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A Giant Leap: How AI Is Transforming Healthcare and What That Means for Our Future
From the author of the New York Times bestseller The Digital Doctor comes a bold, insightful exploration of how artificial intelligence is revolutionizing healthcare—and why that matters.
Healthcare has long resisted the forces of digital disruption that have transformed nearly every other industry.
Until now.
In A Giant Leap, physician and thought leader Robert Wachter chronicles medicine’s AI awakening. Drawing on painstaking research and interviews with more than 100 pioneers at the intersection of medicine, technology, policy, and business, Wachter describes how AI can now match—and sometimes surpass—physicians in areas ranging from diagnosis to empathy.
Even as AI enters hospitals and clinics to assist with documentation, recommend treatments, interpret images, and guide surgeries, challenges remain—including hallucinations, biases, and misinformation. Yet, Wachter argues, in a healthcare system buckling under the weight of medical errors, limited access, maddening paperwork, clinician burnout, and crushing costs, AI doesn’t have to be flawless to be useful—it just needs to be better. And, if we make the right choices, it will be.
Blending clinical insight, vivid storytelling, and journalistic precision, A Giant Leap is a timeless and engaging guide to how AI is changing what it means to heal and be healed in this age of astonishing technology.
Healthcare has long resisted the forces of digital disruption that have transformed nearly every other industry.
Until now.
In A Giant Leap, physician and thought leader Robert Wachter chronicles medicine’s AI awakening. Drawing on painstaking research and interviews with more than 100 pioneers at the intersection of medicine, technology, policy, and business, Wachter describes how AI can now match—and sometimes surpass—physicians in areas ranging from diagnosis to empathy.
Even as AI enters hospitals and clinics to assist with documentation, recommend treatments, interpret images, and guide surgeries, challenges remain—including hallucinations, biases, and misinformation. Yet, Wachter argues, in a healthcare system buckling under the weight of medical errors, limited access, maddening paperwork, clinician burnout, and crushing costs, AI doesn’t have to be flawless to be useful—it just needs to be better. And, if we make the right choices, it will be.
Blending clinical insight, vivid storytelling, and journalistic precision, A Giant Leap is a timeless and engaging guide to how AI is changing what it means to heal and be healed in this age of astonishing technology.
352 pages, Kindle Edition
Published February 3, 2026
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August 26, 2026
Robert Wachter is the head of Internal Medicine at the University of California in San Francisco, which places him squarely in the center of the fight about the use of AI in medicine. He spends a lot of time listening to AI startups and a LOT of time talking to other doctors and patients. This book is a logical successor to his 2015 book about electronic health records.
What AI companies really want, more than just about anything, is access to those health records. Dozens to thousands of doctor/patient interactions per patient, multiplied by hundreds of millions of people, describing symptoms, diagnoses, treatments and outcomes. This is the diamond mine of data mining, and Oracle spent $2.35B to acquire a failing Electronic Health Record company just to get the data.
I had expected the book to come down hard against AI, but Wachter surprised me. He acknowledges that doctors use it all the time, so it makes sense to put some thought into how to use it appropriately. (A company called OpenEvidence, available only to licensed doctors and advanced medical students, had over 100 million inquiries last year. Not least because it's free to use, paid for by -- oooops -- targeted advertising. Keep moving, folks, nothing to see here.)
A random aside: 8% of health care costs in the U.S. go to doctor's pay.
The public is (justifiably) concerned about the spectre of opaque lines of code diagnosing their illness, in part because of early AI enthusiasts claiming that radiologists (people who examine x-ray images, among other things) would be eliminated by AI within five years. (Five years later, radiologists in the U.S. are in great demand and have an average salary of $550,000.)
This is not where the smart money in AI is focused. What Wachter dreams of is software automation that allows doctors to offload the unproductive work that chews up so much of their time. Wachter on AI-in-Healthcare conferences:
But Wachter is very fair and realistic, and follows this with:
What AI companies really want, more than just about anything, is access to those health records. Dozens to thousands of doctor/patient interactions per patient, multiplied by hundreds of millions of people, describing symptoms, diagnoses, treatments and outcomes. This is the diamond mine of data mining, and Oracle spent $2.35B to acquire a failing Electronic Health Record company just to get the data.
I had expected the book to come down hard against AI, but Wachter surprised me. He acknowledges that doctors use it all the time, so it makes sense to put some thought into how to use it appropriately. (A company called OpenEvidence, available only to licensed doctors and advanced medical students, had over 100 million inquiries last year. Not least because it's free to use, paid for by -- oooops -- targeted advertising. Keep moving, folks, nothing to see here.)
A random aside: 8% of health care costs in the U.S. go to doctor's pay.
The public is (justifiably) concerned about the spectre of opaque lines of code diagnosing their illness, in part because of early AI enthusiasts claiming that radiologists (people who examine x-ray images, among other things) would be eliminated by AI within five years. (Five years later, radiologists in the U.S. are in great demand and have an average salary of $550,000.)
This is not where the smart money in AI is focused. What Wachter dreams of is software automation that allows doctors to offload the unproductive work that chews up so much of their time. Wachter on AI-in-Healthcare conferences:
Imagine if you have five thousand twenty-two-year-olds that can't spell HIPAA but are absolutely convinced they an disrupt healthcare. And then you have five thousand venture capitalists that think that, if they can find the right twenty-two-year-old, they can make 100X on their investment."I can vouch for that. Every once in a while a doctor would pipe up with what seemed a very commonsense question, and the AI guys would just get a deer-in-the-headlights look because none of them had spent a day working in a hospital, for the most part.
But Wachter is very fair and realistic, and follows this with:
Of course, two things can be true at the same time. This kind of hype can make an amusing caricature, and this kind of optimistic risk-taking is needed if healthcare is ever to be truly transformed.Wachter's most important point comes in the last couple of chapters, in which he defends the idea of people continuing to study medicine. It is only through the study and practice of medicine, working with real patients, that the craft can be improved, and it ain't gonna be machines based on linguistic statistics that are going to figure these things out.
April 22, 2026
Robert Wachter is an American physician (internal medicine) and Chair of the Department of Medicine at UCSF; I previously read and quite enjoyed his 2015 book The Digital Doctor: Hope, Hype, and Harm at the Dawn of Medicine’s Computer Age. A Giant Leap conveys Wachter's cautious optimism about the future of artificial intelligence in creating positive change in medicine; it's provocative and timely though I wish Wachter had focused a bit more on my specialty (pathology), though I agree with his assessment that there are other low-hanging fruit to address first.
