The a16z Show - Your AI Doctor Is Coming | Julie Yoo

Episode Date: September 6, 2026

a16z General Partner Julie Yoo joins MTS host Sophia Dew to explain why she believes healthcare could benefit more from AI than almost any other industry, and why decades of slow technology adoption may actually give healthcare an advantage in the AI era.Julie traces healthcare’s evolution from paper records and fax machines through electronic health records and telehealth, and explains why AI represents something different: an organic adoption wave driven by tools that doctors and patients actually want to use. Because healthcare never built the same layers of legacy software as other industries, it may now be able to leapfrog directly into agentic AI.They also explore how AI could dramatically lower the cost of care, why consumers are becoming a more important payer, where Julie sees the biggest opportunities for healthcare founders, and a future where everyone has a highly personalized AI doctor in their pocket for life.Resources:Follow Julie Yoo on X: https://x.com/julesyooFollow Sophia Dew on X: https://x.com/sophiadewFollow MTS on X: https://x.com/mtslive  Stay Updated:Find a16z on YouTube: YouTubeFind a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Healthcare is one of the most expensive industries in the world, yet time and medical expertise remains scarce. Julie Yu thinks AI could change that. The A16Z general partner joins Sophia Dew on MTS to explain why healthcare may benefit more from AI than almost any other industry, and why its slow adoption of technology could now be an advantage, allowing it to leapfrog legacy software and move directly to AI-native workflows. Julie also shares where she sees the biggest opportunities for founders,

from consumer health care and AI native care delivery to robotics and new payment models and why the future could include an AI doctor in your pocket for life. Julie, welcome to MTS. Thanks so much for having me. I'm so excited to chat with you and I'm so excited to get into this conversation because often in some of the conversations around AI,

people don't totally understand how it affects them and I think healthcare is one of the most obvious places where you actually get to see that possible. But before we jump into all of the details there, I would love to just start a little bit with your personal story. Why is health care one of the big problems you wanted to solve? Yeah, absolutely. I mean, I've been in the healthcare industry now for probably, gosh, 18 years at this point. And I was too early, you know, like back then.

I was actually a technologist by training. So out of school was a software engineer in the broader tech ecosystem, road code for the first seven years of my career. Did a lot in like the early era of like e-commerce and fintech and manufacturing, et cetera. and then made a career change into health care. Right when the federal government was starting to talk about how do we digitize health care, because I'm sure if you talk to anyone about their experience in health care, one of the first things I'll say is I'm being paper to death, I'm being fax machine to death.

You know, we still have a long way to go. But, you know, imagine 20 years ago when the majority of the industry was actually still working on paper, like doctors' offices still had those paper folders in their cabinets and nothing was digitized. And so the federal government decided to implement this math, massive program, which is kind of a miraculous program when you think about it. Basically what they said was we will pay doctors tens of thousands of dollars to implement electronic health records. And that was the way by which our industry sort of came into the modern era was for over the course of about five to seven years, I would say, literally 100% of doctors in the U.S. were heads down implementing these kind of system of record electronic health record platforms. And that's how we kind of came into digitization. So right around then was when I made a career change thinking, okay, I've now seen what great looks like with respect to enterprise technology being applied to all these other industries, you know, e-commerce, retail, manufacturing, et cetera. You know, now it's time for healthcare to have its shot in the light.

And of course, again, I was like 15, 20 years too early, but obviously so much of the evolution that's occurred in the last 10 years is really what I get excited about. And I initially started out in kind of the genomics era, which was one of the first areas where you saw just an explosion of data. We had the Human Genome Project. We now understood the fundamental code of humanity. And there was a whole industry that exploded around kind of computational biology. How does genomics tie to ultimate disease and things of that sort? So did a couple of really cool companies in that area. And then ultimately around 2010 was when I started Chiris, which was my company, really with the thesis of some of what you described.

