The Future of AI in Dentistry with OpenAI's CFO, The Smilist's President & SGA Dental Partners' CIO

Welcome to the Group Dentistry Nail Show, the voice of the DSO industry. Join us as we talk with industry leaders about their challenges, successes, and the future of Group Dentistry. With over 200 episodes and listeners in over 100 countries, we're proud to be ranked the number one DSO podcast for the latest DSO news, analysis, and events. And to subscribe to our DSO Weekly E newsletter, visit group dentistrynow.com. We hope you enjoyed today's show. Welcome everyone to the Group Dentistry Nail 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 almost maxed out here. But a really great conversation. I think we're going to have regarding AI in healthcare in particular. And it's just such an incredibly, it's so 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 Fryer who's the CFO of Open AI. 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 is going to give us, I think a lot of really great, I know Phil and, and, and, 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 a Sarah Fryer CFO of Open AI. 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 smile list. And for the first time we have Ron Kurenski, CIO of CGA dental partner. So welcome everyone. And with that, I am going to turn over the microphone to 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 embraced 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 is actively shaping. So I wanted to start today with a general high level question. As we move from generative AI to agentex 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 specialise to incorporate the particularities of verticals like dental. Some of the concerns are that have been raised as hard as 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 hip-hop. 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 questions specifically. But right now we are seeing massive uptick. I saw a survey that said 60% of survey 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 chat-cheap team messages globally and we see billions every day are about healthcare, about 7 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 out of tooth and 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, open AI launched open AI for healthcare broadly speaking. And this was really to help clinicians support hip-hop compliance. So today, for example, in the hospital system, we work with customers like Adb and Health. We work with Caesar's 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 hip-hop 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, chat, GPT 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've seen like hallucinations and so on. So reason I 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 along 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 encoding 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 misdeployments 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 in over a longer period of time, reviewing an x-ray, reviewing the treatment plan, and coming back and giving you the dentist, high confidence, and moving to faster treatment, both more confidence overall, on what we've seen are proofpoints 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 spend all those years training on. The thing you love, I'm probably the other pieces is seeing patients get better. My brothers, the doctor, so he 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 a genetic workflows is vital. That makes a lot of sense. And so you're definitely seeing uptake of codecs, 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. So where would you frame this? Are we even in the first innings in terms of 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 to a bad data. So here's how I think it evolves with all the caveat 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, 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, it's 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 thousand. So we're all trying to make sure they want to come and work in our model and 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 were all at 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. So all of these things, and they may be built specifics. 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 it's going to 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 HR 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 house, people tend to say no, I 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, who couldn't afford the big developer group who didn't have all the money by the engineers or the pay the engineers, in particular, I work a lot with small businesses, right? The, you know, as 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 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, it was always something it resonates for me. So we don't expect you all to go out and build a power plant for every dental office or every dental larger business, right? I know you have smile list 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 stat you see coming from OpenAI over the next 12 months. 