Further reading:
Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again by Eric Topol, MD (2019, so outdated now, but still relevant for context)
My statistics:
Book 72 for 2026
Book 2378 cumulatively
My statistics:
Book for 2026
Book cumulatively
Further reading:
Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again by Eric Topol, MD (2019, so outdated now, but still relevant for context)
My statistics:
Book 72 for 2026
Book 2378 cumulatively
My statistics:
Book for 2026
Book cumulatively
March 15, 2026
Useful overview of AI’s promises and limitations (as they currently stand) in the health care space. Helpful for my job but wouldn’t recommend it as pleasure reading
April 12, 2026
Robert Wachter is a physician at UCSF and also an author. This book, as the subtitle indicates, is about the promises and risks of using AI in healthcare. While Wachter is clearheaded about the risks, ultimately he thinks that the benefits to healthcare, now and even more in the future, outweigh the risks. Moreover, he reminds that moving too slowly in adopting new technologies can also be harmful. This reminded me of the shift in hip surgery from posterior to anterior. As a neighbor physician remarked to me, "If your doctor says that he doesn't do anterior surgery, that means he doesn't know how to do it, and you should walk out of the office." AI is already helpful at reducing the amount of burdensome paperwork imposed on physicians. In the future, it will be even more useful in interpreting tests and helping physicians come up with diagnoses. It will never be a cure-all. The need for integrated care, where physicians from different specialties communicate about a patient -- the kind of care that my husband and I get from Kaiser -- is crucial. Although Wachter reminds us that the main function of healthcare is to promote health, not provide jobs, he also believes (as I do) that doctors will always be an important part of healthcare. If their functioning is improved by collaboration with AI, as Wachter fully expects, why not? Wachter says that he will not be discussing the existential threats posed by AI, including the impact on the environment. However, I don't see how he can assess the risks and benefits without considering the existential threats. At the same time, almost every technological advance requires sources of energy. I don't think that the solution is giving up technological advance, but rather investing in sustainable energy, like wind and solar (which is already happening, despite those who want to dig, baby, dig, and who claim that climate change is a hoax. Anyone interested in the impact and promise of AI on healthcare should read this well-written, clear, and often funny book.
February 23, 2026
Not my usual genre of book to read but was highly recommended by Joanna (Midi CEO) so I thought I’d give it a go. I feel like it was as interesting as an AI healthcare book could be for me?? And I stayed pretty locked in the whole time listening to it - it was funny how much I already knew and recognized just from my day to day job. Not sure it really offered much beyond the questions I feel like we are all asking every day. But really interesting anecdotes about AI in healthcare, where it’s at, what he thinks is possible etc. Funny portion about Forward’s downfall lol…
June 14, 2026
3.75. Repetitive in places. While I do not share the level of AI confidence the author has it was a well structured book.
September 23, 2026
A good and fair overview of medicine and the consequences of AI. Leaves you feeling more hopeful with the mess that our health system is and how AI can improve tasks with human oversight.
February 28, 2026
An excellent and inspiring book. He really walks us through the ins and outs of what AI is currently doing in healthcare and what is possible in the near future.
Review of advance copy received from Netgalley
I thought it would be fitting for a book about AI to have its review written by AI—based on my own thoughts. So I provided a few bullet points and asked ChatGPT to do the job. What follows is the result. It is imperfect, distorted, and at times reads as if the AI fundamentally misunderstood me.
Yes, progress in AI is fast—astonishingly so. Every few months we are told that what failed yesterday works flawlessly today. But that is beside the point. This is only a book review. The consequences are trivial. Now imagine the same process applied to your health.
An AI that “mostly understands” you. An AI that improves with updates. An AI that gets it right—except when it doesn’t. In this case, the misunderstanding is no longer an annoyance or an academic curiosity. It is your diagnosis. Your treatment. Your life.
Mistakes in a review can be edited. Mistakes in medicine cannot.
-->
AI in Healthcare: Progress Toward the Light, or a Quiet Drift Toward Dependence?
The promise of artificial intelligence in healthcare is often framed as self-evident progress: automate routine tasks, reduce errors, and free doctors to focus on what matters most—the patient. But this optimistic narrative deserves scrutiny. When examined closely, the rise of AI in medicine raises uncomfortable questions about time, trust, responsibility, competence, and resilience. The issue is not whether AI is powerful—it clearly is—but whether increasing dependence on it is moving healthcare toward human flourishing or systemic fragility.
The first assumption worth challenging is that shifting work from doctors to AI will automatically give doctors more time for patients. History suggests otherwise. Administrative software, electronic health records, and digital reporting were all introduced with the same promise, yet many physicians today report less meaningful patient contact, not more. Time saved is rarely returned to human connection; it is often absorbed by new forms of documentation, monitoring, compliance, and productivity targets. Without structural change, AI risks becoming another efficiency tool that benefits systems and insurers more than patients.
This matters because healthcare is not merely a technical service. It is deeply personal, emotional, and grounded in trust. Human presence—eye contact, tone of voice, the ability to sit with uncertainty—cannot be replicated by machines. A diagnosis delivered by an algorithm may be statistically impressive, but trust is not built on probability alone. Patients trust doctors not only because of what they know, but because of how they listen, interpret context, and take responsibility. The more AI moves from tool to authority, the more this relational foundation is weakened. And a reasonable question follows: how much do we truly trust a machine, especially one we cannot question, confront, or hold morally accountable?
Which leads to responsibility. Machines can and do make mistakes. So do humans—but when humans err, responsibility is at least conceptually clear. With AI, accountability becomes diffuse. Is it the doctor who followed the recommendation? The hospital that deployed the system? The developer who trained the model? The insurer who mandated its use? In practice, responsibility tends to flow downward, not upward, and there is a real risk that clinicians will be pressured to defer to AI not because it is always right, but because deviating from it is legally dangerous. In such a system, critical thinking is not encouraged—it is penalized.
Proponents often argue that AI is simply better at diagnosis. In some domains, this is undeniably true. Algorithms excel at pattern recognition, such as reading ECGs or imaging scans, where even trained clinicians may struggle with ambiguity. But diagnostic accuracy is not the same as clinical excellence. The best doctors are not necessarily those who rely on the most technology, but those who integrate observation, experience, intuition, and restraint. Many exceptional clinicians practiced—and still practice—without constant digital assistance, guided by deep internalized knowledge rather than external systems.
There is also a neglected question of resilience. Imagine prolonged power outages, war, infrastructure collapse, or any scenario where electricity and networks are unavailable. These are not science fiction; they are historical realities. A healthcare system that cannot function without AI, software, or electricity is a brittle system. Reports from organizations like Doctors Without Borders in the 1980s praised doctors trained in austere conditions—such as many Polish physicians—for their ability to operate with minimal tools, improvisation, and judgment. That kind of competence is not backward; it is robust. As we move toward AI dependence, we risk losing skills that cannot be quickly relearned when systems fail.
So are we moving toward the light or toward doom? The honest answer is: both are possible. AI can be an extraordinary assistant—augmenting perception, reducing cognitive load, and improving outcomes—if it remains a tool under human authority. But if it becomes a crutch, an arbiter, or a shield against responsibility, it may erode the very qualities that make medicine humane, ethical, and resilient.
Progress in healthcare should not be measured by how much intelligence we outsource, but by how well we preserve judgment, accountability, and human connection while using technology wisely. The danger is not AI itself. The danger is forgetting how to practice medicine without it.
Yes, progress in AI is fast—astonishingly so. Every few months we are told that what failed yesterday works flawlessly today. But that is beside the point. This is only a book review. The consequences are trivial. Now imagine the same process applied to your health.
