Inspired Vet Article – AI in veterinary medicine: Giving time back to the profession

An article by Dr Adele Williams-Xavier

International Women’s Day, and the conversations it prompts about career longevity, feels particularly relevant to veterinary medicine. The work is demanding, emotionally loaded, and increasingly fragmented by administration. Clinical notes must be accurate and defensible. Referral letters need detail. Owners expect clear discharge instructions and timely follow-up. None of that is optional, but it often spills into lunch breaks and evenings, turning “finishing notes” into a routine rather than an exception.

This matters because time pressure does not land evenly across a workforce. Veterinary medicine is a female-majority profession, and women are also more likely to work part-time across many sectors, often while carrying a greater share of caring responsibilities. When unpaid after-hours admin becomes normalised, the result is not just inconvenience. It reduces recovery time, increases cognitive fatigue, and pushes talented clinicians towards roles that feel more sustainable. If the profession wants retention, wellbeing, and high-quality care, it needs to take documentation burden seriously and treat it as a systems problem, not a personal failing.

Artificial intelligence, when used well, offers a practical way to reduce some of that burden. It will not solve staffing gaps, unrealistic demand, or the emotional complexity of clinical practice. It can, however, remove avoidable friction, particularly around documentation and communication. For an International Women’s Day edition with a focus on inspiration and sustainability, that is a meaningful promise: not futuristic hype, but a realistic opportunity to protect time.

From buzzword to toolset

AI is often talked about as if it were one thing, but in practice it is a set of tools that do different jobs. Some AI is predictive, meaning it uses patterns in data to estimate likelihoods. Other AI is generative, meaning it can draft text from an input such as a conversation transcript, a clinical history, or a problem list. In day-to-day small animal practice, equine work, and referral settings, it is the generative tools that currently have the most direct impact on workload, because they target the administrative layer that expands around every patient.

Generative AI is best understood as a powerful drafting and summarising engine. It does not “think” like a clinician, and it should not be treated as an authority. Its value is that it can take information that already exists and turn it into usable documentation, quickly. That could mean a structured consult note drafted from the conversation, a referral letter drafted from the assessment and plan, or a client-friendly summary that translates clinical language into clear next steps. Used responsibly, it reduces the constant switching between listening, typing, and thinking, which is a hidden driver of fatigue in a busy clinic.

Current applications of AI in veterinary practice

The most useful way to understand AI in vet med is to follow the patient journey, from first contact to follow-up. AI is already being used, or has near-term potential to be used, across front-of-house processes, in-consult tools, clinical support, diagnostics, back-office operations, and even at-home monitoring.

Generative AI is best understood as a powerful drafting and summarising engine. It does not “think” like a clinician, and it should not be treated as an authority.

Front-of-house and client interaction

Before a patient has even arrived, practice teams are already dealing with a volume of messages that did not exist in the same way a decade ago: appointment requests across multiple channels, queries about vomiting at 2am, medication questions, insurance paperwork, and pre-op instructions. AI-enabled tools can support this front door of the practice by helping manage booking workflows, responding to routine questions, and collecting pre-visit information in a structured way. That might look like a guided history form that adapts to the owner’s answers, or a messaging assistant that helps route requests to the right team member.

Triage is a particularly tempting area, because it appears to promise efficiency, but it needs careful framing. Used appropriately, it can help owners describe symptoms clearly, highlight red flags that warrant urgent assessment, and ensure the practice has the right information before arrival. It should not replace clinical judgement, and it should not create false reassurance. When designed and governed properly, it can reduce the back-and-forth that consumes reception time and delays care.

There is another reality here that practices cannot ignore. Owners are already interacting with AI outside the practice, often by searching the internet or using general-purpose tools to ask what might be wrong. That can generate anxiety, misinformation, and unrealistic expectations. One practical response is to provide a trusted, practice-aligned pathway within the clinic’s own ecosystem: structured pre-visit information gathering, clear written guidance, and signposting to reliable resources. The aim is not to ban curiosity, but to keep clinical interpretation within a safe, accountable space.

In-consultation tools: AI scribes

If there is one category of AI that has surged in popularity in veterinary practice, it is the scribe. AI scribes such as CoVet, record the consultation conversation and produce an editable clinical note that is structured and professional. The clinician reviews and finalises it, but crucially they begin with a draft rather than a blank page. AI scribes can also generate owner-facing summaries in plain language, sometimes in multiple languages, which can improve understanding and reduce follow-up confusion. They can draft referral letters, emails, and reports, and also extract practical outputs such as to-do lists, reminders, and billing prompts based on what was discussed.

The wellbeing impact comes from reducing the “typing tax”. In many clinics, typing is not a neutral task. It competes with listening, reduces eye contact, and fragments attention. When documentation can be drafted automatically, more of the consultation can be spent on the examination, on explaining options, and on checking understanding. That supports clinical quality as well as client experience.

Interestingly, some clinicians report a secondary effect. When a scribe tool is listening, clinicians often vocalise findings more clearly, because speaking the assessment improves the draft note. That can sharpen communication with the owner in real time. It also encourages a clearer narrative of clinical reasoning, which is exactly what a good record should capture. In that sense, the tool does not only save time; it can improve clarity, consistency, and engagement.

