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Welcome everyone to the Group Dentistry Now show. I'm Bill Newman and as always, we appreciate you joining us today. It's always great to have new guests on and returning guests, and we have a bunch on today. So I don't know if this is the most we've ever had on, but it's pretty much maxed out here. But a really great conversation I think we're going to have regarding AI in healthcare in particular. It's just such an incredibly topical right now and I think it's very confusing. And we're going to talk to the DSO leaders about just the inundation I think we have when it comes to AI. It's infiltrated everything. I think there's a little bit of overload in the industry. So we're going to get a really cool perspective here from Sarah Friar who's the CFO of OpenAI. So she's going to give us I think a really interesting perspective that we don't necessarily have. We kind of look at it from the dental and the DSO perspective. Sarah's going to give us I think a lot of really great... I know Phil and Rom and Jane we were talking before Sarah jumped on and we were excited to just listen in to hear what you have to say. So we have with us Sarah Friar, CFO of OpenAI. We have Jane Levy. She is the co-founder and CEO of Plan Forward, returning to the show. And also returning to the show is Phil Toe, president of the Smileist. And for the first time we have Ron Kinsky, CIO of SGA Dental Partners. So, welcome everyone. And with that, I am going to turn over the microphone to Jane. Jane and Sarah are going to have a conversation and then I'll be back on after that.
Thanks, Bill. That's great. I just want to welcome Sarah. She's someone who hardly needs much introduction, but she definitely has always impressed me. She brings this unbelievable deep financial expertise as well as operating leadership to the role of CFO. We watch you. You've got an incredible vantage point from where you sit and one of the clearest views into the market structure of AI and the future that your company's actively shaping. So I wanted to start today with a general high-level question. As we move from generative AI to agentic systems, how do you think the market structure is going to change? And in the context of today's discussion, obviously we have general models and they'll have to specialize to incorporate the particularities of verticals like dental. Some of the concerns that have been raised is how does an organization ensure that any training that it does doesn't necessarily benefit its competitors and that its data is siloed and protected so it doesn't violate something like HIPAA.
Yeah. So, Jane, first of all, thank you for having me on the podcast. Thanks everyone. Jane, I was delighted to get the call because it's really fun for us to get to go deeper into a whole field like dentistry. So first of all maybe just to set the scene and then I'll go to your question specifically, but right now we are seeing massive uptick. I saw a survey that said 60% of surveyed dentists are already implementing AI in their practice. They're using it for diagnostics, for treatment planning, but also for a lot of just the paperwork that happens right in any business. What we see in our data is over 5% of all ChatGPT messages globally, and we see billions every day, are about healthcare. About seven in 10 healthcare conversations, so 70%, happen outside of normal clinic hours. And so this is very real. Customers and patients are having a moment. They can use multimodal. Remember one of the amazing things about AI is you can turn on the camera and point it at a tooth or point it at anything that's going on and ask for some help, say what should I do, what question should I be asking of my dentist. And that is very, very real. To meet that moment, OpenAI launched OpenAI for Healthcare broadly speaking, and this was really to help clinicians support HIPAA compliance. So today for example in the hospital system we work with customers like AdventHealth, we work with Cedars-Sinai Medical Center, HCA, one of the largest hospital systems in the country, Stanford Medicine for Children's Health, the University of California, I could keep going. So, the answer is many, many large healthcare institutions are already trusting us because we're stepping up to things like HIPAA compliance. So, it's an essential tool. Dentistry is a high-impact use case and we're here to help improve what a dentist's life is like, not to replace it. So, let me go specifically to your question. So you're asking about I think the shift we're seeing which is we started in 2022, ChatGPT kind of burst on the scene. This is the beginning of generative AI and it was really call and response, system one type thinking. At the end of '24 we had another massive breakthrough in what we called reasoning and that actually started to help with some of the things we'd seen like hallucinations and so on. So reasoning shifted models into system two type thinking so they can think for a lot longer and with that ability to do a long-horizon task, because in tech we couldn't go far without a three-letter acronym. So a long-horizon task in this case, you actually started this dawn of agents. So you could actually give the AI a job to go do and just like the way you would give it to an assistant or to a personal helper, it would go off and take time and it would do that task. So '25 we said this is the dawn of agents. The first agent we have seen a ton of traction with is in coding, probably because coders are just naturally very tech-forward. And so that has taken off like wildfire and in fact our product Codex just hit about three million users just in the first three months of this year. And even I who haven't coded for about 30 years because as my kids like to point out I'm a dinosaur, I'm back to using a coding type tool but I'm using it for day-to-day tasks. And so when it comes to your question, first of all that's where the world is going towards. So I think dentists just like most other jobs in the environment are going to shift from something that just answers questions