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 smile list that have grown through acquisition, they have heterogeneous tech stacks, and mainly 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, we see that 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 in a positive company, for example, trying to get everyone onto the same system. The great thing about this agentech 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, "Sara Fryer." But then online, I log in as S Fryer at. And then somewhere else, I create another account and I'm Fryer-S. It, 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 it's 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, it's just like putting a human to it. Now you can do it at scale. And that kind of intelligent approach doesn't need the same degree of like cleanup of everything. And so I think you're actually going to move 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 contacts, it's going to be able to very quickly parse to get to the important data that you all care about. I'll give you one other example just for me, right? I'm a CFO. I have a lot of systems that I sit on top of here at Open AI. We spend a lot of time trying to do certain things. So one of it is RevRack. So I have thousands of customers every single day. Most of that gets stored. It's 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 an RKSA 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 recontracts anymore. They're out of that business, which was my 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 "non-standard" contracts where something has gotten inserted. The AI tells them why it's non-standard, 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, "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 inside 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, when we think dentists, when you're the layperson 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? Well, 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, 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 at a point where agents are running some of the workflows and we can trust that they're doing so successfully within any organization? I mean, this is going so fast, Jane. I've never seen anything alike it in my career. I think in the next 12 months we're going to absolutely see this happening. If you think what's already happened in Codan, 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, even in really big come 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 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 the rent. Healthcare. Even within the consumer app. So within chat GPT, 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 chat GPT. 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. And 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're on the board of consensus 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. Never dole. There were 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 really interesting conversation with Sarah. And I would love to get both Phil and Ron's wake on what they just heard because you know we all from our seed. Yeah, it's moving really, really quickly. And I think Sarah even acknowledges that. She's even surprised by it. So that's that part to me was was pretty interesting. But Ron, what were your thoughts on what Sharon didn't have to say? Yeah, I thought it was I thought it was very very interesting. It's it's a lot of what I expect expected the here to try to you know focus us into. You know, I like the focus on a gen A. K. I. 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 it's an odd day where I don't have the word AI at all of 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, the where you're working on the network and you know and making sure that we have the right controls in place of the P.H.I. And other data can't get out of that network and be fed in. I think it's it's great to see that there's a lot of thought going into the security specifically for health care in the agenda. I peace. I'm excited about it because I do think, you know, up until now, you know, you could call some things that we have a gen K. I. And I think, you know, some players in the market like plenty of us are starting to edge into that space, but having open AI as a as a brand, you know, committing to the health care market is incredibly exciting. Yeah, absolutely. You know, Ron, what while I've got you a little bit in such a newbie to the podcast. Can you just give everybody a little bit about, you know, your background for bio and then maybe just get us all up to speed on SGA dental partners. Sure. So I've been I'm CIO for SGA dental partners were today were just under 150 practices. We are in 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 was the CIO for a food management company. Actually, I think this is my fourth CIO gig of my career. So not new to being an IT leader just learning dental and I love the space. I think SGA. You know, we're about 70% of our practices are our kind of GP, you know, practices. We have specialty practices for the other 30% mostly perio. But yeah, I mean, we're initially we were based in the southeast were kind of 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 prior to here 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 I've gone to the lights out of the forest. But I, you know, prior to that, I was in retail and as a CIO and retail was a CIO and 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 your your 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 the speed on what's going on at the smile. And fantastic. Yeah, so, you know, I'm one of the co founders of the smile us. We were founded in 2014. That was when we bought our first practice when 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, and, you know, we've been consistent. We had one of our biggest years last year. So we're very proud of, you know, the team and the company in which, you know, we've been able to sustain that growth rate even kind of as we've turned 12 years old. And so, in terms of, you