The key is realism. The record still needs review. AI is excellent at drafting structure, but it can misunderstand context, misattribute a detail, or include irrelevant conversation. The safest and most effective use is to treat the draft as a starting point that must be checked quickly and routinely, much like reviewing a junior colleague’s first draft.

Clinical decision support aids

Another fast-growing area is decision support. AI tools can help formulate differential diagnoses, suggest diagnostic pathways, and summarise management or treatment options. At their best, they function like a searchable, summarised veterinary library that can be accessed in the flow of a consultation. That can be helpful for complex cases, uncommon presentations, and situations where a clinician wants to sanity-check a plan or ensure they have not missed a reasonable alternative.

The quality of these tools varies. Some are built on generalist language models, which are more prone to confident errors if the prompt is weak or the context is missing. Others are trained on ring-fenced veterinary sources and are designed specifically for clinical use. Regardless of the tool, the principle is the same. These systems should assist clinical decision-making, not make decisions for the vet. They can support recall, structure thinking, and provide references, but they do not hold the full context of the patient, the owner, the practice constraints, or the nuances that experienced clinicians weigh instinctively.

AI tools can help formulate differential diagnoses, suggest diagnostic pathways, and summarise management or treatment options.

This is where the profession’s relationship with AI needs to stay mature. The value is not in replacing expertise. It is in supporting it, especially on hard days, in high-volume settings, or when mental bandwidth is stretched thin.

Diagnostic imaging and computer vision

Computer vision, a branch of AI that analyses images as data, has been one of the earliest clinical applications. In human medicine it has been widely explored in radiology and pathology, and similar approaches are increasingly relevant in veterinary settings. The classic examples are radiograph interpretation support and triage, but the scope is expanding. Tools are emerging for ultrasound, CT, MRI, endoscopy, and microscopy-based work such as cytology or parasite egg identification.

The promise here is twofold. First, image analysis tools can improve consistency by flagging findings that might be missed when fatigue is high or time is short. Second, when combined with clinical context, they can support more structured reporting and help clinicians communicate findings to owners. However, imaging support is inherently higher stakes than drafting text, because it can influence diagnosis and treatment directly. That means adoption should be based on validation, careful evaluation, and a clear understanding of limitations, including the risk of bias if the training data does not reflect the population seen in practice.

Even with strong tools, responsibility remains with the clinician. AI can be a second set of eyes, but it is not a substitute for experience, correlation with the clinical picture, or the decision to pursue further diagnostics.

Practice management and back-office operations

Some of the most quietly powerful uses of AI sit outside the consult room. Veterinary practices generate large amounts of data: appointment patterns, presenting complaints, prescribing behaviours, laboratory results, outcomes, and client communication trends. AI is particularly good at spotting patterns in complex datasets, which can support practice management in understanding caseload, auditing care, and identifying trends over time.

This kind of analysis can inform practical decisions, such as refining protocols, improving preventive care reminders, or identifying bottlenecks that create stress for staff. It can also support inventory management. Predictive approaches can help practices order stock more intelligently, reduce waste, and flag items nearing expiry. In a world of tight margins and rising costs, even small improvements in efficiency can reduce the background pressure that contributes to burnout.

Generative AI also has a role here. It can help produce marketing content, client education campaigns, and internal communication drafts. That is not trivial. Many practices recognise that their website, social media, and client comms need attention, but do not have the time. Used with appropriate oversight and a clear brand voice, AI can reduce the effort required to maintain consistent communication, freeing human time for clinical and team priorities.

At-home monitoring and the connected client

Finally, AI is expanding into the home. Tools that analyse body language and facial expressions have been explored for pain recognition, particularly in species where subtle cues can be missed by owners. If owners can use this technology responsibly and share observations back to the practice, it creates opportunities for earlier intervention, better monitoring, and more meaningful follow-up between visits.

This should be framed carefully. At-home AI tools should not be positioned as a replacement for veterinary assessment, and they should not increase anxiety by producing overly certain outputs. Where they can help is in structuring observation, prompting earlier contact when a change is detected, and supporting long-term monitoring in chronic disease. For veterinary teams, that can shift some care from reactive to proactive, which is better for patients and can be less emotionally draining for staff.

The wellbeing opportunity, and why it fits International Women’s Day

The thread linking these applications is not novelty. It is time and cognitive load. Veterinary work is not only physically and emotionally demanding; it is mentally demanding. It requires sustained attention, rapid switching between tasks, and the capacity to communicate clearly under pressure. Administrative burden steals from that capacity. It also steals from life outside work, because documentation often expands into the least protected parts of the day.

AI, used responsibly, offers a way to reclaim some of that time. The most immediate gains are likely to come from documentation support, because that is where the hidden workload is concentrated. Over time, better data insights, smoother client communication, and more efficient back-office processes can reduce the background chaos that makes a day feel unmanageable.

International Women’s Day invites the profession to focus not only on celebration, but also on sustainability. Retention depends on creating working lives that can be maintained over decades, not just survived in bursts. If technology can remove some of the repetitive clerical load and allow clinicians to finish on time more often, it supports wellbeing in a practical, measurable way.

The most promising future is not one where AI replaces veterinary judgement. It is one where AI is used to protect the human parts of veterinary medicine: the attention needed to examine properly, the time to explain options, the space to think, and the energy to remain compassionate. Around International Women’s Day, that is a fitting ambition: not simply applauding the people who keep the profession running, but adopting tools that help them keep going.

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