Health systems are no longer asking whether to deploy ambient AI. They are asking how to scale it across roles, connect it to revenue cycle, and avoid building another layer of fragmented tools. Kenneth Harper, General Manager of Dragon at Microsoft, joins Megan Antonelli to unpack what separates the organizations actually moving the needle from those stuck in pilot mode, what ambient AI's expansion from physicians to nurses and radiologists has revealed about clinical workflow design, and how CIOs should think about building a coherent clinical AI architecture in 2026.
Kenneth Harper, GM, Dragon Product, Microsoft
Megan Antonelli, Chief Executive Officer, HealthIMPACT Live
00:00:00 Intro: Welcome to Digital Health Talks. Each week we meet with healthcare leaders making an immeasurable difference in equity, access and quality. Hear about what tech is worth investing in and what isn't as we focus on the innovations that deliver. Join Megan Antonelli, Janae Sharp and Shahid Shah for a weekly no BS deep dive on what's really making an impact in healthcare.
00:00:30 Megan Antonelli: Every CIO I talk to has the same problem with clinical AI right now. They have pilots running, they have vendors pitching. They have boards asking when this all turns into value and operating leverage. And almost no one has a clean answer for how these pieces fit together. My guest today runs the business that put ambient documentation in front of more clinicians than anyone else in the industry. He is now watching health systems try to scale that from physicians to nurses to, to radiologists, and into revenue cycle and operations. So we're going to talk about what real production looks like, what the architecture has to go to next, and what is genuinely working. This is Megan Antonelli, CEO of Health Impact Live. And this is digital health Talks. I'm here today with Kenneth Harper, general manager of Dragon at Microsoft. Hi, Ken. How are you today?
00:01:22 Kenneth Harper: Hey, Megan. Thanks for having me.
00:01:25 Megan Antonelli: Yeah. Welcome to the show. I mean, you know, I can't believe for as long as I've known you guys over at Dragon, of course, that our friends at Microsoft, we haven't had a chance to meet. So I'm excited to finally meet.
00:01:36 Kenneth Harper: Yeah. I appreciate you letting me come in and have this conversation.
00:01:39 Megan Antonelli: Absolutely. Well, you know, I think what's so amazing about, you know, kind of your history and your background is, you know, you're really one of the first folks to work on this being at, um, Dragon for over, you know, almost over twenty years now. Tell us a little bit about kind of your background and how you got into it.
00:01:58 Kenneth Harper: Yeah. Happy to. I, uh, have a background in human factors, and I had this opportunity coming out of college to, to go work on a company that was doing voice recognition. Personal assistants at the time is what we, we called it. And human factors is very much about, you know, how do we interface with technology and how do we interact with technology to help improve our lives? And so it was just an opportunity that I got really excited about. I didn't know much about voice recognition, to be completely honest. But the, the first part of my career taking this opportunity was, was looking at voice and how you could create really powerful experiences for consumers on how you talk to your phone, to place a phone call if you're driving or send a text message if you're driving for a hands free experience, or how you can ask your TV to find a show that you want to watch because you want to go through the the channel guide or talk to your car and ask it to find directions for for where you're looking to navigate to, and I worked on that for a very long time. You know, more in the consumer industries. And then halfway through my career, it kind of dawned on me, although it was cool what voice was was doing what personal assistants and AI was, was doing. It just didn't feel like the meaning was there as much in terms of the impact that that this was, was having. And I started looking at what else was out there, what other opportunities were out there. And it just so happened that that was about the time that my son was born. And I remember, you know, trying to take him in for a specialist appointment. And number one, it took six months to get the appointment, uh, believe it or not, but even once we had the appointment, I do distinctly remember just the physician. She was great, but the physician was buried in the keyboard as she was was interfacing with with me and asking me questions about about my son. And it was impersonal. And it was just she was in the computer typing the entire time. And it was one of those moments where I said, I do wonder, like, what's in healthcare and how could this technology come into healthcare? You know, and be used as more of that natural interface for, for how physicians are doing their work and the stars lined up. And to make a long story short, I had an opportunity, you know, in same company I was working with, you know, nuance at the time, Microsoft now to come into the healthcare division and stand up this new program around ambient. We didn't call it ambient exactly back then the way we do today, but it was this idea of, could we build an experience for clinicians where they walk into a room, they have a conversation with a patient and smart things start to happen automatically. That was the idea almost a decade ago. Believe it or not, we've been thinking about this and working on it, uh, at Microsoft. And that started everything in terms of coming into healthcare, using this technology to solve real problems for health care workers. And what I will say, I know we'll talk about this more today, but the impact that it's had on care workers and how they're able to to get their lives back and focus on patients. Uh, it's, it's been an incredible journey over the last almost decade, just getting this technology out the door and seeing it scale to the point that it has.
