ODBMS Industry Watch

“When patients say that AI listens better than their doctor, they are rarely making a statement about empathy. They are making a statement about time.”

Q1. Your book (*) argues that medical schools teach the technical anatomy of disease but not the anatomy of human hopes and fears, that physicians learn to diagnose but not always to truly listen. As AI systems increasingly match or exceed physicians on the technical and encyclopedic dimensions of medicine, you suggest the physician’s role as a trusted human ally becomes more important, not less. But that humanistic competency is, by your own account, something doctors are largely left to acquire on their own, often through harsh and humbling experience.

What would it actually take to teach this deliberately, and do you believe medical education as an institution is capable of changing fast enough to do so before an entire generation of physicians has already been shaped by the system as it exists today?

Mathias Goyen: The arrival of AI has created a fascinating paradox. The more capable our technology becomes at processing information, the more valuable distinctly human capabilities become. For centuries, medicine has largely defined excellence through knowledge, diagnostic accuracy, and technical skill. Those qualities will always remain essential, yet they are no longer sufficient on their own because information has become increasingly accessible while judgment, trust, and the ability to accompany another human being through uncertainty have become the true scarce resources.

This is precisely where I believe medical education faces its greatest challenge. We still devote enormous energy to teaching students how diseases behave, yet comparatively little attention is given to how people behave when they become patients. We teach physiology, pathology, pharmacology, and anatomy with remarkable rigor, but far less time is spent understanding fear, uncertainty, hope, grief, or the psychological complexity that accompanies almost every serious diagnosis. Those aspects are often treated as something physicians will simply acquire through experience, as though compassion naturally emerges after enough years on the wards. Experience certainly matters, but experience alone is an unreliable teacher. Some physicians become wiser through it, while others simply become more efficient.

The encouraging news is that I do not believe these qualities are beyond teaching. What we cannot teach through lectures alone can be cultivated through deliberate exposure to complexity. Medical students should spend more time observing difficult conversations than memorizing another list of rare syndromes. They should regularly reflect on situations in which there was no perfect answer. They should discuss uncertainty with senior clinicians who are willing to admit that medicine is often practiced without complete certainty and that wisdom frequently consists of choosing responsibly among imperfect alternatives rather than identifying a single correct solution. In other professions, including aviation, the military, and executive leadership, reflection after difficult situations is considered an essential part of professional development. Medicine still tends to reward certainty even when uncertainty is the daily reality.

AI makes this transformation more urgent, not because it diminishes physicians, but because it changes where physicians create value. If machines increasingly become exceptional at organizing knowledge, physicians must become exceptional at helping people navigate that knowledge. Patients will continue to need someone who can interpret information within the context of an individual life, balance competing priorities, communicate honestly when certainty is impossible, and remain present when medicine reaches its limits. None of these responsibilities become less important because an algorithm is available. If anything, they become more central to the profession than ever before.

Can medical education change quickly enough? I believe it can, but only if we accept that the future physician requires a broader definition of competence than the one that has guided us for generations. Medical schools have repeatedly demonstrated their ability to adapt when science demanded it. We incorporated molecular biology, genomics, and digital medicine into our curricula because they became indispensable. We should now show the same determination in teaching judgment, communication, ethical reasoning, adaptability, and the ability to lead patients through uncertainty. These are not soft skills that merely complement medical expertise. In the age of AI, they increasingly define it.

Q2. Patients increasingly arrive at appointments having already consulted ChatGPT, Gemini, or Claude, sometimes reporting that “AI listens as no doctor did before.” That is a remarkable and uncomfortable statement about the current state of clinical encounters.

What does it actually mean, in practice, for a physician to compete with, or more usefully, to integrate, a technology that can offer patients more time, more patience, and the appearance of being heard, within a healthcare system that structurally cannot offer physicians the time to do the same?

Mathias Goyen: I actually do not believe physicians should think of themselves as competing with AI. The moment we begin framing the relationship as a competition, we have already misunderstood what patients are really telling us.