know, follow up on what Sarah was saying, yeah, you know, absolutely. I think, you know, we're seeing it ourselves in terms of how quickly AI is impacting, you know, the industry and even more specifically, you know, the smile list. You know, there's almost like an endless list of opportunities in which we think we can use, you know, AI to improve the way we deliver patient service to, you know, 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, you know, dental office, there's a lot of things that are, you know, what, like she was alluding to, you know, 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, you know, we could not kind of streamline before. And we are, 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, 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, you know, we've ever seen, seen in dentistry or even health care. And Jane, again, thanks for for being the podcast, the moderator there at the beginning. What surprised you with 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 is been up to you. Yeah, absolutely. So I'll start there. So plan forward actually celebrated its eighth 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 on this podcast because I think what both of them are doing in terms of AI and the use of AI is 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 you know breakthroughs and it's just hard to keep up and it's like drinking from a fire host truly. And so we're thinking about ways to incorporate AI within our platform, but you know it's it's and of course that's going to be you know revolutionary at some point. not necessarily an art 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. We thought for a while maybe it was a COVID thing, it wasn't, you know, it's still continues on. So there are some AI solutions out there that have been really useful and helping Phil that 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, so that's one thing I think that AI can do well to a degree. And then of course, we took 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 is that, does it help with labor? Is that, is this just something we think is helpful? That's another thing. We think it could be helpful, but is it actually helpful? Yeah, yeah, I think, I mean, 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, I don't put voice AI under the other 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 miscall, but we have some places. It's kind of a clinic disposition. They prefer 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, you know, kind of a text AI, right? We were one of the first ones to really drive that hard. We're very tech forward company and so we really wanted to drive that hard and started with a conversation with our COO Miles McAllister and I just, you know, asked the question, well, how much is a miscall worth? And, you know, we actually sat down and kind of, I'd say a 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 miscall, not all miscalls are going to result in, you know, and losing a patient. But the answer was about a hundred bucks. Every miss call, the every call that we miss at the office, if it's not, you know, there's nothing as a safety net behind that, it's worth about a hundred dollars. So that's kind of where we started. It's more about putting revenue that you, that, you know, retention and about keeping your books full, right? And so for us, it was really about, you know, like every, you know, there's a ton of voice AI out there. We used morality health and we settled on them in the, 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 with in five minutes, we'll 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. Like this isn't about producing a person in the office. This is about making sure that every patient who calls in gets what they need right away, right? And so we have a optimized for patient experience. I mean, if you've ever seen trying to talk your, 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, you know, we found a vendor that was willing to optimize for patient experience and not for cost savings, right? And so by doing that, you know, we were able to get that done. Now, we're using an a lot of a lot of different ways, you know, a lot of the tools are out there that have AI kind of stickers on them are a really just like a sliver of AI against a really solid software package. The adgenic AI is going to unseat almost all of them. So I think, you know, 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, you know, they're going to be great, you know, great things in it. Like, you know, like, I think Planet VDS is very, very forward on their agentic AI plan and their vision for that. But RCM tools, patient communication, we do a ton of that. We do a lot, we're starting to get really a lot of data analysis. You know, AI is way better at finding patterns in your data that could be opportunities for you than, than, than people are. And we've got a few vibe coding projects going on right now, which, you know, we have to make sure we're managing well the agnostic AI. We're even starting the 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 a genic AI and, you know, open AI and others are going to learn the challenge as they get deeper into it is that, you know, understanding that we have these systems that were that were not built with modern kind of technologies. The ones that saw the market share. So your Dentrix core and, you know, even Dentrix Enterprise until it goes away and you're, you know, your Patterson, all the stuff, all the Eagles off stuff, you know, all open dental. These are really not built