00:05:14 Megan Antonelli: Yeah. That's amazing. So how old is your son now?
00:05:17 Kenneth Harper: My son just turned eight years old. Oh, wow. So yeah, it's been a it's been a great journey.
00:05:23 Megan Antonelli: Yeah. No. And I mean, there's so many of us, I think, do get into health care and sort of make that pivot when we realize the friction in the system. You know, and I think for many of us around the time our kids are born, is that first real? If we're lucky, it's our first real engagement with the health care system to see just how many challenges there are to fix. Right. And I think this one in particular, I mean, I think back to seeing the the graphic of the physician. You know how, you know, sort of at the computer doing the, um, you know, while the patient sits and is, you know, with his back to the, the patient. And, you know, at the same time, this was when we were pushing electronic health records saying, you know, this, you know, we want this, we need more technology in health care. We need more of this. And yet this was going to this was the consequence of that. And I think what is so exciting about everything you guys have done at Dragon is how much that has changed. You know, the relationship between the, the health system, the technology, the patient and the physician and brought that back. So tell us a little bit, you know, I think we talked a little bit about this before in terms of, you know, our health systems are eager to adopt AI, eager to adopt ambient. It has the technology's been around for a while, but a lot of them are still in pilot mode. And, and it's, you know, how do you get to that place where it is production? You're now seeing health systems who have had this in place for a very long time. So your perspective on kind of what's what they're doing and what the, the value that they're seeing. Um, I would love to hear more about that.
00:06:59 Kenneth Harper: Yeah, we, we definitely are now seeing this technology scale, you know, in healthcare, you know, but not everyone's at the same level of scale. There's, there's still work to, to be done for for sure. But we have, you know, over one hundred and fifty thousand clinicians now where Dragon Copilot, which is our latest version of Dragon, is helping them, them do their work. And so the scale is definitely there. You know, what I would say, though, is where we've seen the most success, you know, inside of organizations who view this as this is now an essential tool that every clinician should have is they put some thought and they, they roll it out deliberately from an enterprise perspective, you know, they don't just take it, you know, to one department or one specialty anymore. They really focus on how do we put a program together inside of an organization? How. How do we think about the change management, which is so critical for any new new workflow tool that you're putting in the hands of clinicians? How do we put together a formal program to roll this out to enterprise, you know, where every clinician should have the right to to use this? And they think about it, they think about the training, making sure there's awareness that this, this tool is there, encouraging people to give it a shot, making sure that if folks have questions, uh, that they, they get addressed in terms of how to make the most out of the tool. They're always with any AI. There's always some tips, tips and tricks, uh, of what you can do to really make it work well, well for you as a, as a clinician. And really what happens is you begin to see this flywheel because inside an organization, when all your colleagues are using something, you hear about it and people start talking about what they're doing and the impact that it's having on their practice and their patients. Uh, and the more people hear it, the more people want to try it. It's almost like the self-fulfilling prophecy of everyone's talking about it, and it creates a lot of buzz in the organization. And before you know it, your entire organization is is lit up. And so I think to answer your question, the organizations that we've seen do this well. Advocate is one example. They're one of the first to really think about rolling this out from an enterprise perspective. We want everyone to have the right to use this, this tool. They've just been a phenomenal partner of ours, but they've put so much time and energy to make sure they've thought about that change management and making sure the support system was there to make it successful. And it's really about that leadership team and the health system saying, we're all in on this. There's no debate on it. We're all in on it, and we're going to make it successful with our clinicians.
00:09:30 Megan Antonelli: Yeah, I think that's, you know, a lot of the things that we've heard in the past is, you know, you'll hear that they don't want it taken away. Those who have it love it. They, you know, and it does, it sort of spreads like wildfire. And they want, you know, the others in the departments want it. Tell me a little bit about, you know, is there, um, what's involved in terms of, of that, you know, if you're going, if you're taking it from the clinicians, physicians, if you say you pilot it with, with one department and then you go to a next. What does it look like? Or what, how do health systems really need to rethink or think about that clinical AI deployment when it's when it's going across roles?