When patients say that AI listens better than their doctor, they are rarely making a statement about empathy. They are making a statement about time. AI never interrupts. It never looks at the clock. It never appears distracted by the next patient waiting outside the door. It allows people to finish their thoughts before responding. That experience alone can create a powerful feeling of being heard, even though the technology itself experiences neither compassion nor understanding.

That observation should not make physicians defensive. It should make us reflective. It forces us to ask a difficult question about our healthcare systems rather than about our technology. Have we gradually created an environment in which efficiency has become so dominant that patients increasingly value uninterrupted attention as much as medical expertise? I suspect the answer is yes.

Ironically, I see this development as an opportunity rather than a threat. If patients arrive having already explored their symptoms with AI, the consultation no longer needs to begin with the simple transfer of information. Instead, it can begin at a much more meaningful level. The physician can help patients interpret what they have learned, distinguish probable explanations from unlikely ones, place isolated facts into the context of an individual life, and openly discuss uncertainty where uncertainty genuinely exists. In other words, the conversation can move away from information retrieval and toward judgment.

This also changes the physician’s role in a subtle but important way. Historically, physicians often served as the primary source of medical knowledge. Increasingly, they become trusted interpreters of knowledge that is already available to everyone. I consider that an evolution rather than a loss. Trust has never depended simply on possessing information that others do not have. Trust emerges when someone helps us understand what information actually means for our own lives.

The real danger, therefore, is not that AI becomes too patient. The danger is that healthcare systems conclude that because AI can provide unlimited conversational capacity, human conversation becomes less necessary. That would fundamentally misunderstand why patients seek physicians in the first place. Patients do not simply come to receive answers. They come to share responsibility for decisions that may profoundly affect their lives. They want someone who can recognize when uncertainty remains, explain why different options carry different consequences, and occasionally say, “I do not know, but we will work through this together.” Those moments create trust in a way that no technology can replicate.

Ultimately, I hope AI will not replace the conversation between physician and patient but elevate it. If AI can assume much of the informational and administrative workload, physicians should have greater freedom to focus on the conversations that require wisdom rather than recall, presence rather than speed, and judgment rather than computation. Whether that vision becomes reality, however, depends far less on the technology itself than on the choices healthcare organizations make about how the time that AI creates is ultimately used.

Q3. You write that the physician today carries not only a stethoscope but also data, and that patients now often have access to the same data and the same AI tools that physicians have. This symmetry is historically unprecedented in medicine. For healthcare leaders and policymakers far beyond any single organization or technology vendor, what do you believe is the single most important structural or educational change needed to ensure that this newly symmetrical relationship between doctor and patient becomes a source of trust and collaboration, rather than confusion, distrust, or a further erosion of the time available for genuine human connection?

Mathias Goyen: If I had to identify a single priority, it would not be the introduction of more technology. It would be the deliberate cultivation of judgment as a shared competency between physicians and patients.

For most of medical history, knowledge itself created an asymmetry. Physicians possessed information that patients simply could not access. Today that asymmetry is rapidly disappearing. A patient can read scientific publications, access clinical guidelines, ask sophisticated questions of large language models, and arrive in the consultation having accumulated an extraordinary amount of information. That development should not be feared. An informed patient is not a threat to medicine. Quite the opposite. Mutual understanding has always been the foundation of shared decision making. The challenge is that access to information is not the same as the ability to interpret it. Modern medicine generates probabilities rather than certainties. Imaging findings require clinical context. Laboratory values depend on medical history. Risk predictions require value judgments about what matters most to an individual patient. AI can organize remarkable amounts of information, yet deciding what deserves attention, what uncertainty remains acceptable, and which option best reflects a person’s preferences continues to require human judgment.

This is why I believe healthcare systems should move beyond thinking primarily about digital literacy and begin focusing much more deliberately on decision literacy. Physicians need to become better at explaining uncertainty without undermining confidence. Patients need to become more comfortable understanding that medicine rarely offers absolute answers and that reasonable experts can occasionally reach different conclusions while acting in good faith. Trust grows when uncertainty is acknowledged honestly rather than hidden behind artificial certainty.