to, to natively do, you know, ingest in a in AI agent. And so people have to find those solutions, right? And so when you have a DSO that has, you know, a ton of these things, you know, keeping it, getting it integrated and keeping it running is going to be, is going to be a big challenge for that. I think folks like us, I think we're looking at kind of trying to condense down into an enterprise PMS, which will be a huge, huge difference for that. So sorry, I think I went on a little long, I'll give a full of chance. Yeah, that was great. Go ahead, Phil. Yeah, no, I would say the way we think about it is, you know, not so different, a bit of even what Sarah alluded to where it's about, you know, the evolution is kind of getting information versus actually doing things. And so I think what has characterized largely kind of dental or dental software has largely been kind of these point solutions. We can do this one thing, you know, or maybe a small handful of things and do it really well. But then, you know, they don't necessarily talk, you know, across. And so our vision and what we're working towards is really kind of building agents that are a teammate, you know, how can it operate more like a person because it does have these reasoning capabilities. And so it's not necessarily, hey, you know, I do, you know, insurance verification well or status saying or even payma posting well. But how do you have that, you know, let's say an RCM teammate that actually has context and understands and then is able to reason like a person would to improve that process, you know, okay, you know, we're getting denials. Why are we getting denials? How do we move up that, you know, that information chain or that process chain to really understand why what's causing those. And then ultimately fix itself. It becomes this kind of self-healing kind of system, which is kind of, you know, how, you know, our current team works things now. You know, they figure out what's wrong and then and then fix it and then, you know, and then monitor and then find new things. And so, so yeah, so it is very much like that. But, you know, someone to what Ron was saying, our thinking is not necessarily, hey, there's like some cost savings. So we're in a very fortunate position where we continue to grow at a rapid pace, both kind of through affiliations, as well as organically. And what we've been able to do is just really make our existing team much more effective because they have these kind of AI teammates that are doing lots of work for them. So oftentimes it starts out quite small, you know, and then over time it kind of begins to grow. But what's great is it just, it has that reasoning and it has that context to be able to cut across, you know, all the different functions. So again, it's not so much, oh, this is an R.C.M. Department type activity and then it kind of stops there, but it's able to cut across all departments because all different departments end up touching, you know, that that patient experience. experience. So for us, we're super excited about this vision. And then even when melding of a bit of the labor and the people versus the systems, you know, Ron J. and I were adding a lot of things, what if the whole concept of like, let's say a PMS doesn't actually, you know, need to exist because when you meld, you know, when you think about like that practice management system, it's an interface to, you know, a set of information and data, right, that we have in it and has some implications in terms of the workflow. And then you have these AI organs that are able to reason and do things. And then they don't necessarily need that interface. And so moving forward, you know, Ron, you know, alluded to kind of vibe coding. What if there is this future where, you know, a lot of software and means are kind of just one, it's both the software and the labor that gets almost created on demand or at least in a very short period of time, that's very customizable. So instead of, you know, the historical view of hey, we create this piece of software that serves many. Now, you know, there can be a lot of custom development of software that's just for one particular kind of customer, you know, for that company. And the cost of that is, you know, come down dramatically. So I think, you know, possibilities like that are super interesting in terms of how it impact, you know, the dental and even the healthcare industry broadly. And I think when we kind of look at how quickly it's moving and how it's going to affect what people's responsibilities are, right, in certain roles. And I, how those are going to change. I mean, I think the most obvious is the front desk person and how that role is really going to change because a lot of times they're handling things that AI can do now or seems like they can do, you know, in the pretty much near future. So things like, you know, the talked about answering the calls or, you know, scheduling or even, you know, something in the revenue cycle management, you know, whether they're taking payments, you know, a lot of that can be now handled by AI. So when you run out, I'll put this to you first. Are you evaluating, you know, how responsibilities and roles are going to change and are like our new positions being created almost where it's not a front desk person, but maybe that role looks totally different. Yeah. I think, and I think it actually, probably the bigger, the bigger impact of that is going to be, you know, rolling all the way back into operations, right? And so we, you know, at SGA, we're tech for it because we have operations team. We