00:10:08 Kenneth Harper: Yeah, they, they definitely think about putting together educational materials. And, you know, I've seen some organizations do webinars, you know, with, you know, going from specialty to specialty where they have everyone come in to make sure folks know, uh, what this is and how it's going to, to change their lives. There's a lot of education and evangelism that, that they do. And so I think going back to creating programs and creating content and collateral that they take to all the different specialists and departments and where they're rolling this out and make sure folks understand it. They are very deliberate. And on this day, this is what you're going to get. And this is the time commitment we're asking from from you to get set up. Um, so they don't leave it to chance, I guess is another way to say it, you know, or it's not, you just get an email like go try this thing. No, they really put some structure around making sure everyone has the opportunity to try it and carving away some time, you know, for that provider, you know, to get set up with it and give it a try. And so it's, it's one of those I, I think it's a recognition amongst leadership that, you know, sometimes you just got to give someone a little bit of time to go try a new tool because, you know, if they go in and they start using it, it's going to have such a big impact, uh, on the outcomes that, that, that clinicians then seeing.
00:11:24 Megan Antonelli: Yeah. What would you say? I mean, in terms of best practices around training? I mean, you know, we talk about the pit a lot on this show lately.
00:11:36 Kenneth Harper: It does. It does come up a lot. A lot of our internal forums. It definitely is a bit of work research. Yeah.
00:11:41 Megan Antonelli: And you know, they sort of they, they hit all the they hit they hit all of our top topics in particularly this, this season. But, you know, I mean, you see where Doctor Sandoz is, you know, he's she's being told to use it. She uses it. But she hasn't really been trained on it. You know it's kind of you know how do you use it. Are there best practices. I don't proclaim to say that the pit is is a realistic view of how those things get rolled out. So but from your perspective, what are the best practices for that kind of training? Or even if there's like, yeah, not in the air on the day that the power's down, but other days.
00:12:20 Kenneth Harper: Yeah, yeah, yeah. I mean, take, take what you see on the pit and assume that's not the best way to roll this out, you know, to get successful adoption and make sure those, those outcomes are there. That's probably not right. You want to do. Um, yeah, it's, it's, it's really simple things. I mean, it's, you know, making sure you have the folks on the ground, you know, that that can go and talk to clinicians and get them set up. You know, Microsoft, we've taken a huge, um, we've made a huge investment in this on actually having a client success team that we send on the ground, you know, to work hand in hand with, with healthcare leadership, we know how important it is to walk the halls and make sure folks, those first couple of days, you know, get, get the help that they need. Because again, there's always some tips and tricks that you want clinicians to, to know to get the most out of the, out of the technology. It's not that hard. I mean, your usual, your typical clinician can get up and running in five, ten minutes, you know, but then how do you sort of optimize that experience for how that clinician practices their things that you can do by walking the halls to help them and answer questions. And so having a team on the ground, you know, working with a vendor that actually has the, the know how and resources of making sure that the success is there during, during the rollout. It's incredibly important. And so you're going to want to sit down with a clinician and carve out fifteen minutes where they're not interrupted. They're not in the middle of running from patient to patient. You want to sit down with the clinician five, ten minutes, explain it, get them set up. Um, go in and watch what they're doing. The first encounter, maybe give some tips and tricks on, you know, hey, if you just vocalize a little bit more because this is a copilot on your shoulder, it's listening to every word you say, you're going to get even a higher quality note or, hey, you have a special template that you want to use. Hey, did you know there's this tool in copilot where you can go in and tell copilot, this is how you like your exam findings captured? And there are all these little bells and whistles, you know, that, that we build into the product to really make copilot work for every, every clinician that that's using it. And it's important to work with an organization, have a team on the ground that can, can, can make sure all the power of the product, you know, gets, gets opened up, right?
00:14:26 Speaker 1: You're listening to digital health talks. When we return, we'll continue our discussion on how technology is revolutionizing healthcare delivery. Stay with us to hear more insights on creating sustainable, patient centered digital health solutions.
00:14:44 Megan Antonelli: You know, we hear so often, you know, this move from and they don't want these point solutions, right? So when I think about the power of kind of dragon and copilot together, that's, that's a really strong story. So tell us a little bit about that and tell me a little in terms of, does that also impact, you know, non-clinical functions like, you know, clinical documentation around like prior auth and revenue cycle? Where are those enter? Where are those intersecting and helping health systems?