So we as consumers experience extreme access issues when we try to get in touch with the healthcare system. the average wait time for a primary care doctor's appointment is, you know, weeks, if not months in most major cities across the U.S. still today. And when we started to, when me and my co-founder started to talk to executives who were running these large, you know, hospitals and physician groups in the industry, what we didn't realize was they were telling us, you know, yes, people are waiting out the door. But if you actually look at the way that our physicians are being utilized, we're still way under 100%, which was shocking, right? we had this paradox of demand out the door, and yet when you looked at utilization rates of physician's time, it was way under 100%. And so that was the thesis behind our company, Chiris, was how do you sort of solve this patient access paradox by creating a single system of appointment inventory across the healthcare system and the ability to route patients to the

right doctor and the right appointment in such a way that you could actually effectively utilize that capacity much more efficiently. And so, So did that for an amazing nine years as co-founder and CPO. But it was, again, in sort of like the stone age of health tech. So, you know, this gets to sort of my current job today. Back then was, you know, imagine tech sort of like pre-stripe, pre all the sort of like API layer of, you know, how you build companies and stand-up companies. That was effectively the situation in health tech back then. Very little venture capital also going into our space back then.

and a lot of the conventional wisdom at the time was healthcare is just so hard, right? It's a highly regulated industry. Things are super slow. People are, you know, understandably conservative because the stakes are very high to, you know, if you get something wrong. If you get something wrong, the stakes are very high.

And so there was a reticence to believe that the, you know, the kind of speed of growth and scale of technology application that you would see in other industries could even happen in healthcare. And so it was not as popular, urban industry for VCs to really kind of put their half behind. So back then, I joke that there was like five guys who like invested in our space and I raised from like all five of them.

And but, you know, it was pre-APIs. We literally, I liken the work that I did literally with my own two hands as taking like a chisel and a nail against this concrete wall of integrating into the infrastructure of healthcare. And so it took a, you know, a lot of time, a lot of capital. It was really hard to recruit talent back then because it just was an unsexy industry. right, like if you had a choice of going to Google versus, you know, trying to build these like 1970s systems, like, why would you choose to come into our space? So we did it the hard way,

but, you know, great outcome. We actually just sold the company last year. Congratulations. Thank you. Yeah. So huge. Yeah. And the decade paid off. Yeah, it was like a 15-year overnight success. But, you know, in that time, so many things occurred to really, you know, mature the industry in so many ways that now, I would argue, like this is our moment in health tech. And I've now been an investor. After I stepped on from my company, I came to the dark side and I now run

the healthcare investing team at Indreason. And, you know, what's occurred over the last, you know, seven years, like literally since I've joined the firm, is, you know, really remarkable. So one, you know, obviously we had COVID, which I think was a huge reason why people were forced to recognize the need to create a digital modality

for engaging with the healthcare system. And it really, you know, tore apart a lot of the previously held assumptions about how healthcare needs to work in terms of everything from, you know, how are physicians credentialed, you know, to practice medicine. Historically, it's been a very sort of local system where we sort of like deliberately constrained supply in healthcare, you know, in weird ways. So you have to get licensed at the state level. And it was not the case that doctors typically would have a license, you know, to practice medicine outside of their state. But with telehealth, you know, all of a sudden you had this national scale demand for

clinical services. And so, you know, lots of states and, you know, federal agencies had to kind of rethink from first principles. How do we relax some of these constraints to enable people to get access to care when you can no longer go in person? That was one. Another was, you know, kind of the way that we pay for health care. You know, telehealth previously was, in many cases, was not paid for unless you had previously had an in-person visit with a doctor. So we had to relax a lot of those roles. So there was a lot of tailwinds in the industry during that period that sort of led to acceleration of the ability to build tech companies in this space. And then obviously AI.

I mean, I think I've declared loudly that I believe healthcare is the industry, that the industry that will benefit the most from AI for many reasons that I'm sure we'll talk about. But, you know, the level of accelerated growth and scale and adoption that we've now seen in the last, let's call it, you know, three to five years post-AI, I think is proving that point and, you know, demonstrating that the moment is here for digital health to be. be a thing. Definitely. It's so fascinating getting to hear your story because you understand how technology has affected the healthcare industry for over multiple decades. And you've gotten to see when you were way too early, as you say, I like how you mention your 15-year overnight success.