An AI that “mostly understands” you. An AI that improves with updates. An AI that gets it right—except when it doesn’t. In this case, the misunderstanding is no longer an annoyance or an academic curiosity. It is your diagnosis. Your treatment. Your life.
Mistakes in a review can be edited. Mistakes in medicine cannot.
-->
AI in Healthcare: Progress Toward the Light, or a Quiet Drift Toward Dependence?
The promise of artificial intelligence in healthcare is often framed as self-evident progress: automate routine tasks, reduce errors, and free doctors to focus on what matters most—the patient. But this optimistic narrative deserves scrutiny. When examined closely, the rise of AI in medicine raises uncomfortable questions about time, trust, responsibility, competence, and resilience. The issue is not whether AI is powerful—it clearly is—but whether increasing dependence on it is moving healthcare toward human flourishing or systemic fragility.
The first assumption worth challenging is that shifting work from doctors to AI will automatically give doctors more time for patients. History suggests otherwise. Administrative software, electronic health records, and digital reporting were all introduced with the same promise, yet many physicians today report less meaningful patient contact, not more. Time saved is rarely returned to human connection; it is often absorbed by new forms of documentation, monitoring, compliance, and productivity targets. Without structural change, AI risks becoming another efficiency tool that benefits systems and insurers more than patients.
This matters because healthcare is not merely a technical service. It is deeply personal, emotional, and grounded in trust. Human presence—eye contact, tone of voice, the ability to sit with uncertainty—cannot be replicated by machines. A diagnosis delivered by an algorithm may be statistically impressive, but trust is not built on probability alone. Patients trust doctors not only because of what they know, but because of how they listen, interpret context, and take responsibility. The more AI moves from tool to authority, the more this relational foundation is weakened. And a reasonable question follows: how much do we truly trust a machine, especially one we cannot question, confront, or hold morally accountable?
Which leads to responsibility. Machines can and do make mistakes. So do humans—but when humans err, responsibility is at least conceptually clear. With AI, accountability becomes diffuse. Is it the doctor who followed the recommendation? The hospital that deployed the system? The developer who trained the model? The insurer who mandated its use? In practice, responsibility tends to flow downward, not upward, and there is a real risk that clinicians will be pressured to defer to AI not because it is always right, but because deviating from it is legally dangerous. In such a system, critical thinking is not encouraged—it is penalized.
Proponents often argue that AI is simply better at diagnosis. In some domains, this is undeniably true. Algorithms excel at pattern recognition, such as reading ECGs or imaging scans, where even trained clinicians may struggle with ambiguity. But diagnostic accuracy is not the same as clinical excellence. The best doctors are not necessarily those who rely on the most technology, but those who integrate observation, experience, intuition, and restraint. Many exceptional clinicians practiced—and still practice—without constant digital assistance, guided by deep internalized knowledge rather than external systems.
There is also a neglected question of resilience. Imagine prolonged power outages, war, infrastructure collapse, or any scenario where electricity and networks are unavailable. These are not science fiction; they are historical realities. A healthcare system that cannot function without AI, software, or electricity is a brittle system. Reports from organizations like Doctors Without Borders in the 1980s praised doctors trained in austere conditions—such as many Polish physicians—for their ability to operate with minimal tools, improvisation, and judgment. That kind of competence is not backward; it is robust. As we move toward AI dependence, we risk losing skills that cannot be quickly relearned when systems fail.
So are we moving toward the light or toward doom? The honest answer is: both are possible. AI can be an extraordinary assistant—augmenting perception, reducing cognitive load, and improving outcomes—if it remains a tool under human authority. But if it becomes a crutch, an arbiter, or a shield against responsibility, it may erode the very qualities that make medicine humane, ethical, and resilient.
Progress in healthcare should not be measured by how much intelligence we outsource, but by how well we preserve judgment, accountability, and human connection while using technology wisely. The danger is not AI itself. The danger is forgetting how to practice medicine without it.
May 19, 2026
A very balanced and cautiously optimistic book about how recent developments in AI have been affecting the practice of medicine in America.
I was about to give it a five until I read the following paragraph on page 270:
" I could easily see how AI could improve the experience of patients in the hospital. Food could be delivered by robots, as could medications. The confused patient might have a robotic sitter by her bedside, providing reassurance, conversation, and maybe even a gentle nudge if she tried to climb out of bed. Vital signs could be taken by sensors, transmitted automatically to the EHR, and analyzed for worrisome patterns ... The dreaded nurse call button --which often feels like bridge to nowhere--would be replaced by a chatbot that could address many of the patient's need and questions, particularly if linked to a multitasking robot. But there would still need to be a human nurse to comfort the patient, talk to families,get the patient to the commode, assess changes in clinical status, and respond to emergencies." (italics mine)
For one thing, taking vital signs (and heart functions, lab results such as glucose levels, etc), sending them to the EHR, and having them analyzed is nothing new.
But I can imagine the experience: admitted to a hospital bed where a robot scans my arm and starts an IV, and sets the flow rate on my pump and educates me about my medication. Then the medication makes me vaguely nauseous and I don't feel like eating. Another robot brings in my tray and sets it at my bedside. After an interval, the robot returns, extends its camera arm to takes photo of my tray and record what percentages and my different food items I have eaten, without questioning me about why I did not eat.
The patient across the hall from me is in a delirium is calling out for help and tugging on her urinary catheter, while her bedside robot is calmly cautioning her not to do that. Ignoring the robot, she starts to get out of bed and is "gently nudged" back. (Trying to envision this.)
Down the hall the medication robot is delivering medication to a patient with hand tremors. The robot arm hand the patient the pills and he immediately spills them. The robot sends a message to the EHR that the crucial medication has not been swallowed.
The post op robot is travelling from room to room, reminding post op patients do their deep breathing exercises or use their incentive spirometers, which now have sensors to send compliance data to the EHR. They also remind patients to turn themselves from side to side periodically, and "gently nudge" them over if they don't.
A patient with new ostomy is calling the call-light bot, and reporting a leak. "I'm sorry, I didn't understand that.," the bot replies, "Did you say,"My back is leaking?'"
I call for something to relieve my nausea, and a the IV robot comes to the room and engages a syringe onto the IV pump and injects a medication, informing me that the call-light bot will call me in 30 minutes to see if my nausea has subsided.
I relax in the bed and smile, reminding myself how much better this hospitalization experience is than in the old days, when humans had to perform these tasks, but also knowing that if I need to use the commode, a human nurse will be there to help me. :)
(But, anyway, it really was a good book, and I would recommend that anyone read it.)
I was about to give it a five until I read the following paragraph on page 270:
" I could easily see how AI could improve the experience of patients in the hospital. Food could be delivered by robots, as could medications. The confused patient might have a robotic sitter by her bedside, providing reassurance, conversation, and maybe even a gentle nudge if she tried to climb out of bed. Vital signs could be taken by sensors, transmitted automatically to the EHR, and analyzed for worrisome patterns ... The dreaded nurse call button --which often feels like bridge to nowhere--would be replaced by a chatbot that could address many of the patient's need and questions, particularly if linked to a multitasking robot. But there would still need to be a human nurse to comfort the patient, talk to families,get the patient to the commode, assess changes in clinical status, and respond to emergencies." (italics mine)
For one thing, taking vital signs (and heart functions, lab results such as glucose levels, etc), sending them to the EHR, and having them analyzed is nothing new.