have an operations leadership team that is very tech forward, like all the way down to every, just about every director level and above, right, are always looking to iterate on that patient experience. But I think, you know, it's definitely going to change. If I think that my vision of this and I hope it's not a hallucination is that my vision is that it's going to change the front desk to be much more focused on the patient experience, the conch ears of the patient, making sure the patients feel heard and cared for, right? While they're at the dentist, I think, you know, what's interesting when most people talk about AI, they talk about all the stuff that AI can do and how it's going to take over. I do not have a vision of one day having an office where you walk in and you interact with an iPad and go see yourself in an operating. I mean, maybe that'll happen at some point in the world, but I think that that really passes over the system that really is the value ad for all of our clinics, which is, you know, that human interaction, that touch, AI can help us to get that. I do think that, you know, I'm one of my best visions of the future and it's something we're actually just starting to play with right now as an idea is that, you know, we solve the problem where we put so much on the office, you know, that they really just can't handle it. So I think, you know, we have one of the best provider retention in the industry if not the best, but, you know, kind of don't ask me about the front desk, right? Because everybody has that problem. They're competing against, you know, a lot of other jobs at that level. And so, you know, when you have people come in and you train them, you get somebody perfectly training, they leave in eight months, you're back to square one, right? Doing it again. And I do think that the vision is to stop making their lives so difficult. We make things very complicated. We have what I call the three compounded fallacies of clinic level reporting, right? Number one, we think that people are reading all these reports, so we send to them and they're not. And then number two, we think that they're going to make the same judgment after reading that report that we in headquarters would have made. And they're definitely not, you know, and then number three, that they're going to make, they're going to take the same action that we would have prescribed if we were in their shoes, right? And they're not. I think AI has the ability for us to flip the script. And I hope this is something that comes in the next, you know, a couple of years at SGA, but the flip the script on that and stop giving people reports all together and give them action lists, right? Like tell them what to do. And if I give you a list that says, call this patient on the phone and confirm with them and do this and do this and do this, you know, these are the things you have to do to satisfy your patients and prove a profitability. You know, we can manage against a list, right? It should not feel like air traffic control when really it's a to do list. And I think if we can get into that mode, AI can help us get there and AI can help us iterate. So if you think about the value of a DSO in general, I think the value, the real value of a DSO is to, you know, improve same source sales, right? And so are you better with us? Are you more profitable because you're a part of our DSO or not? And anybody who can't answer that question affirmatively with really good answers is probably not a good DSO. So I think we, you know, AI is like the next wave of how we do that, the reach of our operational leadership into what happens directly translated into the offices is going to be dramatically impacted by AI, I think in the next few years. And Phil, maybe I'll kind of position the question a little bit differently for you. If you're going to hire five key people, say in the next two years, what would those roles look like? And is that different than maybe what you would have thought a year ago? Absolutely. You know, I totally agree. I think, you know, there's been a lot of rhetoric around how, you know, AI is going to replace and take jobs when it's my view that it's actually going to kind of create a lot of new jobs. And this is kind of like the crux of your question, right? So the five people is not necessarily five of existing positions, but of new positions. And so, you know, again, it's earlier we talked about, you know, knowing what are some of those like specific industry specific, you know, whether it's institutional knowledge, whether it is kind of a process and workflow, or just kind of the specific nuance of a particular function. And so I think, you know, the next five are going to be, you know, process experts. They're going to be product managers. You know, when you think about a DSO, you're like, "Wait, that's kind of crazy. Why would you have a product manager?" But that's, you know, we have some of those roles now. You know, we have somebody that's responsible for insurance verification. And that's what she thinks about, you know, the question we ask ourselves frequently is, you know, when we have a problem, we say, do we have somebody that wakes up in the morning and thinks about that particular problem? And when we answer, when the answer is no, we're like, "Okay, you know, we're going to know why we have that problem?" Because nobody's actually owning that particular thing. And so I think more and more, we're going to have these types of roles, whether you want to call them product managers or kind of process experts, they're going to know these really