Which most startups are. Exactly. Most startups are. I'm going to quote that for my parents. I'm like, no, no, no, I'll be a 15-year overnight success. Just you wait, just you wait. But as you alluded to, healthcare, it's been a long time coming. was maybe prior when you were starting your startup, it wasn't as sexy of an industry. It was harder to get talent. It was harder to get capital. But it seems to me that that's no longer the case, even if what you're seeing with Dario, where he's saying, okay, we're doubling down in health. We're going to cure cancer. I talk to startups all of the time, especially in AI. And one of the common themes that we're seeing is that they're going towards the hard problems,

the ones that are really bureaucratic, the ones that are legacy that, like, if you solve it correctly, literally saves hundreds of thousands, millions, billions of lives. And so I'm so excited to see that. And I would love to just get your opinion. What shifted? What was the big change over the past few years that gave us this renaissance, this healthcare industry renaissance that we're in? Yeah, I think it was a confluence of factors. So, I mean, exactly to your point, it has always been the one industry that literally impacts everyone. Like every single life has some interaction with the health care system at some point. And typically, it's a very negative experience, unfortunately. And so I think one thing is that just, you know, consumers have gotten to a

certain breaking point where especially as all of the experiences in the rest of our life, right, if you think about how Uber has changed transportation, how Airbnb has changed travel, how Instacard has changed the way we think about food, et cetera, et cetera, you know, our standard and our bar for what we expect from any service industry has gone way up while health care is kind of state stagnant. So I think that gap has really gotten to a breaking point where consumers are saying, I want to vote with my feet and my dollars to get better services wherever I can get them. So that's been one big change. I think, you know, at the same time, the incumbent industry is under extreme siege, right?

So if you think about large hospital systems, large insurance companies, employers, you know, put the majority of the bill for, you know, most insurance fees and premium dollars for a vast majority of Americans. And so, you know, all of these organizations are sort of experiencing increased cost structure, So labor has gotten much more expensive, labor has gotten much more constrained. We did unfortunately have a big sort of outflux of talent from the healthcare industry because of COVID, you know, because it was such a stressful and arduous time that a lot of people said, I'm throwing the towel in and I'm going to go do something else with my medical training.

So at the same time, the government has also really come down on the cost, right, and said, you know, we have just unsustainable amounts of bloat right now. And, you know, this is a little bit of a rat hole, but, you know, one of the reasons that health care appears to be so esoteric is that we have this weird third-party payer system, right? Like, the vast majority of your health care is not paid for by you. And so you don't necessarily feel the pain with every, you know, dollar that you're spending in the health care system. And therefore, there tends to be a lot more bloat than if you would have with, like, a free market dynamic. And so, you know, the government's coming down on that. Payers in general are coming down on that.

So you have all this cost pressure on the incumbent system. that has driven, you know, traditional providers and payers to say our business model, like, no longer works. Like, the math doesn't math anymore. And we can't continue to sustain this kind of payment modality. And AI, like I would say certainly AI, in some ways, was like the straw that broke the back where, you know, historically, because healthcare is such an esoteric, sort of scarce training-oriented industry, where you literally have to go to school for, what is it, you know, at least seven years and train and to even become. a specialist, you know, service provider in our industry. So the bar to, you know, being able to

create technology that could replicate any, anything that's close to that level of expertise has been really difficult until we now have this, you know, abundant intelligence, you know, capability that we have with LLMs. And so I think that, you know, those I would say are the, the major confluence of factors that have now resulted in a recognition by both the supplied side and the demand side that things need to change. And, I mean, the last thing I'll say is that But one of the ways by which the system had reacted to this kind of cost bloat in the past was to say, okay, if you have, let's say, insurance covered by your employer, you know, historically the employer covered the majority of the costs and you didn't really feel any of the financial pain. Now what they started to say like a few years ago was, okay, let's actually do some cost shifting. Let's actually give consumers a little bit of skin in the game and say, okay, we're going to have deductibles.