But I can imagine the experience: admitted to a hospital bed where a robot scans my arm and starts an IV, and sets the flow rate on my pump and educates me about my medication. Then the medication makes me vaguely nauseous and I don't feel like eating. Another robot brings in my tray and sets it at my bedside. After an interval, the robot returns, extends its camera arm to takes photo of my tray and record what percentages and my different food items I have eaten, without questioning me about why I did not eat.
The patient across the hall from me is in a delirium is calling out for help and tugging on her urinary catheter, while her bedside robot is calmly cautioning her not to do that. Ignoring the robot, she starts to get out of bed and is "gently nudged" back. (Trying to envision this.)
Down the hall the medication robot is delivering medication to a patient with hand tremors. The robot arm hand the patient the pills and he immediately spills them. The robot sends a message to the EHR that the crucial medication has not been swallowed.
The post op robot is travelling from room to room, reminding post op patients do their deep breathing exercises or use their incentive spirometers, which now have sensors to send compliance data to the EHR. They also remind patients to turn themselves from side to side periodically, and "gently nudge" them over if they don't.
A patient with new ostomy is calling the call-light bot, and reporting a leak. "I'm sorry, I didn't understand that.," the bot replies, "Did you say,"My back is leaking?'"
I call for something to relieve my nausea, and a the IV robot comes to the room and engages a syringe onto the IV pump and injects a medication, informing me that the call-light bot will call me in 30 minutes to see if my nausea has subsided.
I relax in the bed and smile, reminding myself how much better this hospitalization experience is than in the old days, when humans had to perform these tasks, but also knowing that if I need to use the commode, a human nurse will be there to help me. :)
(But, anyway, it really was a good book, and I would recommend that anyone read it.)
March 30, 2026
The latest wave of AI developments, broadly collected under the term agentic AI, frames the central question of where exactly we want the human in the loop. The lightning fast adaptation to generative AI, through LLMs like ChatGPt, Gemini and Claude, have strengthened confidence in the possibilites of AI, and introduced the deskilling of traditional governance tools we use. Whether you are a doomer or a bloomer, the effects are gigantic. And yet the largest impact is yet to come. Agentic AI reasons that integration of workflows into a singular infrastructure will transform the decision-making balance from humans to our trained entity. We've been sold the idea the AI revoltion is a fait accompoli - both doomers and bloomers alike will be caught in it's exhorable force.
Healthcare seems like highly probalistic sector to imagine positive outcomes from the AI revolution. The digitial scribes, summarization tools, pre-authorization coding tools, machine-led radiology screenings, and communication engines are already changing the patient/physician relationship. As Robert Wachter points out, the scene has been dismal. Doctors swimming in paperwork are not able to optimize for relationship building with clients. Burnout is high. Patient load is high. And medical errors remain significant and costly in terms of death statistics and malpractice lawsuits.
"A Giant Leap" starts where the digital revolution in healthcare begins. The build out of a data infrastructure for EHR (electronic healthcare records), supported by the stimulus spending after the 2008 financial recession, paved the way for this AI revolution. Wachter looks at some of the most transformational technologies - such as the Hippocratic AI. The vision is not on the immediate issues facing LLMs, like hallucinations, but on the larger value questions. How do we prioritize care in a way that maintains our humanness? How do we train future physicians - to utilize the tools or to emphasis the problem-solving and rote memorization? How does the AI toolset impact the advesarial relationship of payers and providers?
There are some really excellent pieces within here. The story about the Mayo clinic and the "zebra" cases was fascinating. The discussion on the EHR management systems like Epic and Oracle, and their role in access to patient training data was also interesting. Behind the bureacracies and dianostic codes are real people facing the changes of their bodies. What can be more interesting than building a healthcare system that actually makes people's lives better.
This is a really excellent read that pulls in technical details when necessary, is ultimately a very human story about the future of healthcare. There is so much to cover here, it can seem overwhelming at first. Fortunately, Wachter is a great storyteller and has a way of pulling the abstract AI ideas into a very readable format. I also, think the final chapter "On Being a Doctor in the Age of AI" holds up as it's own essay. Nothing makes us more vulnerable than our health. The financial and political issues around healthcare can make these experiences very painful for us too. "A Giant Leap" gives us a roadmap, navigating a future healthcare system worthy of our collective investment.
Healthcare seems like highly probalistic sector to imagine positive outcomes from the AI revolution. The digitial scribes, summarization tools, pre-authorization coding tools, machine-led radiology screenings, and communication engines are already changing the patient/physician relationship. As Robert Wachter points out, the scene has been dismal. Doctors swimming in paperwork are not able to optimize for relationship building with clients. Burnout is high. Patient load is high. And medical errors remain significant and costly in terms of death statistics and malpractice lawsuits.
"A Giant Leap" starts where the digital revolution in healthcare begins. The build out of a data infrastructure for EHR (electronic healthcare records), supported by the stimulus spending after the 2008 financial recession, paved the way for this AI revolution. Wachter looks at some of the most transformational technologies - such as the Hippocratic AI. The vision is not on the immediate issues facing LLMs, like hallucinations, but on the larger value questions. How do we prioritize care in a way that maintains our humanness? How do we train future physicians - to utilize the tools or to emphasis the problem-solving and rote memorization? How does the AI toolset impact the advesarial relationship of payers and providers?
There are some really excellent pieces within here. The story about the Mayo clinic and the "zebra" cases was fascinating. The discussion on the EHR management systems like Epic and Oracle, and their role in access to patient training data was also interesting. Behind the bureacracies and dianostic codes are real people facing the changes of their bodies. What can be more interesting than building a healthcare system that actually makes people's lives better.
This is a really excellent read that pulls in technical details when necessary, is ultimately a very human story about the future of healthcare. There is so much to cover here, it can seem overwhelming at first. Fortunately, Wachter is a great storyteller and has a way of pulling the abstract AI ideas into a very readable format. I also, think the final chapter "On Being a Doctor in the Age of AI" holds up as it's own essay. Nothing makes us more vulnerable than our health. The financial and political issues around healthcare can make these experiences very painful for us too. "A Giant Leap" gives us a roadmap, navigating a future healthcare system worthy of our collective investment.
May 13, 2026
I became a Bob Wachter super fan during the pandemic. He's an upbeat and extremely knowledgeable academic physician (he coined the term "hospitalist") who leads the department of medicine at world-renowned UCSF. I appreciated his numbered "Covid Chronicles" Tweet threads back when both Covid and Twitter were a thing. He also did a stint as the host of the "In the Bubble" Covid podcast. Whether podcasting or Tweeting, Bob delivered informative, accessible, fact-based medical updates that made me feel safer and less alone, even in the darkest days when the news was always bad.
