The introduction of high-performance AI in veterinary medicine is frequently met with the fear that by making diagnostic reporting “too easy,” we will inadvertently automate ourselves out of a profession. This perspective, however, relies on the “fixed-pie” fallacy, the idea that there is an unchanging amount of work to be done. In reality, the 19th-century British economist William Stanley Jevons discovered that when we lower the barriers to high-quality output, the world does not demand less of the expert; it demands significantly more. Through the logic of the Jevons Paradox, it becomes clear that diagnoVET is not a replacement for the veterinarian, but a catalyst that widens the imaging bottleneck, turning administrative blocks into engines of clinical growth.
The Jevons Paradox
In his 1865 book, The Coal Question, William Stanley Jevons dismantled the prevailing logic of his time. Many believed that more efficient steam engines would lead to a decrease in coal consumption. Jevons argued the exact opposite: that “whatever... conduces to increase the efficiency of coal, and to diminish the cost of its use, directly tends to augment the value of the steam-engine, and to enlarge the field of its operations,” (Jevons, 1865).
When the cost of extracting value from a resource drops, that resource’s breadth of application is greatly widened. In the mid-19th century, that resource was coal; in the 21st-century veterinary clinic, that resource is diagnostic imaging.
Historically, a comprehensive imaging report was a “high-cost” resource in terms of time, mental fatigue, and administrative friction. Before diagnoVET, a single study could consume 40 minutes of a specialist’s day, spent on the manual labor of typing measurements and filling templates. By making this process 85% more efficient, diagnoVET does not diminish the value of the specialist; it swings the balance in favor of imaging, making it possible and profitable to apply high-level images to a volume of patients that was previously impossible to manage.
How diagnoVET Works: Expanding the “Imaging Engine”
diagnoVET is a multimodal AI agent designed to handle the task of “burning through” raw data, allowing the clinician to focus on the high level decisions of the case. Unlike simple image recognition tools, diagnoVET acts as a comprehensive clinical synthesizer, integrating clinical history and X-ray data or ultrasound findings to generate structured, professional reports in under five minutes.
In his article, More Efficiency, More Demand, author and former CTO of Etsy, Mike Fisher, analyses how efficiency drives demand using the example of radiologists. In the same way with diagnoVET, when we lower the time and cognitive costs of a report, we trigger a wave of expansion that transforms the specialist’s role from a bottleneck into a growth engine. Here is how that transition manifests in the real-world clinic:
1. The Widening of the Pipe: From 200 to 600 Studies
Jevons noted that “new modes of economy (innovation) will lead to an increase of consumption.” We see this in the success of veterinarians Josefina Proietti and Macarena Rivero’s clinic when incorporating diagnoVET. By reducing report time by 85%, they didn't reduce their staff; they tripled their patient load. They moved from performing 200 studies a month to 600 with the same three people. With this speed, appointments could become scheduled on the day the inquiry came in, whereas, before diagnoVET there was a three day delay. When the time “cost” of each report dropped, the clinic was able to increase their operations, turning their clinic into a high-output imaging hub.
2. Efficiency as an Ambition Inflator
Better tools inflate ambition, and every resolution ignites a new set of problems worth solving. When you automate the “lower layers” of radiology (typing and template filling), you free the veterinarian to handle the “higher layers” of case management. In this way, human and machine labor are complements, not substitutes. The machine handles the repetitive, the human handles the creative and the governing.
3. Objective Safety and “Exciting New Activity”
Jevons argued that “the progress in any branch... excites a new activity in most other branches.” By providing an objective and unbiased agent, diagnoVET builds trust and resilience. When reports are standardized and comprehensive, referring veterinarians feel more confident in your services, which increases the demand for your clinic’s expertise. diagnoVET’s efficiency doesn't erase the specialist; it multiplies their relevance. By allowing your clinic to handle more imaging, you identify more pathologies, which in turn leads to more surgeries, treatments, and successful patient outcomes, expanding the entire veterinary ecosystem.
Following Jevons Paradox, as diagnoVET gives veterinarians back their time, patients can be addressed sooner and at a greater scale, professionals can focus on the more complex diagnoses, and the efficiency of the field increases, allowing veterinarians to quickly reach a diagnosis, identify the prognosis, and consequently increase the survival rate of patients regarding their pathologies.
The Future of the “Diagnostic Detective”
The fear that AI leads to layoffs assumes that there is a ceiling on how much care we want to provide for our patients. But as the “cost” of high-quality imaging reports drops, a clinic’s potential grows. The veterinarians do not disappear; they become more indispensable. They shift from being data entry clerks to being “Diagnostic Detectives”, specializing on synthesizing more information, handling complex cases, and leading their teams with a confidence that only efficient, unbiased tools can provide.
diagnoVET is not here to do your job. It is here to ensure that your job is no longer limited by the speed of your keyboard, but only by the depth of your veterinary ambition.
References & Further Reading
- diagnoVET Case Study. Clinicians Triple Patient Load and Reclaim Mental Space: Josefina Proietti and Macarena Rivero.
- Fisher, M. (2024). More Efficiency, More Demand: The future of software engineers and data scientists is bright. Mike Fisher's Substack.
- Jevons, W. S. (1865). The Coal Question: An Inquiry Concerning the Progress of the Nation, and the Probable Exhaustion of Our Coal-Mines. Available via HathiTrust.