00:15:12 Kenneth Harper: Yeah. Well, what I, what I would start is Dragon copilot, which are just our latest generation of, of Dragon. It is a comprehensive clinical assistant. You know, that really is, is how we've, we've designed it. It started many, many years ago, almost a decade, like eight years ago was when we had our first version of it. It started around documentation because that was the biggest problem to be solved, and where we know we could save lots of time and documenting something purely based on what you're doing and talking with a patient. And all those outcomes have been proved over the last several years. We save hours a week for clinicians just purely in their documentation time. But where we're going with copilot is there's so much more opportunity of how a clinical assistant can help you throughout the course of the day. You might need help with your orders. You might need help with diagnoses, you know, bringing more coding intelligence into the point of care where, hey, if you serve up a nudge, if there's something a little bit different that you need to capture in your documentation to make sure a procedure gets authorized for a patient, given their payer information, all these things are now beginning to be part of that one universal copilot experience that not only clinicians can use, but we also have it for other personas in the health system. We have a co-pilot for nursing where it's acting very similar. It's a natural language interface and can understand ambient conversation, but the work's a little bit different. What a nurse is doing is different from what a physician is doing. The data they need to capture some of the help that they might need throughout the course of the day, it's a little bit different. And so we think about Dragon Copilot as really it's a framework of point solutions that can be tailored to very specific personas, but it's all running as one sort of consolidated capability or platform, if you will. And so it's a really important aspect of the scale and the impact inside of healthcare. If you're working more as Dragon Copilot, is this broader set of capabilities, and then you can turn on certain features by the persona, it's really how you get the most value out of the out of the capability.
00:17:23 Megan Antonelli: Yeah, absolutely. And I mean, as we look at the health care system, it's, you know, I think the fragmentation and the sort of the siloed of the the departments and divisions is such a big piece of that. So that integration layer is so important. Um, you know, when we've seen that a lot in the, in the discussions that, that we've had, uh, around that. So tell me a little bit more about, you know, kind of where the next few years is going. Like, you know, you've been at it since, you know, over a decade now in terms of what, what's to come in terms of the programs that for the health care systems.
00:18:00 Kenneth Harper: Yeah, there are a couple of things I, I would say that get us really, really excited about where we're going. One, just to sort of segue from your last comment around consolidation, you know, we do view Dragon as becoming what we call internally the UI for AI, meaning it is a workflow that is already being used for a lot of your work, but now it's connecting to all your applications. It understands what you're doing in the EMR, understands what you might be doing in M365 understands all the clinical data that you might be working with. You know, a lot of folks tend to think that the clinical data you're working with only resides in electronic health record. That's one source of data. But you might also be going to a third party website, like up to date and looking at a clinical protocol of something that you need to follow for a diagnosis you haven't seen in a while. There are all these different sources and all these different applications. And Dragon is becoming this centralized natural language interface that connects you to all of it inside of one workflow. And so that's a big aspect of what we're now doing with Dragon. The other aspect is, and this has always been true from the early days of ambient documentation, this vision, which we're now actually realizing is how can we actually bring intelligence into the ambient experience because we now know what's happening between provider and patient while it's happening. And what gets us excited about that is if you think about what has happened in healthcare historically, all these best practice alerts and nudging systems and clinical decision support tools have always required data being entered somewhere before an alert might come into focus, or a nudge or a best practice of this is actually the right treatment plan for a patient that has these types of conditions. You have to talk to the patient, go put information into a system, and then these these alerts come to the foreground. And so alerting in healthcare historically has been retroactive. It happens after the fact. And what we're excited about with ambient Dragon Copilot and Ambient now running at scale, we're now understanding what's happening in the moment between provider and patient, combined with data we're pulling out of the historical record of the patient, how to use all that context and what you're discussing with the patient while the patient is in the room to bring intelligence in, serve it up to a provider while the patient is still sitting there and there's an opportunity to intervene. And so an example of this is in Dragon Copilot. Now there's we have an open framework where anyone can come in, any third party that might be building a really unique skill could plug into Dragon. One of the partners that's plugged into Dragon now is a company called Canary Speech. And what they do is they take that audio snippet that is in the ambient recording, because Dragon's running and we understand what's being discussed with the patient. They can take a snippet of audio. They run it through a series of, of models that they've, they've trained and they can bring back into workflow for the provider an indication of depression probability anxiety probability and also flag early signs of neurological disease. And so imagine someone coming in to primary care for an annual visit. You know, maybe they really aren't comfortable answering some of the survey questions that you get in your intake, you know, around your mental