
In August 2024 I wrote a blog titled Who’s Driving The Bus? Vets at the wheel of decisions about driving the bus to an accurate diagnosis. In January 2025 I am rewriting that blog with the inclusion of AI.

Have you ever wondered who's really driving the complex journey of diagnosing and treating our beloved pets? Imagine this: a veterinarian at the helm of a bus, each stop critical, each decision impactful. But in today’s rapidly evolving landscape, the vet is no longer alone at the wheel.
Artificial intelligence (AI) has emerged as a powerful co-pilot, transforming the way
we approach diagnostics, communication, and treatment planning.
Welcome aboard the diagnostic bus of the future, where veterinarians, assisted by AI, navigate the intricate road from initial exam to effective treatment.
The License to Drive in the AI Era
Just as a bus driver needs a license to operate, veterinarians must be thoroughly trained and certified. With the integration of AI, however, their license now includes the ability to work with advanced diagnostic tools powered by machine learning. AI doesn’t replace the need for veterinary expertise but enhances it, providing quick access to a global database of symptoms, conditions, and treatment protocols. Continuous education for vets now often includes training in AI systems, ensuring they can use these tools effectively while maintaining their critical role as the ultimate decision-makers.
Knowing the Destination and the AI-Enhanced Stops
In veterinary medicine, the destination remains a successful treatment outcome. However, the stops along the way are now augmented by AI, making the diagnostic process more precise and efficient.
History: Enhanced Data Gathering: Traditionally, the vet gathers information about the animal’s health history and current symptoms. With AI-powered tools, this step is transformed. Natural Language Processing (NLP) systems, like AI scribes, can transcribe and analyze conversations with pet owners, flagging potential red flags or patterns the vet might not immediately notice.
Signalment: Personalized Insights: Signalment, which involves identifying the animal’s age, breed, sex, and reproductive status, is now paired with AI's ability to cross-reference millions of data points. This helps vets predict breed-specific health risks and tailor diagnostic approaches more effectively.
Physical Examination: Augmented Observations: AI tools such as wearable sensors, thermal imaging cameras, and portable diagnostic devices can collect real-time data during physical exams. For example, AI can analyze subtle changes in vital signs or detect abnormalities in imaging scans, providing the vet with a detailed overview that enhances their clinical findings.
Diagnostic Tests: Precision and Speed: AI-driven diagnostic tools revolutionize this stop. From interpreting blood test results to analyzing imaging scans, AI accelerates the process and improves accuracy. Machine learning algorithms can identify patterns in radiographs or ultrasounds with precision, reducing the chances of misdiagnosis and enabling earlier interventions.
Charging for the Journey in a Digital Landscape
Just as a bus driver knows how much to charge for the journey, veterinarians must communicate the costs of diagnostics and treatments effectively. With AI-enabled cost estimation tools, pet owners can receive transparent breakdowns of expenses before procedures begin. These tools also help veterinarians balance cost efficiency with the quality of care, offering evidence-based recommendations tailored to the owner's financial situation.
Knowing the Rules of the AI-Powered Road
Veterinary professionals must adhere to ethical guidelines and legal requirements, much like bus drivers follow traffic rules. The integration of AI adds new dimensions to these responsibilities. Ensuring the ethical use of AI involves transparency about its role, safeguarding data privacy, and understanding the limitations of these technologies. Veterinarians must also remain vigilant to prevent over-reliance on AI, always applying their professional judgment to every decision.
The Role of AI in Teaching Future Vets
Teaching veterinary students about the diagnostic process now includes training in AI applications. By learning to collaborate with AI tools, they gain confidence in leveraging technology to enhance their clinical skills. From simulated diagnostic scenarios to AI-guided practice cases, these future veterinarians are equipped to navigate a rapidly changing field.
AI also plays a role in mentorship and remote consultations. Online platforms powered by AI facilitate real-time learning and collaboration between experienced vets and students, fostering a global exchange of knowledge. This prepares new veterinarians not only to manage complex cases but also to adapt to the evolving landscape of veterinary medicine.
The Human Touch in an AI-Driven World
The integration of AI in veterinary diagnostics enhances efficiency, precision, and accessibility, but the human element remains irreplaceable. The veterinarian's role as the empathetic, skilled decision-maker ensures that every step of the journey, from history taking to treatment, is guided by compassion and expertise.
In this new era, the diagnostic bus is no longer a solitary vehicle, but part of a connected fleet powered by AI. Together, veterinarians and AI are redefining what it means to provide exceptional care, steering animals and their owners toward the destination of health and wellness with unparalleled accuracy and empathy.
Will the Bus Become a Self-Driving Vehicle in Veterinary Medicine?
As we embrace the transformative potential of artificial intelligence in veterinary medicine, a provocative question arises:
Will the diagnostic bus eventually become a self-driving vehicle?
In other words, could AI one day replace veterinarians as the primary drivers of diagnostic and treatment decisions?
The Case for Self-Driving Diagnostics
Advancements in AI are already pushing the boundaries of what's possible in veterinary medicine. Algorithms can analyze imaging scans with near-human accuracy, predict diseases based on genetic markers, and even suggest treatment plans based on millions of case studies. Telemedicine platforms powered by AI have enabled remote consultations, where algorithms triage cases and guide veterinarians, or in some cases, pet owners, on the next steps.
AI's ability to process vast amounts of data quickly and consistently makes it a tempting candidate for automating many aspects of veterinary care. In situations where access to skilled veterinarians is limited, such as rural areas or under-resourced clinics, AI-powered systems could act as an interim driver, providing high-quality diagnostics and treatment recommendations.
Will Vets Always Hold the Steering Wheel?
Despite these advancements, the bus of veterinary medicine is unlikely to become a fully self-driving vehicle any time soon. Here's why:
The Complexity of Animal Health: Animals can't describe their symptoms, making veterinary medicine uniquely challenging compared to human healthcare. Subtle behavioral changes or non-verbal cues often hold critical diagnostic information. While AI can assist in identifying patterns, it lacks the nuanced understanding and empathy required to interpret an animal’s condition holistically. At least today.
The Importance of the Human-Animal Bond: Pet owners often view veterinarians as trusted advisors. This relationship is built on communication, trust, and emotional connection. These are qualities that AI cannot replicate - yet. Veterinarians don't just diagnose and treat; they provide reassurance and guidance to anxious pet owners, a role that requires compassion and interpersonal skills.
Ethical Considerations: Ethical dilemmas, such as decisions about end-of-life care, require moral judgment and empathy. These are deeply human traits that no algorithm can embody - yet. Even the most advanced AI systems would struggle to navigate the ethical gray areas that are inherent in veterinary medicine.
The Role of Professional Judgment: AI is only as good as the data it’s trained on, and its recommendations are not infallible. Veterinarians play a crucial role in validating AI-generated insights, applying their professional judgment to tailor decisions to the unique needs of each patient. At least today.
Rick’s Commentary
The foreseeable future of veterinary medicine will likely feature a collaborative model,
where AI acts as a co-pilot rather than a replacement for veterinarians.
In this scenario, AI handles routine or repetitive tasks, such as analyzing diagnostics, creating treatment options, or managing workflows, while veterinarians focus on the critical human aspects of care, such as communication, ethical decision-making, and personalized treatment.
The bus may become smarter, faster, and more efficient with AI in the co-pilot’s seat, but it’s unlikely to drive itself anytime soon.
Right …?
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