Trends, Impact, and Insights with Ameritas' Chief AI Officer

NADP Host: Good afternoon and thank you for joining us nadp is pleased to have Dr Steve Keller a longtime nadp member volunteer and nadp Gabriel award win winner as our webinar moderator Dr Keller I have transferred control of the platform to our presenter so let's begin

Dr. Steve Keller: thank you as AI continues to revolutionize healthc care leaders must navigate its potential to drive Innovation efficiency and improved patient care in today's we inar we sit down with the seasoned AI expert and former Chief Information officer turn Chief artificial intelligence officer and a VP of products of overjet to explore how AI is transforming Dentistry some of the topics that are presented will discuss are the evolution from CIO to CIO and the evolving role of the chief AI officer what does the CIO do and is this role crucial for your organization success the importance of having Workforce Readiness Playbook and preparing for an aid driven future of denst stre how AI is reshaping key roles within Dental practices and how to prepare your team for the shift and how to maximize business impact with AI along with practical strategies for leveraging AI to boost operational efficiency improve patient outcomes and drive measurable results so whether you're just starting your AI Journey or looking looking to elevate your existing strategy today's webinar provide invaluable insights and actionable takeaways for healthcare leaders eager to stay ahead of the curve Richard werbeck is the senior vice president and chief AI officer at ameritus he's responsible for driving higher levels of efficiency productivity and revenue through the use of analytics insights automation artificial intelligence and experiences that matter matter he's a member of the executive management team at ameritus helping to build the company's vision and strategy he's a member of the executive management team uh and Richard was a CIO role at ameritus for 12 years before this new role with responsibility for all technology Enterprises wide leading the companywide transformation program creating the first data and analytics capability the executive sponsor for driving value from the company's Investments and projects and was active in the company's business strategies brand and results prior to joining ameritus Richard led the insurance division for two Global software firms was a Global Financial Service leader in a top five International consulting company worked for major corporations such as TRW Boeing and RR Donal and Suns as well as created a startup Niche technology consulting company that he grew to 35 million revenues before exiting Richard is an energetic executive with the track record of solid accomplishments in all aspects of business from strategy to operations he excels at creating High performing teams he has been a frequent speaker on the future of it the future of work and successful transformations in recognition of his accomplishments and contributions to the tech technology profession Richard was inducted into the global CIO Hall of Fame in 2020 Jay and Elric Anthem is the VP of products at overjet jant is a veteran product executive with over 20 years of expertise in building and scaling Aid driven products and organizations currently he leads the insurance product portfolio to over bringing forward Advanced Solutions in this field his background includes leading product teams at Google and multiple startups such as lean Tas which was acquired by Bank Capital Clara analytics and luminary Cloud specializing in AI applications that improve operational efficiency within health care and insurance JN combines technical Insight with strategic leadership he holds a bachelor degree from the Indian Institute of Technology in New Delhi a masters of mechanical engine engineering from renier Polytechnic Institute and an MBA from the University of Chicago Booth School of Business welcome to you both and let's begin

Jay (Overjet VP): thank you Dr Killa uh Richard it's terrific to have this chat uh whenever youve spoken in the past I've learned a lot from it so really looking forward to uh digging deep in many of these topics so there's a lot to cover so I'm going to jump right in so uh the first question that I had was around uh the CIO role um I mean you've been a very seasoned executive uh really at the intersection of technology and strategy for a long time uh you were not just any CIO you were Hall of Fame inductry CIO so you've been into that role um and in the past one year you've you're you're in the CI role the chief AI officer role so the quick question is around what does a c Chief AI officer do what what is the charter and uh the reason I think a lot of people are thinking about this lot of executives are thinking about having a role like this so it' be great to hear about your your perspective on that

