Veterinary surveys show fast tech uptake, stubborn staffing strain

Veterinary practices are moving quickly on AI and digital workflow tools, but the latest survey data suggest technology alone isn’t solving the profession’s biggest pressure points. New 2026 findings from Instinct Science, reported by Today’s Veterinary Business and detailed in the company’s new general practice report, show broad adoption of new technology across companion animal practice, alongside continued concern about staffing, scheduling, and retention. In short, clinics are modernizing fast, but they’re doing it in response to persistent operational strain, not in place of it. (mychesco.com)

The backdrop is a profession that has spent several years balancing heavier caseloads, burnout concerns, and rising expectations from both teams and pet parents. Instinct’s 2024 emergency and specialty survey already showed staffing shortages affecting 78% of practices, though that was an improvement from 86% the year before. That same report found practices were investing in workflow changes, cloud-based systems, digital treatment sheets, and wellness efforts, with 54% of respondents reporting high or very high job satisfaction, up from 34% a year earlier. Those earlier signs of stabilization help explain why the new surveys are landing as less of a technology story than a practice redesign story. Other 2026 industry commentary points in the same direction: analysts and clinicians increasingly describe the field as being at a tipping point where innovation, client demand, and workforce limits are colliding, forcing practices to rethink not just tools but care delivery and team structure. (info.instinct.vet)

In general practice, Instinct surveyed 763 veterinary professionals for its 2026 State of General Practice Veterinary Care Report. According to the survey coverage, 48% of general practices said they’re already using AI in some capacity, most often for medical record and SOAP note creation, followed by diagnostic support. Nearly three-quarters of AI users said the tools improved efficiency. The same reporting found a sharp shift in employment structure: fewer than 10% of general practices still operate on traditional fixed full-time schedules, while about 40% offer part-time roles and 25% use four-day workweeks. Instinct’s own report summary says the research is meant to benchmark how practices are adopting technology, addressing staffing challenges, and improving patient care. (mychesco.com)

Emergency, specialty, and urgent care settings show a similar pattern, but with slower AI penetration and heavier staffing pressure. In Instinct’s 2024 emergency and specialty data, 79% of respondents said they either were not using AI or were unaware it was being used in their practice. Where AI was in use, it was concentrated in documentation, client communication, administrative work, inventory management, and some diagnostic support. More than half of respondents said new technology had improved work-life balance, and digital treatment sheets and cloud-based PIMS or EMR platforms were identified as top productivity tools. Even so, staffing shortages, compensation pressure, and overhead costs remained defining concerns. (info.instinct.vet)

Outside commentary suggests this mix of adoption and unease is not unique to Instinct’s audience. AAHA’s 2024 coverage of the Digitail survey said nearly 40% of veterinary professionals were already using AI tools, and most of those users were engaging with them daily or weekly. Digitail’s own follow-up framing sharpened the governance problem: in a survey of nearly 4,000 veterinary professionals, 83% said they were familiar with AI tools, 39% were already using them, 70% cited reliability concerns, and 43% said they lacked proper training. That has led some industry voices to argue that clinics may need an internal AI coordinator or champion to handle tool selection, rollout, prompt and template updates, staff enablement, and ethical guardrails, rather than treating AI like ordinary software. Today’s Veterinary Business also reported in 2025 that seven in 10 veterinary professionals were uneasy about the reliability and accuracy of AI tools used for diagnosis and treatment, while a 2026 JAVMA survey found 90.5% of veterinary workers had little or no formal AI training and only 25% said AI was being used in their workplace. Taken together, those findings suggest veterinary medicine is in an uneven adoption phase, where interest and experimentation are outpacing formal education and governance. (aaha.org)

There are also signs that vendors and clinicians are trying to broaden the AI conversation beyond note generation. Some argue the bigger opportunity is using structured visit data to surface operational and clinical patterns, such as missed charges, appointment bottlenecks, or communication gaps, instead of stopping at faster documentation. Others emphasize more practical near-term gains: better client summaries, clearer follow-up instructions, support for difficult conversations, and incremental reductions in charting fatigue. In parallel, veterinary commentators are warning that AI is already creeping into employment workflows, including hiring and screening, adding a labor-market dimension to the profession’s broader AI transition. None of that means the technology is mature or uniformly trusted, but it does suggest AI’s footprint is expanding from the exam room into management, analytics, and employment decisions.

There’s also a physical-design angle to this shift. Today’s Veterinary Business has noted that mobile devices, cloud systems, AI transcription, and client-facing digital workflows are beginning to influence hospital layouts themselves, from smaller reception desks and greeter kiosks to exam rooms designed around conversation and shared screens instead of fixed desktop stations. That matters because it reinforces a broader point from the surveys: digital adoption is not just changing software stacks; it is changing how clinics organize space, staff roles, and client interactions.

Why it matters: For veterinary professionals, the practical question is no longer whether AI and digital systems are entering the hospital, but whether practices can integrate them without adding friction, risk, or distrust. Documentation support, scheduling flexibility, and cloud-based workflows may help teams reclaim time and improve consistency, especially in understaffed settings. But the surveys also point to a widening management challenge: if clinics adopt tools faster than they train teams, define guardrails, or validate outputs, efficiency gains could be offset by clinician skepticism, uneven use, or mistakes in high-stakes clinical contexts. That’s especially relevant in emergency and specialty medicine, where the tolerance for workflow failure is low. The same logic increasingly applies to nonclinical functions too, including hiring, analytics, and client communication, where AI can shape decisions without always being visible. (mychesco.com)

There’s also a business and labor angle. Flexible scheduling appears to be moving from perk to competitive necessity, and the technology conversation is increasingly tied to retention, not just productivity. AVMA’s 2025 economic report found most practice owners felt they were broadly keeping up with technology, but time and cost remained the biggest barriers for those who felt behind. That aligns with the Instinct surveys’ broader message: practices may be willing to modernize, but implementation capacity is uneven, and financial pressure is still real. For independent clinics in particular, the next phase may hinge less on buying tools than on choosing the few that genuinely reduce administrative load for veterinarians, technicians, and support staff. Related trends abroad also hint at where workforce redesign could go next: in Australia, telehealth use among pet owners remains relatively low, but many veterinarians working in telehealth report better mental health, more predictable schedules, and a way to stay in practice while managing family responsibilities or easing into retirement. (ebusiness.avma.org)

What to watch: The next signal to watch is whether veterinary organizations, software vendors, and employers move from adoption metrics to standards, training, and accountability. More survey work is likely this year, but the more consequential developments may be continuing education around AI literacy, clearer practice policies on documentation and diagnostic support, designated internal owners for AI oversight, and stronger evidence on which tools actually improve care team capacity. It will also be worth watching whether digital change spreads further into hospital design, telehealth, and hiring workflows, because those shifts would signal that AI is becoming embedded in the operating model of veterinary care, not just layered onto it. If those pieces lag, adoption may continue, but confidence may not. (pubmed.ncbi.nlm.nih.gov)