health and your feelings of safety. But this is a technology that goes through that because it actually looks at the audio of the patient's voice and tries to detect signals of depression. And by seeing that in workflow, while the provider is still talking to the patient, the provider now has an indication, hey, maybe you should ask a follow on question. Maybe you should nudge a little bit and see if this patient needs some help. And I've already heard one testimonial for someone that's using this in production that they had a grandmother come in and everything seemed fine. No issues on the the survey or the intake information. Everything was fine. It was an annual visit. Healthy. No major medical concerns. But because this was running as part of the ambient dial tone, they got an indication that the patient had high probability of depression. And so they just asked and nudged a little bit more. What was really going on? They actually went into a five minute discussion about the grandmother's son had just moved. She no longer has access to her grandchildren, which are a huge part of her life. And she was really struggling with it. And by having that conversation and knowing to nudge, to have that conversation, you're able to actually make sure that that patient's getting the help they need, you know, through some, some downstream referral therapy in this case. But this is one example of where we're going with Dragon and where we're going in healthcare is there's so much technology out there and so much innovation, but how can we bring that innovation into workflow in one consolidated place where we can begin to change care because we know what's happening between provider and patient, and we can intervene when there's an opportunity to talk to the patient or help the patient, or even just augment your decision making as a clinician with some piece of information that maybe you weren't aware of. This is how we're going to really start to see something like Dragon. And what we're doing with Dragon Copilot began to impact the delivery of care. And that's really what gets us excited about the future.
00:23:39 Megan Antonelli: Yeah, no, that's amazing. And that's exactly what is so exciting about it, right? I mean, the, the elements of, you know, reducing burnout and reducing time, you know, four hours, five hours, fifty hours, however many hours it is that, that it reduces, it is great and it's important. And in many cases, those hours shouldn't have been there. And the system is a bit broken. That puts it there anyway. And it's good to have a tool that gets rid of it. But the ability to actually practice medicine better and make them better clinicians is what's going to make them really love the tools and the patient, love the tools and the patient better, right? And it's just so it's so exciting to see that coming together. And I think that power of these tools to kind of create that infrastructure. Um, I love what you said in terms of the, the o, the o x for what, you know, UX for AI.
00:24:39 Kenneth Harper: The UI for AI is what? Yeah.
00:24:42 Megan Antonelli: I hopefully canaries not listening to my brain degrade in real time. But yeah, u I for AI um, but it is, you know, I think that's, it's, it's an amazing kind of layer of this that is, is so exciting. Tell me a little bit in terms of canary, is that embedded? Is it a partnership? How does how does that is it you turn it on. It's just.
00:25:07 Kenneth Harper: There. Yeah. What what we're, what we're doing in driving copilot is we're opening it up through a open framework, very similar to how you can think of an app store with your phone. We're not discriminating. Who can plug in, uh, anyone. And this is really the power of Microsoft and why we're excited about bringing this to, to market in that we're open. Um, and Dragon's already on the workstation of, of hundreds of thousands of clinicians. So how do we let the ecosystem plug their skill into Dragon and more of a self-service way, you know, where you don't have to go and try to do partner by partner, deal by deal integration, by integration, you have all these one offs. It takes forever to scale innovation. Instead, the idea of a marketplace is you open up what Dragon is in terms of how you can plug into it, and how you can get context from it, and then how you can plug some unique skill back in. And there's thousands of companies that, that focus in very certain areas of health care and revenue cycle management. You have companies that just do prior authorization and looking at guidance that you can serve up to make sure procedures are approved. There are companies that focus on inpatient guidance. How do you look at context about the patient and try to identify opportunities where you might be missing a diagnosis of something that like sepsis that you really need to be be aware of? There are companies out there that specialize in other aspects of coding, like in ambulatory. How do you make sure you're capturing the right information and based on the work you're actually doing, how do you make sure you're actually billing at the right level based on the work you actually did with the patient? There are other companies that bring clinical intervention. You know, Canary is one example, but clinical intervention around this is a clinical protocol that we know is a best protocol to follow for a patient that has these conditions that you're currently treating. There are hundreds, thousands of these types of companies out there in healthcare, but they're missing two things. They're missing one, what is the context? Of what's happening in real time when the patients in the room. And that's something Dragon can solve. And the second thing they're missing is how do you actually plug your skill into a workflow? That clinicians already using where you're in workflow and Dragon is also solving that problem. And so we really view this as opening up innovation at scale in Dragon by letting all these partners come in through a self-service ecosystem, and then the healthcare organization, they get to turn on or off very much like how you manage apps on your phone, but each healthcare organization can turn on or off these plug ins, these skills, if you will, based on the ones that are most valuable to them. And so it really is about self-service and scale to bring the most innovation to our healthcare clients.