There is also an important leadership responsibility. Healthcare organizations should resist the temptation to measure success exclusively through productivity metrics, waiting times, or numbers of consultations completed. Those indicators matter, but they tell us remarkably little about whether patients actually understood the decisions that were made together. If AI allows us to create more informed patients but simultaneously leaves physicians with even less time to interpret information collaboratively, we will have solved the wrong problem.

Ultimately, I believe the relationship between physicians and patients is becoming less hierarchical and more collaborative. That is one of the most profound cultural shifts medicine has experienced in generations. The physician’s authority will increasingly arise less from exclusive access to knowledge than from the ability to guide thoughtful decisions in situations where knowledge alone is insufficient. Patients, in turn, become active participants rather than passive recipients of care. I consider that an extraordinarily positive development because trust built through partnership is ultimately stronger than trust built through dependency.

If we succeed in creating healthcare systems that value dialogue as much as diagnosis, AI may become one of the greatest opportunities medicine has seen in decades. If we fail, we may discover that we improved the flow of information while unintentionally weakening the relationships that give information its meaning.

Q4. You made the unusual transition from practicing physician and academic radiologist to global Chief Medical Officer inside a major commercial MedTech company. That move places you in a position that carries an inherent tension: the Hippocratic commitment to the patient’s interest above all else, and the commercial reality of an organization whose technologies must ultimately sell and generate returns for shareholders.

How do you personally navigate that tension in your day-to-day decisions, and what would you say to a young physician who is skeptical that genuine humanistic medicine and a senior leadership role inside a commercial healthcare company can coexist with integrity?

Mathias Goyen: This question assumes a tension that certainly exists, yet perhaps not in quite the way many people imagine. Throughout my years in industry, I rarely experienced the debate as one between doing what is right for patients and doing what is right for the business. More often, I experienced it as a question of time horizon.

Healthcare is unusual because trust accumulates slowly and can disappear remarkably quickly. Physicians recommend technologies because they believe they improve patient care. Hospitals invest because they expect meaningful clinical value over many years. Companies build reputations over decades rather than quarters. When viewed from that perspective, serving patients well and building a successful business are not competing objectives. They are deeply interconnected. Commercial success becomes sustainable only when clinicians genuinely believe that a company helps them care for patients more effectively.

As a physician working inside industry, I always considered my role somewhat different from many other leadership positions. I was not there to replace commercial thinking. I was there to complement it with clinical perspective. Every discussion about product development, workflow, AI, education, or implementation eventually led me back to the same questions. Does this solve a meaningful problem? Will it make a physician’s work easier, more thoughtful, or safer? Will it ultimately improve the patient’s experience or outcome? Those questions do not eliminate difficult business decisions, but they provide a remarkably consistent compass.

I also learned something that surprised me. Before joining industry, I imagined companies primarily as organizations that develop technologies. Over time I came to realize that their greatest influence often lies elsewhere. They shape education. They convene experts from around the world. They invest in research. They help translate scientific discoveries into everyday clinical practice. They create ecosystems that individual hospitals or universities could rarely establish on their own. When those responsibilities are approached thoughtfully, industry becomes an important partner in advancing healthcare rather than merely supplying it.

To a young physician who is skeptical about entering industry, I would simply say that integrity does not depend on the logo on your business card. It depends on whether you remain intellectually honest about whom your decisions ultimately serve. Good people can make poor decisions in universities, hospitals, governments, or companies. Equally, principled leadership can exist in all of those environments. The ethical responsibility travels with the individual rather than the institution.

Perhaps my years in industry strengthened rather than weakened my belief in humanistic medicine. They allowed me to appreciate healthcare from perspectives that are rarely visible inside a single hospital. I saw how engineers, software developers, regulatory experts, clinical scientists, economists, policymakers, and physicians all contribute different forms of expertise to the same objective. Modern healthcare has become far too complex for any profession to improve it alone.