well. Plus, they're going to be very comfortable with that technology, right? You know, Sarah alluded to, they're going to be people who kind of get it and adopt it quickly. And then they're ones that we're going to be, you know, slower adopters. We see ourselves very much in the early adopter phase. And we're very willing to experiment. And that is very much like the role of that product manager is how to push that along and not have all the historical context of how something was being done to impact how we are using AI to reinvent it. So, you know, whether it be, "Hey, Amazon said, "You know, we're going to do prime and we're going to deliver very quickly and then subsequently added all sorts of services." Somebody, you know, owned that. And so for us, we want various, you know, product managers to own specific functions and really be able to build and reinvent together with AI. Let's talk about the privacy and hippocompliance aspect of AI. We're in an industry where there's a a ton of sensitive data that that we get from patients and have to really protect that. And it's getting to some murky waters with AI solutions. And I always think about somebody at a front desk, maybe going and taking, even something as simple as creating a letter to send to a patient and putting that into chat GPT just to kind of make it sound better, right? Or present better. And all of a sudden, what kind of data have I shared publicly, right? So that's just one thing that comes to mind. So maybe talk about Phil, you can start this off. How are you kind of handling that issue? - Yeah, absolutely. So I would be remissive. I told you we figured it all out. And this is exactly how we do it. And we are exploring it. It's certainly something that we're very sensitive of. I would say one of the first steps is making sure that we have the appropriate licenses so that we don't have a lot of personal licenses of people that are out there trying to do something with the information. We have published kind of policies and guidelines to say for certain things, it's okay and certain things that are not. And it's not so, particularly if you're not technical, there's a lot of technical aspect kind of to it. And so for us is making sure that I'll say the right people are involved so that we don't have, it's very easy, right? Hey, I can just kind of start whatever vibe coding something and not realizing that I'm sharing information that I shouldn't be sharing. So we try and do it in a very kind of more collaborative way so that people do know, hey, this is what's going on. And we hold each other kind of accountable to those privacy standards that exist within healthcare. And then other things, I would say, because of that, we've built some solutions that are very kind of maybe like round about, so that we're doing things a bit more locally than we would otherwise so that we can kind of maintain that security. But yeah, I would say that it's something that we continue to learn and adapt to particularly when the industry is changing very quickly. Let's talk a little bit about rolling out technology solutions and we can obviously were focused on AI right now, but I think technology and AI are almost synonymous now, or I, it seems like it anyway. I guess maybe Tyran's point earlier, maybe not, because you talked about some of the, you know, maybe the older PMS systems that really don't work well with AI or it's not something it's easily used. But this is always one of those, I think, challenges where you've got a really great solution and Jane, maybe you can even chime in here, because I think it's, we hear great products, right? Really, the offering, whatever it is, can be a great, great product, but if there's not a, the company doesn't have a great implementation and roll out solution, then it doesn't matter. So we can may never great solution, but if we can't educate, right, and train all of our locations on a solution, then it fails. And I think there are some really interesting AI specific statistics out there that AI implementations, and this is across all industries, more often than not. And I think it's somewhere in this 70% range, either stall or fail within the first year. So great solutions can implement them, right? So then is it really a great solution? As you can't use it. Just talk a little bit about your strategy run when it comes to, you know, hey, we've got AI, we want to roll it out, do we start with one location, do you start with like a, how do you do that? How do you ensure that that really, you know, is something that, you know, is working out for you? - Yeah, I mean, we always, we're, you know, SGA is a king of pilots, right? We do a lot of piloting and, you know, typically, you know, we hand pick something we think is gonna be a good fit for that and we'll pick, you know, usually, pilot usually starts with one very quickly, goes to three or four, right, lip clinics, because we want to have a little bit of a hedge in our bet that we don't just have a kind of a personal situation there. I mean, I think, first of all, good AI vendors, love scale, bad AI vendors are afraid of it. One thing I would caution you on though, there's so much competition, especially in certain parts of AI, like not so much a genic right now, but like for sure in voice and a few others, that, you know, I'm kind of, I kind of have a reputation for being a really good negotiator, but you can over negotiate very quickly. Like you can put your, you can put an AI, I would caution you not to allow an AI vendor to strike a bad deal, a deal that's bad for them, because what'll happen