to something that will actually get real work done. And so in a dental practice that might be things like patient admin. So, as you all know, right, when you don't do that perfect follow-up, something falls through the cracks. It means that the patient doesn't get the information they need. They might not get the right follow-up care. It also can mean you're reminding them, so you have fewer no-shows, right? Your time is money. And we know, for example, that AI reminders are already reducing missed appointments by 30%. So, it's kind of like adding to the staff that might have made those outbound calls. Second side that we're seeing agents get deeply involved is going off and over a longer period of time reviewing an X-ray, reviewing the treatment plan and coming back and giving you the dentist high confidence in moving to faster treatment with more confidence overall. And what we've seen are proof points like diagnostic accuracy going up by 20%. And for me, what I get excited about is just in the end, it brings you all back to the job that you spent all those years training on, the thing you love. And probably the other piece is seeing patients get better. My brother's a doctor, so always talks about that moment where the patient actually gets better. And it gets you away from a lot of the admin and so on that probably takes a lot of your time and your money in running your business. And so that shift to agentic workflows is vital.
That makes a lot of sense. And so you're definitely seeing uptake of Codex etc. And which is great to hear. I think we're still at the very beginning stages obviously and we're still trying to figure out how agents will be used and how they'll change workflows in the practice. And you know so where would you frame this? Are we even in the first innings in terms of you know what this technology can do?
Yeah. So we are definitely just getting started and I realized you asked a question right at the end of your question too about data. So here's how I think it evolves with all the caveats that it's moving very, very fast. You're going to have these large foundation frontier models like OpenAI and there's not going to be that many of them in the world. In fact, you know, it's a much broader conversation than just today as we think about dentistry, but it's becoming almost geopolitical as well. So, there's China and then there's US-driven labs. And why are there so few? It's because the ingredients to make the model, they're very big and very expensive. It takes massive amounts of compute. It takes large amounts of data and it takes the best researchers in the world. And there are not tens of thousands of these people. They're literally thousands. So we're all trying to make sure they want to come and work in our model architecture. But on top of this, and I mentioned Codex, think of Codex as not just an agent for coding. Think of it as something that becomes, we call it the harness. So it effectively ties the model intelligence. So when we roll out a new model like 5.4 and we tell you how great it is, to the agent itself. And so one agent might be coding but another agent might be a dental CRM system. Another agent might be a call center agent. Another agent might be Excel for finance people. Right? So all of these things and they may be built specific but we are building agents that we're rolling out to customers but they also might be built by you yourself. And that's the important thing about something like Codex is it's turning us all into builders. So think of that large ecosystem of agents sitting on top. So for a large dental group or a small dental office, I think the winning architecture in my mind is working with a strong foundational model but then orchestrating on top. And this is where it's very important that you feel in control of your data. So your EHR integration, your compliance, your permissions, all of the domain tuning, that's still going to be very specialized. It's not going to be a generic chatbot just dropped into a clinic. It's going to get more and more specialized. And I think when data and privacy come into the picture, this is where you're going to get a lot more control. You need to make sure that your data is your data. Right? When we sell enterprise products, we do not train on your data. You explicitly can say I don't want this to happen. Now, some people say, I do want you to train because I want the general purpose model to get smarter. But I think in highly compliant environments like health, people tend to say no and want to explicitly keep that data very, very contained. And so that's how we see the world unfolding, right? Strong base model, probably a lot of APIs for bigger companies that might work on that. And then a harness that allows you to bring agents into your environment safely and securely, but also allows you to build in your environment. And by the way, I get super excited about this because smaller businesses, you know, who couldn't afford the big developer group who didn't have all the money to buy the engineers or to pay the engineers, like in particular, I work a lot with small businesses, right? The CEO of a smaller business, you're the CEO, the CFO, the CMO, the chief legal officer, the head of product, you're everything. Now you're being given tools that actually allow you access to the best in the business but under your direction and under your kind of constraints but specific to your business. Maybe just one final thought, I would think about it like an electric grid, right? If you think about power, the electricity coming is always something that resonates for me. So, we don't expect you all to go out and build a power plant for every dental office or every larger business, right? I know you have Smileist on here, right? They're large. Instead, we're building that and then you're going to plug into it with the specific thing that you care about like your workflows, your imaging, your scheduling. But we need to help you do that in a harness-driven way and that will be the product stack you see coming from OpenAI over the next 12 months.