That realization also changed my understanding of leadership. Leadership is less about representing one profession than about creating conditions in which very different professions can solve meaningful problems together. In many ways, that lesson reflects the central message of my book. Medicine has always been a profoundly human endeavor, yet increasingly it is also a collaborative one, and our responsibility is to ensure that scientific innovation, commercial innovation, and human values continue to move in the same direction.

Q5. Looking back at your own career, from clinical practice and academic medicine to international hospital leadership to your current global role, what is the moment or experience that most changed how you understand what patients actually need from a physician, the kind of moment that you suspect could never be fully captured in a textbook, a curriculum, or, for that matter, in an AI system? And on a personal note: is there a particular patient encounter from your years of clinical practice that you still think about today, and that shaped the convictions behind this book?

Mathias Goyen: I find it surprisingly difficult to identify a single defining moment. That is perhaps because medicine rarely changes us through dramatic events alone. More often, it changes us gradually, almost imperceptibly, through hundreds of encounters that quietly reshape how we think about illness, responsibility, and the privilege of caring for another human being.

When I was younger, I believed that patients primarily came to physicians seeking answers. Over time, I realized that many came for something more subtle. They were looking for orientation at moments when life had suddenly become uncertain. A diagnosis changes far more than a person’s health. It interrupts a biography. It changes how people think about their future, their family, their work, and sometimes even their identity. Physicians naturally focus on understanding the pathology, while patients are often trying to understand what remains possible in their lives. Those are very different questions.

That realization gradually changed my own consultations. I became less concerned with demonstrating how much I knew and more interested in understanding what the patient was actually asking. Quite often, the question spoken aloud was not the most important one. Behind a technical question about an MRI finding or a treatment option there was frequently another question that remained unspoken. Will I still be able to care for my children? Will I become dependent on others? Am I going to die? Learning to recognize those questions probably changed my practice more than any scientific publication I ever read.

For that reason, I cannot point to a single patient who shaped this book. Instead, the book represents a conversation with many patients whose names I no longer remember but whose concerns I still do. They taught me that medicine is practiced simultaneously on two levels. One level concerns disease, where science rightly guides our decisions. The other concerns the human experience of illness, where listening often matters as much as explaining. Medical school prepared me exceptionally well for the first. The second was learned almost entirely through experience.

This is also why I believe some aspects of medicine will always resist complete automation. AI may become remarkably effective at recognizing patterns, generating differential diagnoses, or summarizing scientific evidence. Those capabilities will undoubtedly improve healthcare. Yet every patient enters the consultation carrying a unique life story that gives medical facts their meaning. Two patients with identical diagnoses may require entirely different conversations because their fears, priorities, relationships, and hopes are profoundly different. Understanding that difference requires something more than information processing. It requires curiosity about another human being.

If I were to distill one lesson from my years in medicine, it would be this. Patients rarely remember every detail of what we explained. They often remember whether they felt safe while facing uncertainty. Today, I believe that helping patients feel safe while facing uncertainty may have been one of the most important responsibilities I ever had as a physician, even though it was never formally described in any curriculum I followed.

Q6. You describe healthcare systems as “drowning in bureaucracy” and structured around appointment slots and documentation requirements that consume the time meant for genuine conversation. AI is often proposed as the solution to exactly this problem through ambient documentation, automated coding, and administrative automation. But there is a real risk that the time saved by AI is simply absorbed by the system rather than returned to the patient physician relationship.

What evidence, if any, have you seen that AI driven efficiency gains in healthcare actually translate into more human time at the bedside rather than simply more throughput, and what would need to change structurally to ensure the former rather than the latter?

Mathias Goyen: This is one of the most important questions surrounding AI in healthcare because it reminds us that technology alone cannot determine how its benefits are ultimately used. Technology creates possibilities. Organizations decide whether those possibilities become reality.