I felt a similar sense of informed optimism reading "A Giant Leap" his most recent book on the potentials of AI to improve healthcare, especially its role taking the piles of administrative work off doctors' plates. Bob is bullish on AI, as both a doctor and an acknowledged investor and/or adviser involved in several up-and-coming startups #bayarea #alwayshustling But he is mostly clear-eyed about the challenges and possible payoffs. One thing he emphasized again and again from his perch at one of the premier teaching hospitals in the country is how the demand for healthcare will continue to exceed supply as the decades tick by. This real, very practical problem can't fully be solved by AI, but there's a lot of potential, which he spends most of the book examining from multiple angles.
This was both a peek into AI in medicine, both pre-ChatGPT and now, and AI in general. Many of the questions facing healthcare also face fields like education, or straight-up overlap, as with AI's role in the education of doctors. The fears of de-skilling and consequences of not building one's own knowledge base before using AI are as real in medicine as in K-12 or higher ed. And just as in the education field there is a lot of hand waving about how "eventually" we'll figure out the proper balance, along with hand wringing about what we may lose in the process. The questions about whether and how soon AI can ease the crushing burdens faced by the primary care system are more concrete, but remain mostly in the still-foggy future. Help around the edges isn't nothing. But AI scribes, disease-spotting algorithms and billing services are where the field is now. Bob predicts a greater role for AI in clinical settings in "10 to 20 years." We shall see!
I always feel calmer and more informed after reading Bob, and if you're interested in this topic, I predict you will, too, regardless of how you feel about AI in medicine or anywhere else.
I felt a similar sense of informed optimism reading "A Giant Leap" his most recent book on the potentials of AI to improve healthcare, especially its role taking the piles of administrative work off doctors' plates. Bob is bullish on AI, as both a doctor and an acknowledged investor and/or adviser involved in several up-and-coming startups #bayarea #alwayshustling But he is mostly clear-eyed about the challenges and possible payoffs. One thing he emphasized again and again from his perch at one of the premier teaching hospitals in the country is how the demand for healthcare will continue to exceed supply as the decades tick by. This real, very practical problem can't fully be solved by AI, but there's a lot of potential, which he spends most of the book examining from multiple angles.
This was both a peek into AI in medicine, both pre-ChatGPT and now, and AI in general. Many of the questions facing healthcare also face fields like education, or straight-up overlap, as with AI's role in the education of doctors. The fears of de-skilling and consequences of not building one's own knowledge base before using AI are as real in medicine as in K-12 or higher ed. And just as in the education field there is a lot of hand waving about how "eventually" we'll figure out the proper balance, along with hand wringing about what we may lose in the process. The questions about whether and how soon AI can ease the crushing burdens faced by the primary care system are more concrete, but remain mostly in the still-foggy future. Help around the edges isn't nothing. But AI scribes, disease-spotting algorithms and billing services are where the field is now. Bob predicts a greater role for AI in clinical settings in "10 to 20 years." We shall see!
I always feel calmer and more informed after reading Bob, and if you're interested in this topic, I predict you will, too, regardless of how you feel about AI in medicine or anywhere else.
June 30, 2026
There is no doubt that generative AI is a disruptive technology that will continue to have impacts in the coming years if not decades. Representing one-fifth of the American economy, healthcare is one area where AI has perhaps the most promise to do good. Since much of healthcare runs on textual material, generative AI's ability to process material and respond appropriately brings a huge "wow" factor. UCSF clinician and informaticist Robert Wachter brings those ideas to light and to critical scrutiny as he helps us see pathways to our future.
Of course, any disruptive change has the potential to cause problems, and AI fits in that bucket. Wachter identifies areas that we must watch out for - like whether monopolies will stifle innovation or whether human reviewers (so-called humans in the loop) will do their job adequately without succumbing to fatigue. He carefully identifies many areas where we much give close attention.
Not an absolute critic of the technology, he sees that moving too slowly poses a greater risk than moving too quickly. AI presents opportunities that must be seized to benefit patient care in the nearer term. Only scoffing at the risks will likely cost lives in the long run and even in the short run. In discussing possible job losses in healthcare, he emphasizes that healthcare, above all, is about patient health, not a nice-paying job. That has to remain our north star.
Many audiences will be attracted to this book. Anyone interested in AI's future in clinical medicine (which should be just about everyone in the clinical enterprise) can benefit from the practical opportunities Wachter identifies. Software pioneers can learn about where to direct their development efforts so as to receive a better reception in the healthcare industry. Institutional leaders can learn about new, innovative companies, like Hippocratic AI, and how they are positioning themselves in this new era. This work covers a supremely interesting issue and covers it well enough so that every angle is examined. Although many AI books will come and go with the excitement of the field, this one has real staying potential for a long time to come.
Of course, any disruptive change has the potential to cause problems, and AI fits in that bucket. Wachter identifies areas that we must watch out for - like whether monopolies will stifle innovation or whether human reviewers (so-called humans in the loop) will do their job adequately without succumbing to fatigue. He carefully identifies many areas where we much give close attention.
Not an absolute critic of the technology, he sees that moving too slowly poses a greater risk than moving too quickly. AI presents opportunities that must be seized to benefit patient care in the nearer term. Only scoffing at the risks will likely cost lives in the long run and even in the short run. In discussing possible job losses in healthcare, he emphasizes that healthcare, above all, is about patient health, not a nice-paying job. That has to remain our north star.
Many audiences will be attracted to this book. Anyone interested in AI's future in clinical medicine (which should be just about everyone in the clinical enterprise) can benefit from the practical opportunities Wachter identifies. Software pioneers can learn about where to direct their development efforts so as to receive a better reception in the healthcare industry. Institutional leaders can learn about new, innovative companies, like Hippocratic AI, and how they are positioning themselves in this new era. This work covers a supremely interesting issue and covers it well enough so that every angle is examined. Although many AI books will come and go with the excitement of the field, this one has real staying potential for a long time to come.
August 16, 2025
A Giant Leap : How AI is transforming healthcare and what that means for our future by Robert Wachter M.D. is a fascinating and informative read, and one that gives a realistic overview of the topic in pragmatic terms without resorting to hyperbole or setting unrealistic expectations. While the use of AI in the medical field, as in so many others, is controversial, it is not going to be possible to put the genie back into the bottle, the technology is out there and in use so the best we can strive for is to ensure that it is used ethically and responsibly.
As a practicing doctor who also works in academia the author examines the use of the technology in his current day to day practice as well as touching on how the rapidly evolving tech will require changes to the way doctors and other medical professionals are trained, after all any tool, including AI is only as useful as the person using it is skilled. The author is very aware of the concerns and hesitation from both medical professionals and the general public and does his best to explain how the weaknesses in the technology evolve and how they can be prevented in the future, and generally speaks in favour of a model where AI is not used to replace clinical staff but rather to eliminate some of the more routine tasks and administrative burdens they face, freeing up more time for patient focussed care. The balance between autonomous AI based care and human oversight is a fine line and one that is bound to shift as the technology develops and its use becomes more widespread and I found much of the discussion of the topic in this book enlightening and thought provoking, overall it left me a little more hopeful and much better informed about the issue.