00:28:00 Megan Antonelli: Oh, wow. And that, you know, I think it's, I've always thought about it from the sort of broader, you know, sort of integration with epic and, and the partnership with Microsoft. And that that is the, the power of this. But in fact, now you're also bringing in the power of this ecosystem of Microsoft partners that people can access through there, which then takes care of that, you know, sort of point solution problem, um, by, by creating a platform for the health systems as well. On both, both ends.
00:28:30 Kenneth Harper: Exactly. Right. And why that's also we think of it as the UI for AI, right? Because it's the thing that you talk to, the thing that you interact with that gives you access to the ecosystem of innovation, right?
00:28:41 Megan Antonelli: I need one for event production. Two, does Microsoft have that?
00:28:46 Kenneth Harper: We'll work on that.
00:28:47 Megan Antonelli: I know, but you know, and it is it's it's this sort of over, you know, we're in this phase of, you know, sort of hyper innovation adoption that is overwhelming. And I think it's overwhelming at an individual level and as at an enterprise level. And, you know, sort of the way that you guys are approaching it makes it at least manageable from, from that, um, that place for the health system. So, uh, I wish we had a little bit more time, but we're running out of time. We always like to end on, um, we have a segment called five good things. So in thinking about kind of what's good and what's great that's coming. What is your, you know, sort of, uh, most excited, uh, development that you see coming within healthcare, whether it's digital health or healthcare more broadly.
00:29:34 Kenneth Harper: Yeah, I think, I think the most exciting thing about what's what's happening in healthcare is AI is actually solving real problems. You know, this, this is not in a lab. It's not in pilot phase is solving real problems. And I think we're going to see this transformation. You know, I think this idea of becoming a frontier firm, a frontier AI firm, you know, in healthcare, I think healthcare is actually embracing it, in a way that maybe we haven't seen historically in health care, in terms of embracing technologies as early, um, healthcare, I think as an industry is really seeing the impact AI more broadly can have on everything they're doing, you know, care delivery, back office operations, all the different personas that they have, even front, front end workers, you know, in the hospital system and the patient experience, you know, thinking about someone calling in and trying to get help about how to navigate, uh, their care. AI is, is here in a way that's going to solve a lot of, of these issues. So I think when you see in the industry people talking about a frontier firm, I think what's exciting to me in healthcare is I think healthcare is actually for maybe the first time in a technology revolution, you know, almost be at the forefront, you know, of, of really having this technology solve some, some really meaningful problems.
00:30:54 Megan Antonelli: Yeah, that is, that is very exciting. And it is, it's an unusual place to be at the front front edge of innovation versus the the lagging behind. But, you know, to, to your credit, kind of being there early with Dragon, you, you know, have brought us brought us there. So tell our audience where they can, you know, sort of learn more and follow up.
00:31:15 Kenneth Harper: Yeah. If you go to Microsoft dot com slash health, you'll find out everything that Microsoft is doing in healthcare, inclusive of what we talked about today with Dragon Copilot.
00:31:25 Megan Antonelli: Perfect. And we'll put that link in the show notes too. Well, Ken, thank you so much for joining us. It was really a pleasure to learn about this. Uh, you know, in in greater detail. It's such an amazing thing. We have such a lucky opportunity to host our health impact forum at the Microsoft offices in New York. And, you know, it is a great opportunity where all the partners do kind of come and, and meet. So I hope we'll we'll see you there as well as some of our listeners, uh, October sixth and seventh in New York. And to our audience, thank you so much for joining us. You know, that was Kenneth Harper, general manager of Dragon at Microsoft. What was provided was a really incredible, useful map around clinical AI and where it is right now and where it's going next for our listeners. You know, I think the takeaways are pretty clear. The health systems are pulling ahead are the ones connecting AI to operations, not just to documentation. And you can think of the Dragon platform as the UA for AI, and that matters more than any single tool. And the case for optimism is strong. So if you like this conversation and you agree that this is the whole point, share it with someone who needs to hear it. Subscribe to Digital Health Talks and follow us on YouTube at Health Impact Live. This is Megan Antonelli, CEO of Health Impact Live. This is digital health talks. Let's keep fixing health care one conversation at a time.
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