There is growing evidence that ambient documentation, intelligent summarization, and administrative automation can reduce the time physicians spend interacting with computers. That is encouraging and represents meaningful progress. At the same time, I believe we should be careful not to make a logical leap that the current evidence does not yet fully support. Saving documentation time does not automatically mean that physicians spend more time with patients. In many healthcare systems, the newly available capacity is immediately redirected toward seeing more patients, completing more documentation, or fulfilling additional administrative requirements. Efficiency is created, but humanity does not necessarily increase.

This distinction is crucial because the true value of AI should not be measured simply by minutes saved. It should be measured by what those minutes become. If every efficiency gain is automatically converted into higher throughput, we may discover that physicians become more productive while patients do not feel more cared for. That would be a remarkable paradox. We would have built technology capable of giving time back to medicine without actually giving time back to the people who practice it.

I therefore believe that the successful implementation of AI is ultimately a leadership challenge rather than a technology challenge. Leaders need to decide explicitly what they want AI to achieve. Is its primary purpose to maximize productivity? To improve quality? To reduce burnout? To strengthen the physician patient relationship? These objectives overlap, yet they are not identical, and organizations that never articulate their priorities often discover that efficiency silently becomes the default objective.

This also requires us to rethink how we evaluate success. Healthcare has become exceptionally good at measuring activity. We know how many patients were seen, how many procedures were performed, and how long documentation required. We are much less sophisticated at measuring whether physicians had enough time to explain uncertainty, whether patients genuinely understood their options, or whether trust improved during the consultation. Those dimensions are more difficult to quantify, yet they may ultimately matter far more.

Perhaps the most profound opportunity offered by AI is not that it enables physicians to work faster. It is that it offers us a rare opportunity to decide what medicine should do with the time it recovers. That is not a technical question. It is an ethical and organizational one.

If we consciously return even part of that time to thoughtful conversation, shared decision making, and the human aspects of care that have gradually been crowded out by bureaucracy, AI may become one of the greatest restorations of humanism that modern medicine has experienced. If we simply use it to accelerate an already overloaded system, we should not be surprised if physicians continue to feel exhausted despite having better technology.

Q7. You write about situations where physicians cannot save everyone, where they are powerless and have no answer to a patient’s question, and about the power of silence as something that can be as comforting as words. These are precisely the situations where AI, by its nature, cannot help, it has no silence to offer, no genuine powerlessness to share with another human being. As AI takes over more of the technical and diagnostic burden, do you believe physicians will have more capacity to be present in these irreducibly human moments, or do you worry that a healthcare system optimized around AI efficiency will paradoxically squeeze out exactly the kind of presence that cannot be automated?

Mathias Goyen: I think the answer depends far less on AI than on ourselves. Technology does not decide what medicine values. We do.

There is an understandable tendency to imagine that if AI assumes more technical work, physicians will naturally have more time for the deeply human moments that accompany serious illness. I sincerely hope that proves true, yet I do not believe it is inevitable. Healthcare has a long history of converting efficiency gains into additional activity rather than additional presence. Unless we consciously choose otherwise, the same pattern could easily repeat itself.

That would be deeply unfortunate because the moments you describe are, in many ways, the essence of medicine. There are conversations in which physicians have no treatment left to offer, no reassuring certainty, and no words capable of removing another person’s suffering. Yet those encounters are not failures. Sometimes the most meaningful thing a physician contributes is simply the willingness to remain present when uncertainty, fear, or grief cannot be taken away.

One of the lessons I learned during my clinical years is that patients rarely expect physicians to solve every problem. They understand, often better than we imagine, that medicine has limits. What they hope for is that those limits are not faced alone. Presence is therefore not the absence of action. Presence is itself a form of care.

This is one reason why I hesitate whenever discussions about AI become dominated by questions of replacement. The real opportunity is not to replace physicians in the human dimensions of medicine. It is to relieve physicians of tasks that never required their uniquely human capabilities in the first place. Every administrative burden that disappears creates the possibility of another conversation. Every repetitive task that becomes automated creates the possibility of another moment of attention. Whether those possibilities become reality depends entirely on the values embedded within the healthcare system.

