Artificial intelligence has been part of conversations about the future of medicine for years. As a medical student, I have heard about its potential in lectures, read about its development in health care, and watched discussions about how it may change the way physicians practice. For a long time, though, it felt like something that would arrive later, after I had already learned how to be a doctor.
Then I saw a sponsored social media advertisement for a $33 application promising to help medical trainees create anesthesia plans. My first reaction was honestly curiosity. As a student preparing to apply to residency, the idea of a tool that could help organize information and support learning was exciting. But it also made me think about what it means to learn medicine in this moment.
My generation will not experience AI as something that appears after we become physicians. We will train with it from the beginning. We will have access to tools that can summarize information, recognize patterns, and potentially help guide decisions before we have spent years developing our own clinical instincts. That is both exciting and uncomfortable.
Anesthesiology has always evolved alongside technology. New tools have changed what physicians can see, anticipate, and respond to in real time. AI seems like a natural extension of that. A system that can identify subtle changes in a patient’s physiology or help anticipate problems could become incredibly valuable. And it should.
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Medicine has always advanced because physicians were willing to use better tools. The stethoscope, ultrasound, and advanced monitoring changed the way clinicians care for patients. AI has the potential to do the same. The challenge is making sure that in becoming better at using technology, we do not lose the skills that technology cannot replace.
An anesthesiologist is not just responding to numbers. A monitor can show a change in blood pressure, but it cannot understand why it happened without clinical context. A patient asking multiple questions before surgery may be looking for information, or they may be afraid. A plan that makes sense on paper may need to change when the patient in front of you is different from the one you expected. Those decisions require more than information. They require experience.
As medical students, we learn through the process of watching, questioning, trying, and reflecting. We learn why one physician chooses a different approach than another. We learn how experienced clinicians recognize when something feels different before there is an obvious crisis. Those lessons are difficult to quantify, but they are central to becoming a physician.
My concern about AI is not that it will replace doctors. It is that we may be tempted to use it before we have fully developed the ability to think independently. If a tool gives us an answer immediately, we may miss the slower but essential process of learning how to arrive at that answer ourselves. That does not mean we should avoid these technologies. It means we need to be thoughtful about how we use them.
As I prepare to enter residency, I know I will be learning alongside artificial intelligence. I hope my generation uses these tools to become more capable, more informed, and safer physicians. But I also hope we remember that medicine is not only about knowing the right answer. It is about understanding the patient, adapting when situations change, and taking responsibility for decisions when there is no perfect answer.
AI will become part of anesthesiology. The question is not whether we allow it into the operating room. The question is whether we allow it to make us better physicians while preserving the judgment and responsibility that define the profession.
This essay is cited in the KevinMD record on artificial intelligence.
Ritika Segireddy is a medical student.