I read and reviewed an ARC courtesy of NetGalley and the author, all opinions are my own.
As a practicing doctor who also works in academia the author examines the use of the technology in his current day to day practice as well as touching on how the rapidly evolving tech will require changes to the way doctors and other medical professionals are trained, after all any tool, including AI is only as useful as the person using it is skilled. The author is very aware of the concerns and hesitation from both medical professionals and the general public and does his best to explain how the weaknesses in the technology evolve and how they can be prevented in the future, and generally speaks in favour of a model where AI is not used to replace clinical staff but rather to eliminate some of the more routine tasks and administrative burdens they face, freeing up more time for patient focussed care. The balance between autonomous AI based care and human oversight is a fine line and one that is bound to shift as the technology develops and its use becomes more widespread and I found much of the discussion of the topic in this book enlightening and thought provoking, overall it left me a little more hopeful and much better informed about the issue.
I read and reviewed an ARC courtesy of NetGalley and the author, all opinions are my own.
March 27, 2026
A great read if you're curious about how AI is reshaping healthcare. Wachter isn't a newcomer to this space as he's served as a medical advisor to numerous healthcare companies and spent years studying how digital changes like EHRs and patient portals have transformed medicine for good and ill. He's a pretty sober observer I would say. Very clear-eyed about what excites him, what worries him, and what he thinks is overhyped. The thing he's most eager for AI to tackle is the administrative bloat suffocating doctors and nurses today. Some of his stats about how long physicians spend answering inbox messages are mind-blowing (and, as a professor myself, painfully relatable). Beyond that, he's genuinely excited about AI empowering both doctors and patients with better explanations, clearer options, and more personalized care. His biggest fear, though, isn't hallucinations, and that's where the book gets interesting. Despite all the headlines, he thinks hallucinations are bugs that are being fixed (my own experience tracks with this). What actually keeps him up at night is AI as a misinformation machine, telling people what they want to hear or actively lying to them. He's also skeptical about some of the grander promises floating around Silicon Valley. People already know they should sleep more, eat better, and exercise. Is a personalized AI health coach really going to change that? He's doubtful. And despite watching AI get frighteningly capable, he doesn't think it's going to replace actual physicians anytime soon. As someone who is getting more serious about his health, I found this book really helpful knowing what is happening right now and what might be around the corner.
November 28, 2025
I have been using ChatGPT for simple wellness queries but I have always wondered how much trust I could put in it in terms of comprehensiveness, reliability, and medical integrity. A Giant Leap made me excited about future possibilities in the medical realm while also grounding me in today’s reality.
A Giant Leap strikes a balance between overhyped optimism/total reliance on AI and doomsday fears/conspiracy theories. The potential for generative AI to not only pore through thousands of medical content on the web in seconds, but also to analyze, iterate, interpret, diagnose, and even recommend several treatment options is clear. Dr. Wachter, however, tempers this optimism with stories that show it is not yet at a point where medical diagnosis and treatment recommendations can be fully delegated to AI without physicians in the loop.
Dr. Wachter succinctly summarized his thoughts on AI: “True transformation will emerge through AI’s ability to help diagnose illnesses, recommend treatments, coordinate care, facilitate precision medicine, and empower patients with self-management tools—not from solving important but relatively small-bore problems like documentation and prior auths.” I guess the only question left is WHEN.
Personally, I think it will be challenging to get humans to completely trust a non-human when it comes to the health of loved ones. I think it will take longer and many more success stories before AI earns the complete trust of patients. I can see a day when we would live in a world where physicians and medical staff interact closely with AI to give patients holistic, comprehensive, and safe medical care. But replacing physicians and medical staff totally? Not just yet.
This book is great reading for anyone in the healthcare industry, interested in tech (specifically AI), or even considering investing in AI platforms.
Thank you to Netgalley, Dr. Wachter, and Portfolio for this ARC. All opinions here are my own.
A Giant Leap strikes a balance between overhyped optimism/total reliance on AI and doomsday fears/conspiracy theories. The potential for generative AI to not only pore through thousands of medical content on the web in seconds, but also to analyze, iterate, interpret, diagnose, and even recommend several treatment options is clear. Dr. Wachter, however, tempers this optimism with stories that show it is not yet at a point where medical diagnosis and treatment recommendations can be fully delegated to AI without physicians in the loop.
Dr. Wachter succinctly summarized his thoughts on AI: “True transformation will emerge through AI’s ability to help diagnose illnesses, recommend treatments, coordinate care, facilitate precision medicine, and empower patients with self-management tools—not from solving important but relatively small-bore problems like documentation and prior auths.” I guess the only question left is WHEN.
Personally, I think it will be challenging to get humans to completely trust a non-human when it comes to the health of loved ones. I think it will take longer and many more success stories before AI earns the complete trust of patients. I can see a day when we would live in a world where physicians and medical staff interact closely with AI to give patients holistic, comprehensive, and safe medical care. But replacing physicians and medical staff totally? Not just yet.
This book is great reading for anyone in the healthcare industry, interested in tech (specifically AI), or even considering investing in AI platforms.
Thank you to Netgalley, Dr. Wachter, and Portfolio for this ARC. All opinions here are my own.
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March 19, 2026Wachter offers an analysis seasoned with wisdom rather than hype. Rarely does a technology come along poised to be as disruptive as artificial intelligence, and his thoughtful, measured predictions are a welcome antidote to the breathless coverage AI typically receives. I expect this book to have enduring value even as the capabilities of AI evolve year over year.
I still can’t figure out where I stand on this topic. The use cases for improving medical care are compelling — I'm particularly excited about AI's potential to restore the relational aspects of medicine, such as digital scribes that free doctors to turn away from their screens and back toward their patients. But medicine also has a long track record of adopting transformative technologies that, over time, simply become the standard of care. Minimally invasive robotic surgery, biologics, CT and MRI scans, mRNA vaccines — these were once revolutionary and are now commonplace. Looking back, artificial intelligence may prove to be another step in our upward trajectory, rather than the giant leap its proponents envision.
My bold prediction: GLP-1 medications and their successors will be seen as the more significant medical innovation of this decade. I would be glad to be proven wrong. But so far, I don't see AI creating new drug classes or running large clinical trials. It may eventually sift novel insights from the cacophony of data buried in our EHRs — but until then, I see a useful new tool, and perhaps nothing more.
I still can’t figure out where I stand on this topic. The use cases for improving medical care are compelling — I'm particularly excited about AI's potential to restore the relational aspects of medicine, such as digital scribes that free doctors to turn away from their screens and back toward their patients. But medicine also has a long track record of adopting transformative technologies that, over time, simply become the standard of care. Minimally invasive robotic surgery, biologics, CT and MRI scans, mRNA vaccines — these were once revolutionary and are now commonplace. Looking back, artificial intelligence may prove to be another step in our upward trajectory, rather than the giant leap its proponents envision.
My bold prediction: GLP-1 medications and their successors will be seen as the more significant medical innovation of this decade. I would be glad to be proven wrong. But so far, I don't see AI creating new drug classes or running large clinical trials. It may eventually sift novel insights from the cacophony of data buried in our EHRs — but until then, I see a useful new tool, and perhaps nothing more.
