How a recent grad became an AI founder in veterinary medicine

CURRENT FULL VERSION: Jason Szumski, DVM, is emerging as a visible example of a new veterinary career path: moving almost immediately from vet school into both clinical practice and AI product building. The recent attention around Szumski comes through veterinary media and podcast coverage focused on how younger veterinarians are helping shape technology adoption in practice, especially around AI scribes and workflow tools. Publicly available background shows Szumski graduated from the University of Illinois in 2023 and co-founded VetSOAP with Aaron Smiley, DVM, to automate SOAP-note creation from exam audio. A Vet Life Reimagined profile fills in more of the picture, describing him as a full-time veterinarian at a 24/7 ER/GP clinic, a speaker at major meetings, and someone trying to build veterinarian-owned tools around what he sees firsthand in practice. (aaha.org)

The backdrop is a profession under pressure to do more with limited time and staffing. In AAHA’s 2024 coverage of AI in practice, Smiley and Szumski argued that documentation automation could help practices redirect time toward patient care and communication with pet parents. That framing lines up with broader workforce concerns in companion animal medicine, where efficiency, retention, and support for newer graduates remain central operational issues. AAHA’s article also cited IDEXX’s “Finding the Time” report projection that productivity would need to rise by 40% by 2030, helping explain why AI tools are getting serious attention beyond the innovation fringe. (aaha.org)

The clearest reported details about Szumski’s path come from the University of Illinois alumni feature on VetSOAP. That article described him as a recent graduate practicing in suburban Chicago while helping build software designed to generate patient records from audio recordings. It also tied the product concept to a specific early-career pain point: confidence. Szumski said the transition from student to practicing veterinarian leaves many new grads with knowledge gaps and limited support, and he suggested AI could serve not just as a documentation tool, but as a form of structured clinical backup by surfacing curated information and possible diagnostic options. At the time of that report, VetSOAP was in beta. Vet Life Reimagined adds that Szumski originally thought he might become an aerospace engineer before moving into veterinary medicine, a detail that helps explain the engineering-style lens he now brings to workflow problems. (vetmed.illinois.edu)

That same Vet Life Reimagined conversation also points to a broader ambition for the technology than note-taking alone. Szumski discussed using AI to analyze his own clinical conversations through a research partnership with PetSmart Charities, with the aim of better understanding the gap between the care veterinarians offer and the care clients actually accept. That idea connects AI documentation to a bigger operational and ethical question in practice: not just what was recommended, but what was understood, feasible, and ultimately chosen. It also places VetSOAP in a wider movement toward using data and workflow tools to make care delivery more realistic and sustainable in everyday settings.

That message fits a wider wave of experimentation with AI scribes in veterinary medicine. In January 2026, Andy Roark, DVM, MS, and Aaron Massecar, PhD, discussed AI scribes through the lens of human medical literature, emphasizing potential benefits such as reduced administrative burden, improved records, better client connection, and possible burnout prevention, while also warning against uncritical hype. Roark was notably direct that he likes the technology, uses it, and finds that it makes his time in practice better by taking away administrative work he dislikes. Their conversation is notable because it shows the discussion has matured: the question is no longer whether AI will enter practice, but how veterinary teams should use it wisely. (drandyroark.com)

Industry adoption data suggests this is no longer a niche conversation. A 2024 survey conducted by Digitail in collaboration with AAHA collected responses from 3,968 veterinary professionals and found that 39.2% reported using AI tools in practice; among those who had tried AI for professional tasks, 69.5% said they used it daily or weekly. AAHA’s own editorial coverage summarized that finding as “nearly 40%,” reinforcing that AI has already moved into everyday workflows for a meaningful share of the profession. (prnewswire.com)

The wider conversation around innovation in veterinary medicine also helps contextualize why stories like Szumski’s are resonating. In Vet Life Reimagined interviews with leaders including Christie Long, DVM, and Mike Mossop, DVM, the recurring theme is that technology should support safer, more sustainable, relationship-centered care rather than distract from it. Mossop explicitly framed AI as a potential “co-pilot,” while Long emphasized that veterinary teams do not come to work primarily to innovate in the abstract; they come to care for patients, so any new tool has to make that work more sustainable for both people and pets. Those perspectives reinforce why AI scribes are gaining traction: they promise not just speed, but relief from friction that can erode care quality and team wellbeing.

There is also a parallel workforce conversation about what veterinarians are being trained to do in resource-constrained settings. In a separate Cone of Shame episode on spectrum of care, Roark and AAVMC leaders discussed the idea of pursuing “golden outcomes, not a gold standard” and meeting clients where they are, rather than defaulting to referral or idealized plans that may be out of reach. That framework matters here because tools that capture and analyze clinical conversations could eventually help practices better understand where recommendations break down, how options are presented, and whether communication supports realistic decision-making.

Why it matters: For veterinary professionals, the significance of Szumski’s story isn’t just that one young veterinarian launched a company. It’s that the skills increasingly valued in the workforce now extend beyond medicine alone: systems thinking, workflow design, data literacy, communication, and comfort evaluating software claims. If AI scribes continue to spread, practices will need clinicians who can test outputs, protect record integrity, think critically about privacy and accuracy, and decide where automation helps versus where human judgment must stay central. Szumski’s rise also suggests that recent graduates may play an outsized role in shaping these decisions, because they’re often closest to the friction points in training, onboarding, documentation, and client communication. The added reporting around his ER/GP work and research interest in recommendation-versus-acceptance gaps strengthens that point. (vetmed.illinois.edu)

There’s also a caution embedded in the momentum. Much of the public commentary so far comes from founders, vendors, and innovation advocates, which means the profession is still building its evidence base around veterinary-specific performance, error patterns, and best practices for implementation. Roark’s recent framing is useful here: AI scribes may reduce burden and improve connection, but veterinary teams still need to pay attention to what problems they might quietly create. And as Long and Mossop suggest in adjacent innovation conversations, the real test is not whether a tool feels advanced, but whether it supports humane, sustainable care in the exam room. (drandyroark.com)

What to watch: The next phase will likely center on validation and governance: more practice-level case studies, more discussion of data handling and record accuracy, tighter integration into practice software, and growing demand for evidence that these tools improve workflow without introducing new clinical or legal risk. It will also be worth watching whether AI documentation platforms expand into adjacent uses such as communication analysis, mentorship support for early-career veterinarians, and tools that help practices deliver spectrum-of-care medicine more consistently. For workforce leaders and educators, that may also mean expanding training around AI literacy, not as a novelty, but as a practical professional skill. (drandyroark.com)