Oh really interesting Sarah. So in terms of architecture then do you think that there is a move to on-prem from the cloud? And do you think so businesses like SGA and the Smileist that have grown through acquisition they have heterogeneous tech stacks and many are trying to move to standardize but that's a huge change management challenge. So if agents can then stitch together these API calls on the fly, maybe you don't need standardization.
I mean it's a great question and it's definitely a big debate right now. You know my background Jane, that I actually started my life as a Wall Street analyst. I covered software. So I actually made in some ways my career on the shift to the cloud. So I've seen these major tech shifts happen. Personally I don't think it's a full swing back from cloud to on-prem because there's just so much goodness in cloud computing but I think we are seeing a little bit more of a hybrid model emerge. So I think the cloud is still absolutely where most of the intelligence lives. Back to the point, right, these models are huge. They're being built on large compute fabrics in the gigawatt scale and so you know that's not going to live on premise. And if you want to get access to latest models, all the continuous improvement that we see like when something like reasoning happens as a breakthrough, again that's not going to happen on premise in any way, shape or form. So the cloud is still a very valid way for you to access things. That said, I do think that for organizations, you're going to more and more want to keep that sensitive data, the systems within your controlled environment. And in the old world where we had to standardize everything, right? You spend a lot of time if you were an inquisitive company for example trying to get everyone onto the same system. The great thing about this agentic layer is it has just raw intelligence to it. So it can actually, as long as it can get connectors into your system, it doesn't need everything to be perfectly the same. Let me give you a little bit of example from kind of my prior life, right? In a world of deterministic software. If you were a retailer and let's say you had an e-commerce business and an in-store business and I come into your store and I pay with my card and it says Sarah Friar, but then online I log in as S Friar and then somewhere else I create another account and now it's Friar S. I look like three different people, but in the next column over, you might see, oh, but it's all going to the same address. So, it's clearly the same person, right? A human looking. And I'll be like, of course, it's the same person. But in deterministic software, that was one of the complications is it couldn't think. So, it just looked at a table of rows and said, 'Oh, three customers.' And so, you spent forever doing these things that software did forever, which was trying to make sense out of the madness. The beautiful thing about intelligence is it's just like putting a human to it. Now you can do it at scale and that intelligent approach doesn't need the same degree of cleanup of everything. And so I think you're actually going to be able to live in a world of more heterogeneous outcomes because the agentic layer sitting on top, as long as it has connectors down into your system and context, it's going to be able to very quickly parse to get to the important data you all care about. I'll give you one other example just for me, right? I'm a CFO, Bill. I have a lot of systems that I sit on top of here at OpenAI and we spend a lot of time trying to do certain things. So, one of it is revenue recognition. So I have thousands of customers every single day. Most of that gets stored sometimes in a PDF, sometimes in a doc, sometimes in god knows what else. And I was building a team whose job was to read every contract to look for non-standard language. What we realized is we couldn't keep going on that way. Otherwise, we were going to have hundreds of people in our revenue team. And so we created an agent that opens up every contract at night, dumps it into, in our case, a Databricks table, and then it reads it looking for that non-standard language. So in the morning when my revenue team comes to work, they don't read contracts anymore. They're out of that business, which was mind-numbing. And nobody went to university to do accounting, to do that for a living. Instead, they come to work and they look only at the quote-unquote non-standard contracts where something has gotten inserted. The AI tells them why it's non-standard. It tells them what it thinks the next best step is. And for me, it gives me insights of what's happening inside my financial systems. Because sometimes the answer isn't about finance. It's about going to talk to the sales team. Like why are you inserting this clause? Please don't do that again. Or oh wow, something has changed in our business and customers are trying to buy a different way. We should have a new pricing system for them. So you can really get to the insight fast. I'm giving you an example as a CFO and clearly you all are the experts. I think the rest of this conversation is going to continue with true experts. But when you think about what is that same thing for a dental practice, right? When we think dentists, when you're the lay person like me, you think, okay, they've got to get to diagnostic and teeth right away. But it's a business. And so I suspect there's a lot of places where today what feels like dirty data that needs to be better standardized, you're not going to need to do that as much on premise because the intelligence layer is going to be able to do that in a much more kind of human way. Does that make sense?