There is another aspect that deserves attention. Physicians themselves often struggle with silence because medical education teaches us to respond, explain, and intervene. Yet some of the most memorable consultations occur precisely when no explanation is sufficient. Sitting quietly with a patient after delivering difficult news can communicate honesty, solidarity, and respect in ways that language sometimes cannot. Those moments may appear unproductive from the perspective of operational efficiency, yet they are profoundly productive from the perspective of healing, even when cure is no longer possible.

Perhaps the ultimate purpose of AI is not to make physicians less necessary, but to allow them to become more fully what only they can be. If AI helps restore the time and emotional space for conversations that have gradually been displaced by documentation, administration, and fragmented workflows, it will have achieved something far greater than efficiency. It will have helped medicine recover an essential part of its own identity.

Whether that future emerges is not a technological question. It is a cultural choice.

Q8. Burnout among physicians is one of the most consistent findings in healthcare workforce research worldwide, and you connect it directly to the gap between what medical school promises and what the healthcare system actually delivers. As AI becomes more capable and more embedded in clinical workflows, there is a genuine debate about whether it will reduce physician burnout by removing administrative burden, or increase it by adding new layers of complexity, oversight responsibility, and the cognitive load of constantly evaluating AI generated recommendations. Based on what you are seeing across health systems globally, which direction do you believe is more likely to dominate over the next five years, and what would tip the balance one way or the other?

Mathias Goyen: I believe AI has the potential to reduce physician burnout, but only if we first become more precise about what we actually mean by burnout.

Physicians are certainly exhausted by documentation, fragmented workflows, repetitive administrative tasks, and the growing complexity of modern healthcare. AI can help address many of those burdens, and I am optimistic that it will. Intelligent documentation, decision support, and automation of routine activities can remove work that adds little professional satisfaction while consuming enormous amounts of time and attention.

Yet there is another dimension of burnout that receives less attention. Many physicians are not simply tired because they work hard. They are tired because they increasingly spend less time doing the very work that originally inspired them to enter medicine. Most young physicians do not dream of becoming experts in documentation, coding, or navigating digital systems. They choose medicine because they want to solve problems, accompany patients, and make meaningful decisions during important moments in people’s lives.

If AI merely changes the nature of administrative work while leaving physicians equally disconnected from the human purpose of their profession, I doubt burnout will improve substantially. We may create more efficient workflows without restoring professional fulfillment. Excessive workload certainly contributes to burnout. Equally important is the gradual loss of meaning that many physicians experience when they spend less and less time practicing the kind of medicine that drew them into the profession. 

This is why implementation matters so profoundly. Across healthcare systems around the world, I have seen remarkable enthusiasm for AI, yet successful implementation rarely depends on the sophistication of the algorithm alone. It depends on whether clinicians trust the technology, understand its limitations, feel appropriately involved in its introduction, and experience it as genuine support rather than additional oversight. AI should reduce cognitive burden rather than simply replacing one form of complexity with another.

I therefore believe the next five years will be determined less by technical progress than by implementation quality. Organizations that introduce AI thoughtfully, redesign workflows, invest in education, and deliberately return time to physicians will likely see meaningful improvements in professional satisfaction. Organizations that simply layer AI onto already overloaded systems may discover that physicians now carry responsibility for both their own decisions and the continuous evaluation of algorithmic recommendations, while still remaining accountable for every outcome. That would increase complexity rather than reduce it.

Perhaps the most important lesson is that burnout cannot be solved by technology alone because its origins are not purely technological. Burnout emerges when physicians gradually lose the connection between their daily work and the deeper purpose that drew them into medicine in the first place. AI can help restore that connection by removing unnecessary burdens, but it cannot create meaning on behalf of the profession. That remains our responsibility.

In the end, I remain cautiously optimistic. If we implement AI with the explicit intention of helping physicians spend more of their professional lives practicing medicine rather than managing medicine, I believe it can become one of the most important contributors to physician well being that we have seen in many years.

