours or days, significantly improving time management. If you’re looking for new in-house lab equipment, consider analyzers with AI image analysis for quick and accurate results that bypass manual microscopy.
5. AI chatbots and telemedicine — AI chatbots can perform 24/7 symptom triage for pet owners, assisting in determining the necessity of clinic visits and supporting telemedicine by enabling continuous monitoring of patients.
6. Large language models — ChatGPT, Google Gemini, and Microsoft Co-Pilot are publicly available large language models (LLMs) that users can “play” with to their hearts’ content. Visit them, ask questions, and chat with the AI to learn its capabilities and limitations. For example, you can use LLMs to draft emails, summarize long documents, or brainstorm ideas.

Before you start: Ethical and legal considerations

AI can’t replace the logic and reasoning possible in a human brain, so take their outputs with a grain of salt. Responsible AI use and careful data management are essential in veterinary medicine for ethical and secure implementation.

Most AI-enhanced clinical tools have a narrow operational scope, are trained by experts in their respective fields, and can be tested for accuracy and reliability before they hit the market. However, generative AI like ChatGPT isn’t so heavily policed and often makes mistakes.

Always double-check an AI tool’s work, as it could contain fabricated facts, sources, and quotes presented as truths. Never use a client or patient’s protected health information when chatting with an AI tool, as the platforms may use or store the data in ways that compromise security.

Similar ethical and legal challenges regarding artificial intelligence are also seen in human healthcare, highlighting the need for careful oversight in both fields.

Informed consent matters

If you’re using AI-assisted diagnostics or decision-support tools as part of your clinical workflow, consider how that fits into informed consent.

Clients generally expect transparency around how medical decisions are made. While AI decision-support tools will never replace your judgment, they may influence recommendations. Practices should:

• Be clear that AI tools are used as support, not autonomous decision-makers.
• Ensure the attending veterinarian reviews and validates all AI-generated suggestions.
• Document clinical reasoning independently of the AI output.
• Align policies with state board guidance and malpractice carrier recommendations.

In human healthcare, the standard of care increasingly includes disclosure when algorithmic tools meaningfully influence decision-making. Veterinary medicine is likely to face similar expectations as adoption grows.

Triage chatbots and liability risk

AI chatbots used for client-facing triage deserve particular caution.

If a chatbot provides symptom guidance, urgency recommendations, or next-step instructions, misuse or overreliance could create liability exposure, especially if:

• Clients delay care based on automated reassurance.
• The system fails to recognize red-flag symptoms.
• Staff assume the chatbot “handled it” without review.

Best practices include:

• Clear disclaimers that the tool does not provide a medical diagnosis.
• Explicit instructions directing clients to call or seek emergency care when appropriate.
• Internal protocols for staff review and follow-up of triage interactions.
• Avoiding chatbot systems that operate without clinician oversight.

Remember: If a client reasonably believes they received medical guidance from your practice, whether through a person or an automated system, the standard of care may still apply.

Harness the power of AI with Shepherd

You don’t have to be a tech genius to incorporate artificial intelligence in veterinary medicine into your daily workflow.

Shepherd is a single platform for veterinary practice management, designed to bring the best technology to modern veterinary practices and their clients. Built-in client communication and automation tools, integrated solutions, and workflow-first design enhance client engagement and streamline communication, improving the overall experience for both your team and patients.

Our unified approach supports the veterinary field by advancing operational efficiency and elevating standards of care across veterinary practices. Explore Shepherd’s automation features or contact our team to learn more about our cloud-based practice management software.