Oh, so much sense. Very, very interesting. I could talk to you for hours Sarah, but one last question. Given the pace of change that you're seeing, you know, and you've got really a great seat into what's going on in the world. How long do you think it is before we are, you know, at a point where agents are running some of the workflows and we can trust that they're doing so successfully within, you know, any organization.
I mean, this is going so fast, Jane. I've never seen anything like it in my career. I think in the next 12 months we're going to absolutely see this happening. Right? If you think what's already happened in coding, so a year ago we started to launch our first autonomous software engineer which is like a big fancy term. Today the brand is Codex. And it is incredible to me to watch like even in really big companies like I have the privilege of sitting on the board of Walmart. Walmart when I talk to the internal tech team today, 60, 70, maybe it's up at 80% of all code is now created by tools like Codex so it's effectively created by agents. No human creates it now. It does mean that humans move into things like quality assurance testing, they move into compliance, they move into the inside piece but the actual agents are doing a lot of the underlying work. And I know very quickly, like we have not to pre-announce anything on your podcast, but we have some really interesting launches coming over the next couple of weeks for specific verticals. I can see what we're building in healthcare, even within the consumer app, so within ChatGPT we have a lot coming for just pure healthcare so that you as an individual can create your health data in your own project. So I'm kind of pointing over here because in my mind it kind of sits in the sidebar of ChatGPT. It's your data. So I find like when I go for my annual physical and now upload all of that outcome, I tell it to go back a year, back another year because I have three years of data. Finally got with the program about three years ago. And I say for me, Sarah, given what you know about me, my age, and so on, what's going well? So just talk in normal language. What's going well? What's not going well? What could be the conversation I should be having with my doctor when I go into review. And so I just find it so already acting like a personal assistant, but you know, this is coming fast. And I think the folks that get it are going to be blown away by how much it changes their business. I think the folks that don't get it may feel a little left behind. And I think throughout this whole change, like one of the things we need to do as an industry and as a company is to keep building trust. That's why I love to take the time and just come talk to real people about what AI can do for them positively and then what we're doing to make sure that we keep things safe and trusted.
Amazing. Thank you. Well, the thing I'm really excited to see, I noticed you were on the board of Consensys as well. I want to see what's going to be happening with the confluence of AI and crypto and what that looks like and I'm sure you're going to help shape that future too.
Thank you so much. This has been fantastic.
My pleasure. Thank you so much. Good luck with the rest of the podcast. Take care.
Well, that was great. Thank you, Jane. You're a natural as a podcast host. So that was a really interesting conversation with Sarah and I would love to get both Phil and Ron's take on what they just heard because you know we all from our seat yet it's moving really, really quickly and I think Sarah even acknowledges that she's even surprised by it. So that part to me was pretty interesting. But Ron, what were your thoughts on what Sarah and Jane had to say?
Yeah, I thought it was very interesting. It's a lot of what I expected to hear to try to, you know, focus us into... I like the focus on agentic AI, the solving the number one thing that I think more of us in dentistry need to really focus on, the compliance part of it and you know where's your data going. And you know in our day-to-day, I mean I think it's an odd day where I don't have the word AI at all in my day, right? It happens but it's very rare. And when we actually focus on this everybody wants to go, go, go and you know we usually have to talk about segmenting off, you know, where you're working on in the network and making sure that we have the right controls in place so the PHI and PII and other data can't get out of that network and be fed in. I think it's great to see that there's a lot of thought going into the security specifically for healthcare in the agentic AI piece. I'm excited about it because I do think up until now you could call some things that we have agentic AI. And I think, you know, some players in the market like Planet DDS are starting to edge into that space, but having OpenAI as a brand, you know, committing to the healthcare market is incredibly exciting.
Yeah, absolutely. You know, Ron, while I've got you a little bit since you're a newbie to the podcast, can you just give everybody a little bit about your background, short bio, and then maybe just get us all up to speed on SGA Dental Partners?
