New-grad veterinarian turns AI builder as vet med tools mature
CURRENT BRIEF VERSION: A new generation of veterinarians is starting to shape the AI conversation in practice, not just use the tools. In a recent Vet Life Reimagined episode highlighted around WVC, Jason Szumski, DVM, described his path from recent veterinary graduate to co-founder of VetSOAP, an AI documentation platform built with Aaron Smiley, DVM. University of Illinois College of Veterinary Medicine reporting shows the pair launched VetSOAP in late 2023, with the product designed to turn exam-room audio into SOAP notes and, in Szumski’s telling, help address two pain points for early-career clinicians: confidence and speed. AAHA also profiled VetSOAP in 2024 as part of a broader wave of AI tools entering veterinary workflows. (vetmed.illinois.edu)
Why it matters: For veterinary professionals, this story is less about one founder and more about where innovation is coming from. Szumski’s comments connect AI adoption to the realities of new-graduate practice: higher caseloads, documentation burden, and the need for mentorship when experienced support isn’t always available. That lines up with broader industry signals. In recent Vet Life Reimagined conversations, leaders including Christie Long, DVM, and Mike Mossop, DVM, framed veterinary innovation around sustainability, relationship-centered care, and using technology as a “co-pilot” that supports people rather than replacing them. Research cited in Frontiers in Veterinary Science points to growing optimism and adoption of AI among veterinary professionals, while JAVMA-linked reporting and AVMA commentary have also framed technology and record-keeping improvements as one path to improving efficiency in companion animal practice. At the same time, conversations in the field are shifting from novelty to oversight: Andy Roark, DVM, said on The Cone of Shame that AI scribes have made his days in practice better by reducing administrative work, but he and Aaron Massecar, MA, PhD, also urged practices to look past marketing claims and ask what these tools actually improve, what errors they may introduce, and how privacy and quality control are being handled. Roark’s related discussion of training veterinarians to work across a spectrum of care also reinforces why efficiency tools matter only if they fit real-world practice constraints and support better outcomes in context. (vetmed.illinois.edu)
What to watch: Expect the next phase to focus on whether veterinary AI tools can prove they save time, protect record quality, and fit safely into training and supervision models for early-career teams—while supporting a more sustainable, more human version of practice rather than adding another layer of complexity. (vetmed.illinois.edu)