Richard Werbeck: yeah thanks uh uh Jan and um and Dr Keller you know wow that was a a wonderful uh history there that uh made me blush a little bit it was like uh so I appreciate the kind words um I I think the way I would answer that a little bit is just the conversation that uh the CEO and our our president and coo had and myself while I was still in the CIO job we actually sat in a room and talked about how are we going to advance and move into this world and and make sure we wake up three years from now and we haven't um not taken advantage of where AI is moving um so is it just another applied and enabling technology and you continue to manage it from um from the same way we've been managing any kind of new tech that's coming in the door um and we just don't do anything different and I think when we looked at it uh we kind of started landing around the amount of change that we believe AI is actually going to bring into the environment forced us to say well we really need to go make sure that um that we don't uh we don't just look at this as just another uh enabling technology we see this one as driving significant amounts of transformation creating people change process change and Tech change and so that was kind of the impetus to say well then we really want a business executive that is thinking about how do we go do that and building the right Partnerships in the organization and if you think about as you said just what I call that next Generation CIO um that's kind of some of the traits that you're expecting out of that uh Next Generation CIO job and I still have a ton of you know uh friends and colleagues that are in CIO jobs and and so making sure that that uh that that partnership is still enacted but you really need to be also looking at how am I making sure that we are driving some type of result and so for us it was let's have a business role that's focused on an objective um part of that objective is making sure we don't uh wake up and have uh missed the the boat on on what AI can actually do for us uh and and not just what it can do for us in terms of value and opportunity but what it can uh how we're going to need to manage it responsibly as we go forward so hopefully that answered the question the way you were looking for it if not you can ask another one

Jay (Overjet VP): absolutely so I think uh I mean just to paraphrase really focuses on business impact and figuring out how do we connect all the dots organizationally to be able to create the business impact that we need and that's a great point because AI is not just about the technology it is going to require u a tremendous um a lot of energy to figure out how to restructure our processes right across the board we'll talk a little bit more about this later on but that's a that's a great kind of point of view one question that a lot of um kind of our customer Executives have is around when is a good time to have a CH Chief AI officer um when should you think when should you think about that uh any thoughts in terms of like if you were a CEO when would you decide how would you decide whether this role is required or not

Richard Werbeck: yeah and and you know that's I mean it's probably I get ask that question a lot and and I can I can obviously form an opinion but I think it is one of the tougher questions you know do you I I think that dialogue that I described I think that's the dialogue you got to have uh as a set of Executives and I think you have to be open to um because you know in the past uh companies we've created specialized roles all day long we created the chief digital officer we created the chief data officer we create right we've done those different things in different firms um and and they've some of them have worked out and some of them haven't right I feel like this is one where take a step back have that if you feel your executive team can get in a room and you've got somebody who can own AI get out of all of the things that are in their way I think one of the one of the big decisions that pushed us was no matter how much you try to say I'm strategically focused the CIO is burdened with the run you always have that on your plate you always have that issue right and and that is going to create a dist ction on your ability to go uh push towards uh a future that isn't just about getting that Tech leveraged and put in place and delivered it is going to be about um how do you go change the way you do business right and I I look at you brought up a really good point think about uh in the 1990s right re-engineering was a really big thing and we really haven't heard re-engineering for years and I will argue the reason you haven't heard anything about re-engineering is re-engineering um there's been no tools in the tool bag right streamlining automation you know uh eliminate process redund redundancy those types things were the tools in the re-engineering tool bag to get in and look at processes and I think AI is now a tool that goes in that tool bag that can have you fundamentally look at a function and and re-engineer it think about the way work gets done think way about the what people do what AI does and you can really completely re-engineer uh functions into in processes in a way that you never have before and that's a very transformative um piece of work that if you don't get out of all of those burdens you will you will get dragged into them right so I think that's one of the factors think about how much do you want a leader burdened by those pieces I will also argue you don't want a leader that's just running around rough shot one of the comments I like to make is I spend a lot of time as a CIO trying to make sure that there wasn't Shadow and Rogue it and I don't want to be uh a to create more Shadow and Rogue it and a new job right so I do think you want to make sure that you you Scope that role to say Hey you even though the burden of the run is on the CIO you can't go create a bad burden right or an additional uh burden so I think as you think about looking at that role but I would encourage a lot of leaders to think about how do we want to go create that focus and do we want a seite job do we want a job that reports to somebody in the sea Suite um but I do believe it is a significant enough change that you should be looking at some type of a role that gets up every day and is pushing towards that business outcome right not not pushing towards uh AI Hammer looking for AI nail but pushing towards that business outcome and bringing all those perspectives together and I know I dragged that out a little bit but I I think it's important to think through that Dimension those those aspects and dimensions