Sure. So, I'm CIO for SGA Dental Partners. We're today we're just under 150 practices. We are in the doing a series of acquisitions that's going to dramatically increase that as well. But my background, I've been at SGA for about three and a half years now. And first time in dental, so outside of here, prior to here, I was the CIO for a food management company. It's actually, I think this is my fourth CIO gig of my career. So, not new to being an IT leader, just learning dental and yeah, I love the space. I think SGA, you know, we're about 70% of our practices are kind of GP practices. We have specialty practices for the other 30%, mostly perio. But yeah, I mean, we're initially we were based in the southeast. We're really stretching the barriers of that, especially with some of the recent acquisitions. You know, we're becoming more of a national DSO. And so, yeah, prior to here, I was in food management. I did spend some time with an insurance company. I don't like to say that with dental companies. That's like I've gone to the light side of the forest. But you know, prior to that, I was in retail and as a CIO in retail, was a CIO in the construction business.
Thanks, Ron. And Phil, love to get your, you know, just your feedback on what you heard from Sarah and then also, you know, you've been on the podcast before, you're a vet in the industry, but maybe there's a couple people that don't know who you are. So, just a little bit on your background and yeah, get us all up to speed on what's going on at the Smileist.
Fantastic. Yeah, so you know, I'm one of the co-founders of the Smileist. We were founded in 2014. That was when we bought our first practice and we're up to about 116 locations now. So we're very focused on the Northeast. That's kind of where we like to continue to build and expand and you know we've been consistent. You know we had one of our biggest years last year. So we're very proud of the team and the company in which we've been able to sustain that growth rate even kind of as we've turned 12 years old. In terms of, you know, follow up on what Sarah was saying. Yeah, absolutely. I think, you know, we're seeing it ourselves in terms of how quickly AI is impacting the industry and even more specifically, the Smileist. You know there's almost like an endless list of opportunities in which we think we can use AI to improve the way we deliver patient service to the patients. And you know a lot of it is admin, some of it is clinical but when you think about like the overall workflow of a dental office there's a lot of things that aren't connected. Right. And so how do we leverage AI to connect it and then really be able to streamline a process that previously we could not kind of streamline before? And we are, you know, we envision us adding a lot of value because, you know, we have some very specific workflows and the way we do things. You know, perhaps we're at end of one. But being able to use these tools for us to move quickly, you know, I agree with her so much. It's been unprecedented. Nothing like we've ever seen in dentistry or even healthcare.
And Jane, again thanks for being the podcast moderator there at the beginning. What surprised you if anything from the conversation you had with Sarah and also just for the people that may not know who you are a little bit about your background and tell them a little bit about what Plan Forward has been up to.
Yeah, absolutely. So, I'll start there. So, Plan Forward actually celebrated its 8th birthday last week. I've been at the company four years. We do for those who don't know membership plans for uninsured patients and it is the one piece of software that our practices and groups use to generate ROI from day one. And so, you know, SGA is one of our biggest and best customers, they're using it to great effect and so just super proud to have both Ron and Phil on this podcast because I think what both of them are doing in terms of AI and the use of AI is quite on the cutting edge. So what surprised me with... it doesn't surprise me with what Sarah said, but I still think there is so much that's unknown and every week there are new changes and new breakthroughs and it's just hard to keep up and it's like drinking from a fire hose truly. And so we're thinking about ways to incorporate AI within our platform. But you know it's... and of course that's going to be revolutionary at some point not necessarily in our platform but just in the way it revolutionizes the workflows within groups and dental practices but I do think that the set of decisions that many DSO leaders have today are going to be completely different in 12 months from now and I just look forward to embracing that change.
And I think we're going to talk about that right now. Can I talk about what you know things just moving so quickly and how Ron and Phil are kind of dealing with that? So let's talk a little bit about... So now we're going to focus on dentistry and group practice in particular. We've got this labor issue that's been ongoing. You know, we thought for a while maybe it was a COVID thing. It wasn't. You know, it still continues on. So there are some AI solutions out there that have been really useful in kind of helping fill that, you know, certain issues when it comes to labor, whether it's at the front desk. I think even kind of freeing up clinicians when we talk about diagnostic AI, that can be helpful. But I'd like to, you know, that's one thing I think that AI can do well to a degree. And then of course we talk about data integration. We have all these different systems out there. They don't necessarily play nicely with each other. So can we use AI to really kind of pull data out of one, you know, whether it's a PMS and share it with another solution that we have or maybe we have patient engagement software and you know, how do we pull that data out? So Ron, talk a little bit about how SGA is using AI currently and how that's really helping you out, you know, and does it help with labor? Is this just something we think is helpful? That's another thing. We think it could be helpful, but is it actually helpful?