Q9. You suggest that medical education should teach adaptability, agility, and tolerance for ambiguity as core competencies for physicians navigating an era of technological disruption. These are qualities that are notoriously difficult to teach in a classroom and are often only developed through direct experience with uncertainty and failure. What concrete pedagogical approaches, whether from medicine or from other fields entirely, do you believe could actually cultivate these qualities in medical students, rather than simply naming them as desirable traits in a curriculum document?

Mathias Goyen: One of the greatest misconceptions in education is the belief that judgment can simply be transferred from one generation to the next through lectures. Knowledge can be taught remarkably efficiently. Judgment develops differently. It emerges through reflection on experience, through exposure to uncertainty, and through the gradual realization that many important decisions do not have perfect answers.

Medicine has traditionally rewarded certainty. Students spend years learning that there is a correct diagnosis, a correct treatment, and a correct examination answer. That approach has obvious value because medicine must remain scientifically rigorous. Yet the reality of clinical practice is often very different. Patients rarely present exactly as described in textbooks. Several reasonable treatment options may exist simultaneously. Evidence may be incomplete. Individual values may legitimately lead to different decisions. Physicians therefore need to become comfortable making thoughtful decisions even when certainty is unattainable.

I believe this can be taught, but only if medical education changes what it chooses to reward. We should spend more time discussing cases where experienced physicians disagreed respectfully, where outcomes remained uncertain despite excellent care, and where ethical dilemmas had no universally accepted solution. Reflection after difficult clinical encounters should become as normal as learning anatomy or pharmacology. Students should not only ask, “What happened?” They should also ask, “How did I think? Why did I make this decision? What uncertainty did I overlook? What would I do differently next time?” Those questions gradually cultivate professional judgment.

Some of the most valuable lessons may also come from outside medicine. Aviation has developed a remarkable culture of structured debriefing in which experienced professionals openly analyze mistakes without automatically assigning blame. Elite sports recognize that performance improves through deliberate reflection rather than repetition alone. Military leadership education acknowledges that leaders frequently make decisions with incomplete information and changing circumstances. Executive leadership increasingly emphasizes adaptability, self awareness, and the ability to learn continuously as environments evolve. Medicine can learn from all of these disciplines because uncertainty is not unique to healthcare. It is a defining characteristic of leadership itself.

AI adds another important dimension. Future physicians will increasingly practice alongside systems that generate sophisticated recommendations within seconds. Their responsibility will therefore shift further toward evaluating, interpreting, communicating, and occasionally questioning those recommendations. Medical education should prepare students for that future by encouraging intellectual humility rather than intellectual certainty. The most valuable physician will not necessarily be the one who memorizes the greatest number of facts, but the one who consistently asks thoughtful questions, recognizes the limits of available knowledge, and remains willing to revise conclusions when new evidence emerges.

Perhaps that is ultimately what adaptability means. It is not the ability to change one’s opinion easily. It is the willingness to continue learning throughout an entire professional life without losing sight of the values that make medicine a profoundly human profession.

If I could change one thing about medical education, it would be this. We should spend less time asking students whether they know the answer and more time exploring how they reached it. In the age of AI, the quality of our reasoning may become more important than the quantity of our knowledge.

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Prof. Dr. med. Mathias Goyen is a physician, radiologist, professor, author, and international healthcare executive. After many years in academic medicine and clinical practice, he served for almost fifteen years in global medical leadership at GE HealthCare, most recently as Global Chief Medical Officer for Imaging. Throughout his career, he has worked at the intersection of medicine, AI, leadership, and healthcare transformation. He is the author of What I Didn’t Learn in Medical School: Notes on Medicine, Leadership & the Human Side of Healing, which explores the human side of medicine in an age of AI. He is also Co-Founder of HelloAI, an educational initiative dedicated to responsible AI in healthcare.

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(*) What I Didn’t Learn in Medical School: Notes on Medicine, Leadership & the Human Side of Healing

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