Jay (Overjet VP): that's a great point because I was just recently looking at um an interview of Satya nadela from Microsoft and and uh one of the key points that he brought up which is way tight to what he just said is this is a kind of a reemergence of business process re-engineering with uh this really strong toolkit that's coming up right now right and it requires a lot of energy to Think Through what that would mean from an organizational standpoint across the board to drive business impact and you're absolutely right I think there's so much going on in the AI space that if you are trying to mix that along with like the burden of the run like you said it's just too much to one of the things will essentially fall fall through the cracks right and so really having a separate role focused on really where is AI going what's happening how should we rethink work I think is is a great great Point uh that's terrific um I wanted to just switch gears uh I know we've spoken a lot about um the implementation process of AI and I know many of the many of our um attendees as well as many of folks we spoken to are quite early in their AI journey and so for folks who are in the early in the AI Journey any thoughts in terms of how they should figure out how to get started and uh what use cases should should focus on what framework should they use on ways to get started and maybe tied to that is how should they go about the journey because it's quite a scary Journey it's an exciting Journey but a scary Journey how should you think about like step one step two step four

Richard Werbeck: yeah and so uh there's a lot to unpack in that but I I I think let me try to think about how to frame that um so one of the mental models I would throw out right out of the gate is I think uh the journey into AI is a lot like the journey into the internet right I don't know how many people remember pre- internet but you can catch some funny YouTube videos If you go like think it's like Bryant Gumble and somebody on The Today Show and they're saying hey you know come in and explain this internet thing to us um and so and it's kind of interesting to watch given that we're now in the era where that is you know ubiquitous but I think it's very similar right what we think it's like um and then what we thought about the internet once we were in it were very different and the decisions we started making once we were in it were very different so I would argue step one of your journey to AI is get in it just get in it get it in in an experiential way um um and and so I always uh the way we describe it is stage one is experiential learning get in it begin to understand it uh begin to uh adopt it use simple use cases right um and there are and we all know I I I probably want to point this out for anybody that's kind of studied the space a little bit ai's been around for quite a while just in different forms so you know in Meritus we've been using algorithmic and machine learning AI for 5 years now specifically in our Dental space um with overjet using uh you know uh looking at dental X-rays and actually uh handling that part of our business and processing that very rapidly but that's kind of the algorithmic ml now you bring in gen Ai and you put those two together and I think um so that stage one experiential learning simple gen AI use cases Knowledge Management help people get work done that they're already doing you know volumes of uh uh information and data it's not a dental example but they're probably I could probably come up with one there we uh like in our life business attending physician statements handwritten notes medical records etc etc our Underwriters have to review those sometimes those are 800 pages of and years of stuff and the AI can whip through that uh read all of that answer 10 or 12 questions the underwriters have it's not doing underwriting but it's helping an underwriter do their job and do it quickly fast and even better we're seeing that it finds things and looks for connections and corollaries that the underwriter might have possibly missed but that's stage one what I call experiential already and then stage two is begin to mature that kind of AI usage um and start to look for more complex uh uh use cases where you're now stringing things together and actually taking the Gen Ai and the algorithmic Machine La Ai and starting to make them work together so now I've got a very pointed AI doing some work and I have uh gen AI kind of handling the interpretation analysis and movement of the work and in that stage two begin to then experiment with the gentic AI That's new and on the horizon and we're hearing about it but I look at at it as help you do work start to do the work and then it can begin to own the work and I think once you're in that own the work you can truly then start to kick in that uh re-engineering aspect of rethink the work rethink the work entirely how it gets done and you might even get to a point where it's not just AI helping the work or doing the work it's AI managing the work and now humans are in the control and the oversight and the monitoring and might even be working side by side and then you start to scale that up so uh I think that that third uh stage is really grow it begin to reimagine the work and the fourth stage is then start to scale that and really Kickstart and advance and mature that um re-engineering function and so you know and and and I describe all of that and none of that is a timeline based approach it's almost an event-based approach we've built a set of exit criteria that says we know we're out of experiential learning when we've accomplished the following things we know we're out of of um agentic AI when we've accomplished the following things we know we're out of the reimagining work when we've accomplished the following things and then you kind of book in that with you know kind of a responsible governance what do I want it to do and not do and what you and I spent some time talking about how do I prepare the workforce to live in that world as I'm maturing myself down those stages so I hope that gives you a little bit of that uh concept of the Playbook um and depending on where you are again I just go back and say it today it's the worst it's ever going to be it's always going to get better get in start to learn start to find and I would look for use cases that add value everybody's going to have a different goal our goal is productivity and efficiency first we're not ignoring Revenue we're not ignoring quality because we think both of those will come but if you look at us as a company you know Topline growth we've been good at uh you know uh the insurance industry fundamentally has what I would call a cost curve uh Challenge and and we want to go uh focus on that challenge so I think you have to always put your use cases in the context of what is the objective and the outcome you're after and uh but also put those use cases in the context of where you are in your maturity so we've got use cases in our pipeline that are look like Great Value propositions but they require us to be much more mature than we are to implement them so they are sitting kind of in a hold pattern while we go prove that we actually are mature enough to handle that if that makes sense