July 13, 2026
The author of “A Giant Leap,” Dr. Robert Wachter is Department Chair of Medicine at the University of CA San Francisco and a member of the National Academy of Medicine. He is the author of a book published in 2015 called “The Digital Doctor: Hope, Hype, and Harm at the Dawn of Medicine’s Computer Age.”
This book is about the promises of using AI in healthcare as well as the risks. Dr. Wachter is certainly cognizant of the risks, and provides some examples of AI mistakes, but he believes that overall, the benefits of AI to healthcare far outweigh the risks. As always, the focus of healthcare is to promote health not jobs. While AI can make a doctor’s job more efficient, provide more insights into possible treatment, help interpret various diagnostic tests, and streamline mundane jobs like record keeping and sharing electronic health records (EHRs), doctors will never be completely replaced by AI. In fact, the best medical outcomes usually occur when skilled physicians use assistive technology like AI to provide insights regarding the treatment of patients.
Electronic Health Records have long since replaced manilla file folders of doctor’s notes and discussions between doctors and patients in an office visit are usually recorded during the office visit and summarized by AI promptly afterwards. However, one area that has not yet been taken over by AI is emails sent to doctors in the patient portal. Perhaps that will happen in the future.
Very interesting book.
This book is about the promises of using AI in healthcare as well as the risks. Dr. Wachter is certainly cognizant of the risks, and provides some examples of AI mistakes, but he believes that overall, the benefits of AI to healthcare far outweigh the risks. As always, the focus of healthcare is to promote health not jobs. While AI can make a doctor’s job more efficient, provide more insights into possible treatment, help interpret various diagnostic tests, and streamline mundane jobs like record keeping and sharing electronic health records (EHRs), doctors will never be completely replaced by AI. In fact, the best medical outcomes usually occur when skilled physicians use assistive technology like AI to provide insights regarding the treatment of patients.
Electronic Health Records have long since replaced manilla file folders of doctor’s notes and discussions between doctors and patients in an office visit are usually recorded during the office visit and summarized by AI promptly afterwards. However, one area that has not yet been taken over by AI is emails sent to doctors in the patient portal. Perhaps that will happen in the future.
Very interesting book.
October 9, 2026
A Giant Leap — Robert Wachter
An insightful and thought-provoking exploration of the opportunities and challenges of AI in healthcare. This book was recommended to me by a colleague, and I'm glad I picked it up.
Working in healthcare quality and patient safety, many of the opportunities and constraints Wachter discusses were familiar to me. What I especially appreciated, though, was the depth he brought to the subject, especially his exploration of the early evolution of AI in healthcare, the systems, approaches and industry leaders that shaped its development.
Wachter draws on decades of experience as a frontline clinician, educator and adviser to industry, bringing valuable perspectives alongside wonderful anecdotes and real experiences from patients and clinicians.
I listened to the audiobook, narrated by Wachter himself, and would highly recommend this format. He's a clear and engaging speaker, and hearing his own voice added nuance and colour to the narrative.
My only minor criticisms were that some themes felt a little repetitive, and the book is understandably very US-centric. Working in a European healthcare context, certain aspects felt less directly relevant, although the broader lessons are certainly transferable.
Overall, a worthwhile listen that offers an understanding of how we arrived at this point in healthcare AI and a thoughtful examination of where we might be heading. I haven't yet read Wachter's earlier book, The Digital Doctor, but this has certainly inspired me to pick it up!
An insightful and thought-provoking exploration of the opportunities and challenges of AI in healthcare. This book was recommended to me by a colleague, and I'm glad I picked it up.
Working in healthcare quality and patient safety, many of the opportunities and constraints Wachter discusses were familiar to me. What I especially appreciated, though, was the depth he brought to the subject, especially his exploration of the early evolution of AI in healthcare, the systems, approaches and industry leaders that shaped its development.
Wachter draws on decades of experience as a frontline clinician, educator and adviser to industry, bringing valuable perspectives alongside wonderful anecdotes and real experiences from patients and clinicians.
I listened to the audiobook, narrated by Wachter himself, and would highly recommend this format. He's a clear and engaging speaker, and hearing his own voice added nuance and colour to the narrative.
My only minor criticisms were that some themes felt a little repetitive, and the book is understandably very US-centric. Working in a European healthcare context, certain aspects felt less directly relevant, although the broader lessons are certainly transferable.
Overall, a worthwhile listen that offers an understanding of how we arrived at this point in healthcare AI and a thoughtful examination of where we might be heading. I haven't yet read Wachter's earlier book, The Digital Doctor, but this has certainly inspired me to pick it up!
August 30, 2026
Read this on Kindle and thought this was an excellent primer on how AI is transforming healthcare, especially for anyone already working in the space. Dr. Wachter starts by walking through how healthcare got into its current mess, the information overload, the record burnout, and the financial bloat that has built up over decades. From there he surveys the health AI landscape, highlighting the companies and use cases leading the charge across care delivery, ambient scribes, clinical decision support, and administrative automation. I will admit, there is some bias on which companies were highlighted here, but he's transparent about his affiliations and potential conflict of interests throughout the book.
There is a real, balanced look at which use cases are actually ripe for AI success right now versus which ones are further out, plus a clear eyed section on the regulatory, security, and privacy guardrails needed to keep patients safe. As someone who builds product in health AI, a lot of this validated what I have already seen and read, but it was also useful to see it organized into one coherent narrative.
The writing itself is easy to get through. Wachter is not dense or overly technical, and he explains complex concepts in a practical, digestible way without dumbing them down. For anyone working in or curious about health AI, this is a must read. It gives you both the optimism and the caution needed to think clearly about where this industry is headed.
There is a real, balanced look at which use cases are actually ripe for AI success right now versus which ones are further out, plus a clear eyed section on the regulatory, security, and privacy guardrails needed to keep patients safe. As someone who builds product in health AI, a lot of this validated what I have already seen and read, but it was also useful to see it organized into one coherent narrative.
The writing itself is easy to get through. Wachter is not dense or overly technical, and he explains complex concepts in a practical, digestible way without dumbing them down. For anyone working in or curious about health AI, this is a must read. It gives you both the optimism and the caution needed to think clearly about where this industry is headed.
April 19, 2026
A Giant Leap by Robert M. Wachter delivers a rigorous and timely examination of artificial intelligence’s integration into modern healthcare systems. Grounded in extensive interviews and clinical insight, the book frames AI not as a distant innovation but as an active force already reshaping diagnostics, decision-making, and patient interaction.
What distinguishes this work is its balanced treatment of both capability and constraint. Wachter does not overstate AI’s promise; instead, he contextualizes its value within the imperfections of existing healthcare systems, arguing persuasively that incremental improvement at scale can still yield transformative outcomes. This pragmatic framing elevates the discussion beyond hype into actionable relevance.
The book ultimately functions as both a strategic lens and a field guide for understanding the future of medicine. By connecting technological advancement with systemic inefficiencies, burnout, cost, access, and error, it positions AI as a necessary evolution rather than an optional enhancement.