And so up to $1,000, your insurance is not going to kick in. so anything under that you're going to have to pay for. And then that actually is what caused consumers to realize, okay, gosh, I have to pay how much for what kind of crappy services? And, you know, people really start to feel it directly. And now you have this proliferation of services to kind of fill that void, right? We have amazing companies that you can pay literally $10 per month out of pocket to get incredible services that when compared to what you could get

for that same amount of dollars with the traditional healthcare system is just a thousand times better. And so that's what really, I think, has caused the adoption wave that we've seen by just individuals. Oh, interesting. So what I'm hearing is there's some systemic shifts around how healthcare is just paid for,

and that's really been changing over the last two years. And then, of course, what exists now with technology and AI, and one of the things that you argued is that health care may benefit more from AI than arguably any other industry. And so I want to just unpack a little bit more about where exactly, you can see AI's benefits when it comes to healthcare.

One of the areas we were just talking about yesterday is in discovery of diseases and drug discovery, but there's still a whole development pipeline that doesn't totally benefit the consumer until maybe it goes through a bunch of clinical trials. I know there's a lot of different angles. If we can just briefly touch upon the whole staff, where is AI actually playing?

How will I as a person, as a consumer, as a customer, how will I feel this benefit? Yeah, absolutely. I'll talk about it in a couple of different ways. One is the industry itself has been almost like antithetical to technology adoption historically. We literally have been like the lowest in terms of dollars spent on tech relative to revenue, like the lowest of the lowest in terms of industries. And so one thing that's changed now is kind of this like what I call a leapfrog dynamic where when you think about every other industry, they spent the last, you know, a couple of decades. laying down like workflow SaaS rails, right?

Like software service companies. And they had this whole sort of like middleware layer on top of infrastructure that they spent tens of billions of dollars on, trained a whole generation of workers on. And then when AI came along, they said, oh my God, we have to rip and replace this whole previous paradigm of technology and replace it with agentic AI and retrain our whole generation of workers on that modality. Healthcare for better for worse did not spend that amount of money, right?

So we only had really like the ERP layer with EHRs and then labor. Like we were just throwing bodies at every problem. And so in some ways, we have less of a sunk-cost bias as an industry to say, okay, this new technology paradigm has come along, and we can just leap right to it. We don't have to worry about ripping out, you know, 20 years and tens of billions of dollars worth of middleware software. We can actually just go directly to this agentic form of technology. And that's actually been a huge boon to many of the companies that sell into the space. So the other, I wrote a blog post about a year ago that talked about the fact that historical eras of technology adoption and health care were always very unnatural. like what I talked about earlier.

You had to pay doctors to adopt technology. You had to have a pandemic to force people to use telehealth. This is currently is the only, like the first real organic adoption wave that we've seen in health tech where doctors are just using AI scribes because they freaking work. And they're so good and they really change the nature of their job for the positive. And you're seeing a lot more of this almost like PLG-led motion where individual physicians and frontline workers actually have agency and being able to use these tools in a different ways. So that's one part that's happening more on kind of the enterprise side. On the consumer

side, you know, thank you, ChatsyPT and Claude. Like everybody is going to LLMs for health-related questions, right? And they're pretty damn good, right? And they've gotten a lot better since the early days when they first came out, less hallucination, much more, you know, sort of actionable advice and recommendations. And they're starting to like forward integrate into actual marketplaces where you can get advice from Chach, GBT, and then go book an appointment with the real doctor. And so I think that's just taught a whole generation of humans. There's, number one, just a much more low friction way to get medical advice. Even if the medical advice might not be regulated and licensed and, you know,

and fully validated in the way that you would get from doctors, the trade-off is I either, you know, have to wait four months to get a real doctor's appointment or go to an emergency room and pay $2,000 or I can just open up my phone. And so I think that trade-off, again, that Delta makes it incredibly easy. for people to just go to the lowest friction place. And so I think people, like consumers are now educated that there's a better way. And now we have a whole wave of new companies,

many of which we've invested in, that are taking a specialized approach to how we leverage AI to create consumer grade experiences where you're now seeing like a company, we have a company called Council Health in our portfolio, which is literally an AI native doctor practice that is a 24 by 7 asynchronous chat modality with real doctors. Like imagine chatting with your chatbot, but having an actual licensed

