A new generation of physicians is emerging who understand both clinical medicine and artificial intelligence from the ground up, fundamentally changing how doctors will practice in the coming decade. Stevan Fairburn, M.D., M.S., recently became the first student to earn a Master of Science in AI in Medicine from the UAB Marnix E. Heersink Institute for Biomedical Innovation while simultaneously completing medical school, representing a shift in how medical education is preparing doctors for a technology-driven future.

Rather than treating AI as an afterthought or external tool that physicians must learn to tolerate, Fairburn's dual degree program embeds artificial intelligence directly into medical training. This approach reflects a growing recognition across healthcare systems that clinicians need hands-on understanding of how AI actually works, not just how to use it. For Fairburn, who grew up in Tuscaloosa, Alabama, and attended the United States Air Force Academy before switching to medicine, the path to combining these fields was unexpected but ultimately natural.

How Did a Future Surgeon Become an AI Expert?

Fairburn's journey began with a simple flyer taped to a wall at UAB in 2023. At that time, artificial intelligence had suddenly become impossible to ignore, with AI chatbots gaining widespread attention just months earlier. Curious about what was actually happening beneath the headlines, Fairburn enrolled in a course on AI in medicine through the newly established Marnix E. Heersink Institute for Biomedical Innovation. What started as a single class evolved into something far more ambitious.

He completed the AI in Medicine Graduate Certificate program while balancing the already demanding workload of medical school. Fifteen additional credit hours. Long nights. Extra projects. Additional research. The deeper he went into the material, the more he recognized a familiar feeling from childhood, comparing it to sitting on the floor building with Legos and becoming fascinated not just by the final structure but by the architecture underneath it. By the time Fairburn finished the certificate program, UAB had officially launched the full Master of Science in AI in Medicine, and he was already halfway through the requirements.

"I basically went to them and said, 'Hey, I am already halfway through this. Are they going to make me stop now?'" Fairburn said, laughing about convincing medical school leadership to let him pursue a second graduate degree simultaneously.

Stevan Fairburn, M.D., M.S., First MS Graduate in AI in Medicine at UAB

The program moved beyond headlines and hype into the mechanics of how artificial intelligence actually works. Fairburn studied neural networks, model architecture, implementation science, responsible deployment, bias evaluation, and healthcare integration. He learned the critical difference between an AI system that sounds convincing and one that can safely function in a clinical environment where lives are at stake. Most importantly, he learned how physicians can shape the future of AI rather than simply react to it.

What Does AI Fluency Actually Mean for Doctors?

Ask Fairburn what meaningful AI adoption actually looks like in medicine, and he does not immediately jump into technical jargon or futuristic predictions. Instead, he explains it in terms of what he calls three levels of AI fluency, with the first level being the most accessible and, in many ways, the most important because it removes fear from the equation.

At the foundational level, AI becomes a thinking partner. This is where professionals use tools like language models to brainstorm ideas, organize thoughts, summarize information, explore possibilities, and challenge assumptions. No coding background is required. No technical expertise is necessary. The goal is simply learning how to ask better questions and interact with the technology intentionally.

Steps to Building AI Fluency in Clinical Practice

• Foundational Level: Use AI tools like language models as thinking partners to brainstorm ideas, organize patient education materials, simplify research summaries, and explore clinical possibilities without requiring coding skills or technical expertise.
• Clinical Integration: Learn how to safely deploy AI systems in healthcare environments where patient safety is paramount, including understanding bias evaluation, responsible deployment practices, and how to maintain clinician oversight.
• Physician Leadership: Develop the ability to shape the future of AI in medicine rather than simply react to technological changes, ensuring that clinical needs and patient care remain at the center of AI development.

Fairburn's capstone project reflected exactly where his clinical interests and technological interests intersected. He developed an AI model to give clinicians real-time access to their documents at the point of care, solving a practical problem that directly improves how doctors work with patients.

What intrigued Fairburn most was not the fantasy of AI replacing physicians. In fact, he believes the opposite is true. He emphasized that clinicians cannot be removed from medicine, and AI is not going to replace doctors. Instead, AI can help physicians empathize more with patients by giving them back the extra five minutes to really connect with the person sitting in front of them.

"You cannot take the clinician out of medicine. AI is not going to replace doctors. But it can help them empathize more with patients. It can give them back the extra five minutes to really connect with the person sitting in front of them," Fairburn explained.

Stevan Fairburn, M.D., M.S., First MS Graduate in AI in Medicine at UAB

The MS in AI in Medicine program at UAB represents a broader shift in medical education. Rather than waiting for physicians to learn about AI after they finish their training, the program integrates artificial intelligence directly into medical school. Fall semester applications are due August 1, and the program offers hands-on AI training, opportunities to learn at the intersection of clinical care and innovation, research opportunities to work on real-world healthcare challenges with expert faculty, and career preparation for roles in imaging, diagnostics, precision medicine, and AI healthcare.

Fairburn is heading to a general surgery residency at Wake Forest, where he plans to apply AI in the surgical setting. He represents something larger than a single graduate from a new MS program. He is a new kind of physician emerging at the intersection of medicine, technology, and human connection, and as healthcare systems across the world wrestle with burnout, workforce shortages, information overload, and rapidly evolving technology, his approach offers a model for how medical education can prepare the next generation of doctors to thrive in a world where artificial intelligence is not a future possibility but a present reality.