Yeah. I think from a labor perspective, probably the biggest piece that we've added is the voice AI. And you know, I think it's a little bit of a misnomer. It's not... I don't put voice AI under the heading of cost savings. I mean, we're really not unless you're actually overstaffed in your office, you're not likely to be able to reduce staff because you have an AI voice agent answering the phone when, you know, typically we do it when it's a missed call, but we have some places it's kind of a clinic disposition. They preferred it to answer first and it's working out great in that role. But it's really not... I mean it doesn't come down to being a cost solution for us because you know it really started a few years ago before we were even dealing with voice AI. We were dealing with text AI right and we were one of the first ones to really drive that hard. We're a very tech-forward company and so we really wanted to drive that hard and it started with a conversation with our COO Miles Mallister and I and I just you know asked the question well how much is a missed call worth? And you know, we actually sat down and kind of I'd say put pencil to paper, but it was really an Excel spreadsheet. But we figured out using a lot of fuzzy math because not all calls are about appointments and not all missed calls are going to result in losing a patient. But the answer was about a hundred bucks. Every missed call that every call that we miss at the office if it's not, you know, there's...
Nothing as a safety net behind that is worth about $100. So that's kind of where we started. It's more about putting revenue, retention, and keeping your books full. For us, it was really about, you know, there's a ton of voice AI out there. We used Reality Health and we settled on them in the sea of voice AI vendors out there only because they were willing to work with us and customize and optimize the AI the way we wanted it. We're not trying to replace, you know, we're not Dell computers with 70,000 person call centers, right? It's not a cost savings. And every one of these folks when you get on the phone within five minutes will start talking about what percentage of calls they can handle without handing it to a person. And I'm like, that is just the worst thing you could say to somebody who actually understands dental because that's not what we want. This isn't about reducing a person in the office. This is about making sure that every patient who calls in gets what they need right away. And so we have them optimized for patient experience. I mean, if you've ever seen trying to talk your doctors and your front desk folks into implementing this, every single one of them has been stuck in an AI that won't let them get to a human, right? This kind of hopeless loop that she gets stuck in. And so we found a vendor that was willing to optimize for patient experience and not for cost savings. And so by doing that, we were able to get that done. Now, we're using AI in a lot of different ways. A lot of the tools out there that have AI stickers on them are really just a sliver of AI against a really solid software package. The agentic AI is going to unseat almost all of them. So I think within, and I think it's going to start doing it very soon, right? You're going to start seeing it first in the areas where there are going to be great things in it. Like, I think Planet DDS is very forward on their agentic AI plan and their vision for that. But RCM tools, patient communication, we do a ton of that. We're starting to get a lot of data analysis. AI is way better at finding patterns in your data that could be opportunities for you than people are. And we've got a few vibe coding projects going on right now which we have to make sure we're managing well. Diagnostic AI, and we're even starting to mess around with some, we have a project right now that's kind of a pet project that is around visual AI. So massive restoration, being able to show somebody visually what the end result would look like. So right now most of our use is vended. We do have a handful of projects internally that we're doing that are kind of internally. But yes, I mean I think the biggest issue right now in building agentic AI, and OpenAI and others are going to learn the challenge as they get deeper into it, is understanding that we have these systems that were not built with modern kind of technologies, the ones that still have the market share. So your Dentrix core and even Dentrix Enterprise until it goes away, and your Patterson, all this stuff, all the Eaglesoft stuff, all Open Dental, these are really not built to natively ingest an AI. And so people have to find those solutions. And so when you have a DSO that has a ton of these things, keeping it integrated and keeping it running is going to be a big challenge. I think folks like us who are looking at trying to condense down into an enterprise PMS, which will be a huge difference for that. So sorry, I think I went on a little long. I'll give Phil a chance.