What distinguishes this work is its balanced treatment of both capability and constraint. Wachter does not overstate AI’s promise; instead, he contextualizes its value within the imperfections of existing healthcare systems, arguing persuasively that incremental improvement at scale can still yield transformative outcomes. This pragmatic framing elevates the discussion beyond hype into actionable relevance.
The book ultimately functions as both a strategic lens and a field guide for understanding the future of medicine. By connecting technological advancement with systemic inefficiencies, burnout, cost, access, and error, it positions AI as a necessary evolution rather than an optional enhancement.
May 11, 2026
Wachter argues that that digitization in medicine was inevitable, potentially revolutionary, and deeply disruptive (the process has often been chaotic, expensive, and psychologically draining for clinicians). The EHR is the platform for the deep entry of AI into healthcare, and the success will be highly dependent on implementation, incentives, and human oversight. Wachter identifies the most likely benefits (including safer care through prediction, expanded access to expertise, more personalized medicine, continuous learning healthcare systems) and pitfalls / risks (overreliance on algorithms, algorithmic bias, opaque black box decision making) of this transformation...his tone is balanced and reflective; neither anti-technology nor blindly enthusiastic. I particularly enjoyed learning the backstory on EPIC and its founder Judith Faulkner. Improved understanding of the history of digitization and AI in modern healthcare (i.e. how we got to now), and where we may be going left me somewhat optimistic...
July 27, 2026
I greatly respect the effort Dr. Wachter put into a Giant Leap. Where the book is strongest are the case study examples of AI applied to non-medical settings, and thinking of how public opinion and our regulatory policy could ripple through clinical care. I think he goes through a lot of the important sociological questions about medical training, staffing, and more that AI can do as well.
The main thing that left me “wanting” was slightly more firm stances on where it should and shouldn’t be used. Of course, predictions of this nature have the possibility of backfiring, but I feel like saying “we should prioritize this style of medicine because medicine in America can be synergistic” TODAY is a worthwhile claim. That conversation needs to be active and likely centrally agreed upon; otherwise, we are going to get fractured solutions. Fractured solutions could make this more of a game of clinical wack a mole opposed to better care for patients. Time will tell!
The main thing that left me “wanting” was slightly more firm stances on where it should and shouldn’t be used. Of course, predictions of this nature have the possibility of backfiring, but I feel like saying “we should prioritize this style of medicine because medicine in America can be synergistic” TODAY is a worthwhile claim. That conversation needs to be active and likely centrally agreed upon; otherwise, we are going to get fractured solutions. Fractured solutions could make this more of a game of clinical wack a mole opposed to better care for patients. Time will tell!
February 11, 2026
This is Nonfiction and it explores how AI is already transforming healthcare and how its impact will likely grow in the coming years. The author dials in on both the opportunities and the challenges that the use of AI brings. His enthusiasm for AI's potential is clear, but he also urges careful and responsible use and I will also add, for doctors to stay involved and not turn it all over to AI.
The primary focus here is healthcare, but he also touches on how AI is shaping, and will continue to shape, many other aspects of daily life. There is plenty of food for thought here.
Overall, it's a forward looking discussion that encourages curiosity while acknowledging ethical thoughts and considerations. But all in all, this was kind of fascinating, so 4 stars.
The primary focus here is healthcare, but he also touches on how AI is shaping, and will continue to shape, many other aspects of daily life. There is plenty of food for thought here.
Overall, it's a forward looking discussion that encourages curiosity while acknowledging ethical thoughts and considerations. But all in all, this was kind of fascinating, so 4 stars.
March 2, 2026
A digital health skeptic turned enthusiast discusses how AI may revolutionize healthcare. A few key points emphasized:
1. AI tools address many emr shortcomings that allow docs to interact with data in plain language with actionable insights
2. Rapid adoption and trust building signals benefits in improving efficiency and interaction with complex health system which may lead to a promising future.
3. Balanced governance and continued human role in coordination of care delivery balancing innovations with patient safety.
It may help make healthcare more impactful, efficient, safer and less expensive.
1. AI tools address many emr shortcomings that allow docs to interact with data in plain language with actionable insights
2. Rapid adoption and trust building signals benefits in improving efficiency and interaction with complex health system which may lead to a promising future.
3. Balanced governance and continued human role in coordination of care delivery balancing innovations with patient safety.
It may help make healthcare more impactful, efficient, safer and less expensive.
April 9, 2026
Robert M. Wachter’s A Giant Leap is a compelling and timely exploration of how artificial intelligence is reshaping the future of healthcare. Blending rigorous research with engaging storytelling, Wachter examines both the promise and the challenges of AI from improving diagnoses and reducing errors to addressing systemic inefficiencies in modern medicine. What sets this book apart is its balanced perspective, acknowledging the risks of bias and misinformation while highlighting the transformative potential of AI when applied thoughtfully. Insightful and accessible, this is essential reading for anyone interested in the intersection of technology, medicine, and the future of care.
September 5, 2026
This is an interesting book on the state of AI in healthcare. All aspects of healthcare are considered, with pros and cons given. For me, the most enlightening tidbits were the Doctor Digital Twins, and the story of Epic as a platform for pulling together medical data (both the product and the backstory on the founder). And the data point that in 1950 medical knowledge doubled every 50 years as compared to today, where medical knowledge doubles every couple of months. This book gives me a good foundation to understand the healthcare advances to come.
Recommended. Not for pleasure reading but you will learn a lot.
Recommended. Not for pleasure reading but you will learn a lot.
February 23, 2026
As someone interested in how AI is being adopted by different sectors, I found this to a be a very accessible overview of the current and potential impacts of AI on healthcare. The general theme of the difficulty of overcoming human systems and the high stakes challenges in healthcare are not earth shattering epiphanies, but the author brings these issues to life with his knowledge and examples. I have little background in healthcare personally. I imagine readers more familiar with this terrain may find parts of the book too basic.
June 30, 2026
Very interesting - thoughtful overview of the history of medical AI endeavors, where it is currently being used effectively, impact on medical education, and possible futures. Cautiously optimistic about positive impacts it could have on the lives of patients, physicians, and all allied health members. Our current system isn’t great so open to exploring new ways to address. Self proclaimed that it did not touch on the many potential negative impacts of AI - which are significant.
Read via kindle
Read via kindle
August 12, 2026
Reassuring to hear that my future career probably won’t be erased by AI in the next few decades, but a bit concerning that my med school admissions might be decided by one.
I enjoyed how Wachter broke down the different tasks that AI models are being trained to take over, and the challenges with each. I also thought the problem with human supervision getting progressively worse without doctors regularly practicing tasks themself was interesting.
Overall, a digestible and optimistic overview of the current state of healthcare AI.
I enjoyed how Wachter broke down the different tasks that AI models are being trained to take over, and the challenges with each. I also thought the problem with human supervision getting progressively worse without doctors regularly practicing tasks themself was interesting.
Overall, a digestible and optimistic overview of the current state of healthcare AI.
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