MD in the chat who can fully prescribe, who can fully refer, who can fully diagnose. And so you kind of get the best of both worlds of, you know, AI native care with real doctors who can actually provide clinical utility. And so you're seeing the advent of these new capabilities that literally were not possible even just a few years ago. One of the things that just wasn't possible a few years ago that I wanted to bring up, there was this hackathon by Anthropic AI and AWS Cloud. And it was called the rare disease real kid hackathon. And they had $50,000 in prizes. And the way that they did it is they actually had a child. They uploaded the kid's genome and the clinical data. And they shared it with the community, of course, with parental consent. And people were able to actually

understand. Yeah. And generate insights. And I saw this. And I was amazed. I was, this is so cool. You can actually, for specialists, it's really hard to find specialists, especially for rare diseases. Those are, and children with rare diseases, there's so little resources actually going into, the money doesn't actually make sense. And so seeing this, I was like, wow, this is amazing. This is one really clear example of how AI can actually play out, can actually save human lives.

curious to hear what your opinion was of this whole hackathon if you saw it. Yeah, no, absolutely. I think every day, I mean, one of the most exciting things is that like literally every day on my ex-feed, I will see 100 examples of something like that. And I think to me there's sort of three parts. One is, you know, how do you lower the barrier to access intelligence, which, again, that barrier used to be a real, you know, kind of impediment to people getting access to health care. Now that thing, that's really gone away. And then I think now the question moves towards what do you do about? it, right? Once you actually understand a bit more about what your issue might be or what diagnosis

you might have, you still need to, number one, get that verified. You might need actual testing or, you know, kind of clinical grade testing to get it fully diagnosed. You might need to be either prescribed a therapeutic or a procedure or, you know, get some sort of in-person care. And then there's like the longitudinal aspect of it as well. A lot of the way that people are using, which is great. I mean, medical AI today is highly transactional. Imagine if you can have a doctor for life that's powered by that kind of modality. We know what that could mean for life. So I think the first bucket is being solved by, you know, a lot of these generalist

tools. I think it's really the second and third bucket that therein is the opportunity for, you know, health tech builders to really take a crack at that last mile of what do we do about it and how do we stay with you for life until it's resolved until the next issue comes up, etc. That's so cool. One thing I wanted to get your opinion on since now you're in the investor side coming from the builder's side to now that investors.

side, you one, have to make a bit of predictions about where things are going to go. And two, you get to see the opportunity landscape almost at a macro level. And so someone is coming to you for maybe advice or there's a founder who is asking, okay, Julie, where do I go? What are the big opportunities here? What are the big problems that still need solving? What advice would you share? Yeah. How much time do we have? I mean, there's the opportunity. It's like the best time to be building in this space. I'm so jealous about my founders who gets me building right now. I think probably a couple that I would highlight that we've written about recently so folks can kind of check out our thesis on this. One is definitely the consumer angle. I joked a few months ago that if you had

come to any investor, let's call it, you know, seven years ago and pitched a consumer health business, you would have been kicked out to the room because there was no viable business model. It was not clear that consumers understood and had agency to, you know, really take control of their health, et cetera, and the payment models were not there. So now that all that's changed. And some of the fastest growing companies that we see in health tech are cash pay. You just pay out of pocket for a service at a disruptively low price. I think that's actually the biggest lever that's changed is even if you could pay for things

out of pocket historically, the price was prohibitive. And now because of the magic of AI, the cost structure to deliver an actual medically credible service is like 100 times lower than it used to be. And so you're seeing a whole proliferation of an entirely new marketplace of products that were designed for the consumer, not like historically where you had to design for the insurance company and the doctor. And then consumers almost as an afterthought, consumers are now at the top of that pile in a really exciting way. So we wrote a piece called Consumers Are the New Payer, basically, to sort of recognize that trend. So that's one big area. Another post that I had just last week actually was one where we made the argument that