is they'll just, they'll end up having to make adjustments that will affect quality on the other side of it, so the thing you pilot is not the thing you roll out, right? And so, but we usually do start with a small group and we'll iterate and we'll make sure that we had it right and that we're kind of firing on all cylinders and there's a lot of, you know, iteration, if you look that the product we have today versus the product we had, you know, when we first started, you know, and the patient, patient communication side, it's like night and day, it's not the same product. So, we wanna make sure we have people that are willing to be on the bleeding edge in those early pilots. And then the biggest thing, you know, well, two big things I'll add is that we're SGA is one of our core tenants, does clinical autonomy, anything that affects clinical autonomy, we give our, our doctor's the ability to opt out of a lot of things, you know, where it makes sense. On the flip side of that, it's more of a pull. So, when you show your doctors the proven effect in the numbers, right, this is going to, you know, answering these calls is gonna result in this many more bookings, a fuller schedule for you, you know, or we show them the effect that it has, especially for their patient, because the doctors really do. Most of them really do care about the patient experience more above all else, right? And so they'll stand, if you show them the value they're gonna get, they'll stand in line for it. You don't have to like ask them and push them and, you know, but be aware that like, local works for 140 practices might not work for 10, and that's okay. You have to be willing to, to be okay with it. - Phil, how do you roll things out at the smile list? - Yeah, we agree, roll things out kind of very similarly. I think this is just one of those like lessons and change management, right? And making sure that, you know, the people that it's impacting that they, you know, that they understand like the why, and perhaps even being, you know, part of the decision. So, you know, a lot of times they don't, they don't particularly like it when things are kind of being pushed down to them, you know, at the, at the corporate level without having their input, and really kind of understanding how, you know, things work, you know, their, their individual workflow. And when you're able to demonstrate that, and, you know, kind of going down the pilot route, and then, and then kind of a broader adoption, those all, you know, they all make sense, but it's all in the execution, right? I think, you know, you'll, it'll be hard for you to find any DSO that they're gonna say something too dramatically different, but it's all in the execution, making sure, you know, the right people are out there getting feedback, making sure that they're involved. There's kind of good collaboration between, you know, the company, or as Ron said, you know, to not overnegotiate something, and then, then you don't quite kind of get the same, same product. So, so it's in the, the thousand little things in terms of managing change, as opposed to, you know, the big broad thing of, oh, you know, we're gonna do a pilot and then go from ex locations to Y locations and in broader role that. I would say, you know, when I look back, the ones that have been successful is where we've gotten, you know, a good number of the team engaged, and where they understand the why and kind of vested in the success of it, because it impacts them. - Yeah, I can add a bit to also, you know, they say history repeats itself or history rhymes, I guess. And I remember the Royal Art of Internet 1.0. Only people thought it was first, you know, a marketing tool, so they would put up these static websites that you couldn't click through on. And then, you know, most companies abandoned that idea because it wasn't particularly impactful. And then came, you know, hypertext links that you could click through. And so, you know, we all think iteratively, we don't, it's hard to see around the next corner. And so the current implementations of agents are going to look, you know, really juvenile in six months. So I think tech changes so fast. And so you might try something, find it's not completely impactful, abandon it, but that does equip you really, well, for the next time to try again, when that new tech comes out or that new workflow needs to be automated, you've already got all the learnings from the original implementation. And so I think that's just how tech gets adopted, kind of in a step, step fashion. And I think we'll see that later too. - Yeah, that's a great point. As we wrap things up here, if this could be like a three hour podcast, there's so much to discuss. And of course, then in six months, we'd have to do it all over because things have moved that much quickly, right? So maybe we'll do this in six months, but. build versus buy versus partner. And I think Ron kind of touched on this when he talked about, was in reality health, where they were a partner that was willing to create something custom for you. So you've got organizations like that that'll work with you to kind of create custom solutions. There are probably some that are a little bit more out of the box. This is kind of the offering and you kind of get what you get, which could be good for certain things. And then now there's the option to do your own coding and build things in-house. So talk about kind of what your strategy there is, Ron. - Yeah, I mean, I think, I mean, we do a lot, we do quite a bit of both, right? And so it depends where the money is, right? I think