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A 2024 survey cited by Veterinary Practice News found that 39.2% of 3,968 veterinary professionals were already using AI tools, but adoption alone does not show whether practices are earning a return. The report identifies documentation and client communication as practical areas to measure, while stressing that practices need pre-adoption data and staff buy-in to judge results.
AI use is spreading in veterinary practices, but a Veterinary Practice News report says that does not establish whether clinics are getting a return on their investment. Citing a 2024 survey of 3,968 veterinary professionals, the report says 39.2% were already using AI tools or software; it argues that practices need baseline measurements and consistent staff use to assess whether those tools save time or improve workflows.
The survey was conducted by Digitail in collaboration with the American Animal Hospital Association. Among respondents who had tried AI, nearly 70% said they used it daily or weekly, while 38.7% of all respondents said they were interested in adopting it soon. Those figures describe reported use and interest, not the amount of money or time practices gained from the technology.
The report identifies clinical documentation as one area where practices can track results. Ambient documentation tools listen during appointments and draft records for veterinarians to review. Suggested measures include average time to complete a chart, the share of records completed the same day and after-hours charting time per doctor. The report says completed records may also support handoffs among veterinarians, technicians and front-desk staff, but does not quantify that benefit.
Client communication is another potential source of operational savings. Tools that help with reminders, appointment confirmations, follow-ups or discharge summaries may reduce manual work, the report says. Practices can monitor no-show rates, reminder responses and staff time spent on outbound calls. Diagnostic decision-support tools are discussed as a way to surface relevant considerations for clinicians, not replace their judgment; the article says that value can be harder to express in dollars.
How Clinics Can Test AI’s Return
The distinction between adoption and return matters for clinics deciding whether to keep, expand or cancel an AI subscription. A practice may use a tool regularly without knowing whether it has changed costs, workload or client outcomes. Conversely, a tool may deliver practical benefits that are overlooked if the clinic has not tracked the work it was intended to reduce.
The report recommends collecting two to four weeks of baseline data before implementation, focused on the problem the practice wants to solve. Comparing those figures with results after rollout can provide a more grounded assessment than relying on impressions. The article does not offer a universal ROI figure or a claim that AI will pay for itself in every clinic; outcomes depend on the task, measurement and whether staff incorporate the tool into routine work.
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Use Is Not the Same as ROI
The report describes AI as moving beyond novelty in veterinary medicine, while warning that reported uptake is not a measure of success. Its cited survey provides a snapshot of professional use and interest in 2024; it does not establish how representative respondents were of all practices or calculate financial returns across the industry.
Tom Walsh, a veterinarian and owner of PrimePet Rehabilitation Therapy in Myrtle Beach, South Carolina, says documentation was the first area where his office saw a practical benefit. He describes using a tool to draft mobility and therapy notes during visits, rather than reconstructing them later. That account is an individual practice experience, not a controlled study or a sector-wide result.
The article also points to implementation as a factor in whether tools remain in use. If a clinic selects software without consulting the team or providing adequate training, staff may return to familiar workflows. In that case, the subscription cost can continue even if use fades. The report frames staff input and training as part of evaluating the investment, alongside the software itself.
What the Available Data Cannot Show
The cited survey does not report cost savings, revenue changes or payback periods for AI users. The article also provides no controlled comparison between practices that adopted AI and those that did not. It is therefore not possible from the cited figures to determine an average ROI or establish that AI caused a specific improvement.
Results for individual tools may vary, and the report does not specify common prices, implementation costs or the time required to train staff. It also does not quantify the accuracy or clinical outcomes of decision-support systems. For clinical decisions, the report says the veterinarian should remain in control. Whether any particular clinic’s tool is accurate, well-integrated and used consistently must be assessed locally.
Track Results After Rollout
For practices considering AI, the report’s next step is to define a target before signing or rolling out a tool: for example, reducing after-hours charting or cutting time spent on reminders. Clinics can record the relevant measure for two to four weeks beforehand, then repeat it after staff have received training and had time to use the system.
Practices should also check whether the tool is being used as intended and ask staff what is helping or creating extra work. The report does not identify a future industry-wide ROI study or a scheduled milestone. For now, whether AI pays off remains a question for each practice to answer with its own baseline, costs and post-adoption results.
Key Questions
Does the 2024 survey show that AI pays for itself?
No. It reports that 39.2% of respondents used AI and describes usage frequency among people who had tried it. It does not calculate financial returns or time savings.
Which veterinary tasks may be easiest to measure?
The report points to documentation and client communication. Practices can track chart completion time, same-day record completion, after-hours charting, no-show rates, reminder responses and time spent on outbound calls.
How should a clinic establish a baseline?
Before adopting a tool, the report recommends recording relevant measures for two to four weeks. The measures should match the problem the clinic wants the AI tool to address.
Can AI decision-support tools replace a veterinarian’s judgment?
The report presents these systems as tools that may surface relevant considerations, not make the clinical decision. It says the veterinarian should remain in control.
Why might an AI subscription fail to produce a return?
The report says a rollout without staff consultation or adequate training can result in employees reverting to old workflows. If use declines while the subscription continues, the clinic may not receive the intended benefit.
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