the best companies right now are those that are AI native and AI proof. And it kind of gets to what I was saying earlier where, yes, you can have an amazing, you know, medical, sort of general medical intelligence LLM that answers a bunch of questions that, you know, historically you had to go wait for six months to see a specialist to get. But what about the rest of it, right? So how do you actually deliver in-person services to people who can't travel to the hospital? How do you actually do, you know, how do you take a blood draw and actually diagnose, like what you actually have? How do you, you know, do all the things that today, at least in our country, are not, like, legal to do, you know, lest you have some sort of regulated entity? So we have a lot of

companies that on the outside, and this kind of mirrors a lot of what we saw in the first era of tech, you know, more broadly, where you had kind of these challenger businesses that were full stack in nature. So, like, from the outside, they might just look like a retailer or just look like some kind of service provider, but on the inside they were obviously highly AI native and therefore had a surface area that was not achievable, you know, through historical means and a cost structure that was disruptive such that they can continue to invest in innovation because they had high margins. We're seeing a ton of companies that are embracing kind of the best of both worlds in that

way. So I think AI Native AI proof combination is a lot of where the excitement is, hardware companies, you know, are included in that. So I think robots are like I think there's product market fit between, you know, what robotics companies can do and what is necessary in really like high acuity health care settings. And then the final thing I'll say is like insurance, like the payment rails are one of the reasons that like, you know, people look at health care and they say, oh, it's so screwed up. Like it's so like why is it so screwed up? I'm like it's actually designing exactly as planned. Like if you actually study the innards of how incentives are aligned based on, you.

the payment system that exists in health care, it results in exactly what we experience today. And so there's a lot of really ambitious companies that are saying, what if we blew up that current healthcare payment modality and built a new one from scratch? And, you know, that is amongst probably the most ambitious things that you could do is kind of build almost like a mini health care system in one company. But there's companies like devoted health and others who are doing this. And I think now it's possible because, again, the cost to entering into building a company in our space has gone down because all this infrastructure now exists, you can do so much more with AI. And the appetite from the system, both in terms of consumer customers, as well as the traditional ecosystem,

is there in a way that's never been before. Oh, that is so exciting and exciting to hear. My last question for you, what prediction do you have that will be true in a decade from now? I would love to one day, you know, tell my kids or my future kids, yeah, back in my day, healthcare was X and now. Yeah, yeah. And then what do you think? I mean, I think, so getting to your example about the sort of, you know, roll your own genome analysis thing, like I do think there will be a lot of roll your own

health care, where you will have end of one solutions that are like only like super personalized to you but still get, you know, the kind of benefit of the broader set of intelligence that everybody's contributing back to. I mean, one of the interesting things about healthcare is that in order to train a model in health care, I would argue that we actually don't even have the data sets necessary to truly train like a medical grade AI because we rely heavily today on electronic health record data, which is really sporadic, right? Like how many times you actually go to see a traditional doctor in your life? It's like maybe at best once a year.

So there's a whole narrative arc of your experience as a patient that is absent from pretty much every data set that exists today. So I think a lot of companies will start doing these kind of N of one experiments that generate the new data rails that then drive the next generation of models that are built in our space. So I think N of one health is a big idea. And I think all of us will genuinely have an AI doctor in our pocket for life. Yeah, we'll all have a personalized specialist that knows us better than anything in the world. That is so exciting to see. And this is one of the reasons I am such a big tech optimist and so excited for the future and how technology is impact. the future and you touched upon directly some very concrete reasons. But Julie, really wanted

to thank you for joining us today on MTS. Absolutely. It's such a great conversation. Thanks for having me. Thank you so much for joining. Thanks for listening to this episode of the A16Z podcast. If you like this episode, be sure to like, comment, subscribe, leave us a rating or review and share it with your friends and family. For more episodes, go to YouTube, Apple Podcast, and Spotify. Follow us on X at A16Z and subscribe to our substack. a16z.substack.com. Thanks again for listening and I'll see you in the next episode. This information is for educational purposes only and is not a recommendation to buy, hold, or sell any investment or financial product. This podcast has been produced by a third

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