if we're trying to make a decision on building something ourselves, I mean, it's the barriers lower, right? Because we can do some pipe coding with vibe coding. I'm just like, people get very excited about it. I just want to like put a little caution out there that code is not always really good. It's not always good architecturally. It's not good for scale and it's not necessarily good for security. And there's a lot of, so anytime you do a vibe coding kind of scenario, which I think is a great thing to do, whenever you do that, it is smart to get a real developer to review that code and help iterate, help the LLM kind of iterate through the code to make it secure and compliant and scalable. I think that that's kind of an important thing. So when we do this, we're at the very early part of this. I think another big part for us is, you know, when you have something like what OpenAI is coming out with for the medical group and we can get a BA and it kind of describes where data, you know, how our data will not be used. I think you can get away with a little bit more. I still feel more comfortable with the local models and having it in a secured area where, you know, I know what's going in and out and we have like controls on even, you know, anything that looks like PHI shutting it down on the way out of it because, you know, ultimately, these are tools that can have massive value, but that can also be tools of massive, you know, uncompliance, right, very quickly. And it can go from zero to very, very uncompliant, very quickly. So we're a little bit careful about that, but I think from whether we bring it in-house or outside, it always comes down to like, is this a real competitive advantage for us, right? And how much is it going to cost to get it there? Because if it's going to cost us, you know, I mean, there's the reason why there's so many voice AI agents out there or voice AI vendors out there is because it's all built on the back of these libraries that already exist and, you know, anybody can stand one of these things up fairly quickly. To get that model right takes a lot of money, right? A lot of time, a lot of energy. And so it's not worth it for us to try to recreate something like that, but is it, is there something that creates competitive advantage? And I want to create something that, you know, I don't want my competitors to be able to immediately imitate we're probably going to look to bring that in-house. - Excellent, Phil, your thoughts? - Yeah, so for us, I'm going back to my comment earlier about, you know, what do we think of? - Well, we wake up in the morning. I can assure you, we don't think of building software. And so I would say that, you know, the vast majority of our efforts are around partnering up with the right companies externally that can help us realize the vision that we have. So, you know, again, similar to what Ron said about, you know, some of these startups, they're wonderful to work with, you know, they're very nimble, they're quick, they're, you know, they're like drinking from a fire hose, really understanding, you know, both the industry as well as a smile specific requirements. And so those are the companies that we really like to partner up with, you know, to build our solutions. There's some, you know, small internal projects here or there, but again, we don't view that as our core competency. And so, you know, while I may address some, you know, more, I'll say perhaps probably focus more on internal needs, as opposed to something that's kind of enterprise grade, scalable, secure, that are more for external needs. Those, you know, we want to partner up, partner up with the pros. - Makes, makes a lot of sense. Okay, it's a great conversation. There's a lot here, Ton Pack for sure. Contact information from everybody. If Jane, thank you so much for bringing everybody together. First off, and thank you to plan forward. That has been a really great conversation. And I think, you know, the clouds are starting to part when it comes to understanding AI. So I'm actually, you know, I feel like I'm understanding it a little bit more. I think the industry is starting to find use cases for it now where it was a, but there's still a lot of overload, right? A lot of options out there. And I think you could get overwhelming. You talked about roles in the future. I mean, you could have somebody that could just be out there to evaluate technology solutions or AI solutions for you. That could be their only job. They probably never get to the point where they'd be able to evaluate everything. So Jane, how can people learn more about plan forward and how can they connect with you if they want to? And then we'll get to Ron and Phil on your contact info as well. - Yep, great. So it's just planforward.io. And I'm just J-L-E-V-Y, they will be a fan for you. - Thank you, Jane. - Ron? - Yeah, SGADental.com for SGA. And my email is just R Karinsky and SGADell. - Thank you, Ron and Phil. - Yep. - Simple, Phil at the Smilest. - Excellent. All right, and it's at Smilest.com, right? - Smilest.com, yes. - Okay, cool. And thank everybody for watching today. Really appreciate this. This is definitely, this is the best conversation we've had to date on AI and appreciate everybody's time. And again, thank you, Jane, for getting this all coordinated. Until the next time, this is the Group Dentistry Now Show. - Thank you for joining us today. Don't forget to subscribe to the podcast to stay up to date on the latest DSO news, insights and events. Also subscribe to our DSO Weekly E newsletter at group dentistrynow.com. (upbeat music)