Jay (Overjet VP): oh this is terrific I think uh just to do a quick recap I love the framework that we had spoken about earlier as well and you just mentioned which is the whole thing about when you're looking thinking about a use case and how to phase things out think about first how do I use AI to help me with what what we're doing currently the second thing is how can we help them do the work that we're doing currently and the third part is actually how do we help them own um work in a different way how do we REM work and it in a different way and I think there is uh that that that if we skip steps and we start kind of running before we can crawl uh we trip over ourselves and really that's a very important kind of part to think about the other part is really getting into it just get into it start small start with something and then build up the muscle memory to can of keep keep building up one thing that I uh we found quite useful is because there's so much to be done and so much that can be done uh in terms of the objective people kind of uh we get a little confused in terms of like what is the final goal and we found it quite useful to think about like the patient outcomes uh the helping the patient as being a good notar to really align all our goals because at the end of it all that's what we here for to helping the patients and uh really getting getting everything aligned on that would be is a great way to get started and uh but it's a journey that we got to just jump into and get started with thanks a lot for that

Richard Werbeck: but I so and maybe we'll come back to it but I I would add on that to your point Point uh cuz we've talked about this if we can go create the efficiencies whereafter if we can go create work being done better does that create the space for us to now go focus and care more about oral Wellness right we talk about oral Wellness on in ameritus a lot um and I think when you get outside of the insurance frame and into the dental practices it's patient care but you know I would argue oral Wellness should care about the patient um does it give us the opportunity the space to then say well you know what's that Northstar that Northstar should be oral Wellness better patient care right and and and I think there's a there's a huge opportunity for us to grab a hold of that and put that in the Forefront as we go through this um but but that is a decision that people are going to have to make and Management's going to have to make

Jay (Overjet VP): absolutely the other thing that I think just based on our experience with working with Emeritus um and customers like you is it's it's important to focus on Roi focus on impact it makes it much more tangible and so um just like with our teams as well we were able to kind of show Roi early on and then we kind of build up on top of that and so uh so really creating kind of smaller efforts that we can show quick Roi with and then kind of building up on that momentum and then going forward I think helps a lot it energizes the team it shows that this is real and so uh that that one more kind of point I think that's kind of important to highlight um I want to shift to one more thing that uh I've learned a lot from you about regarding Workforce Readiness this is an important thing um there is so much to be thought through in terms of organization structure at a high level um roles and responsibilities and all the way down to an individual what should i as an individual do right and how do I build myself up in this in this new world uh so maybe I can start with the organizational aspect of it the executives perspective so if I was an executive um what guidance would you give me Richard in terms of how to prepare my Workforce for to really start driving towards this AI kind of intense world

Richard Werbeck: yeah and I I think there's uh two parts to that equation right so the part is again how I I like to go back to this experiential learning how do we get how do we get people in it and using it right because you can uh you can have a fear-based response and you can have a excited response and I think you'll find people have both of those uh but a lot of that is just just start you know hey go use it make sure it's not something you're afraid of but it's something you understand um and so I think the first thing we talk to Executives about is how do we just start to get your organization in and using it and create that dialogue and give them a a team that they can go to because a lot of times you're still kind of learning as you go so we want to make sure as you try something and it doesn't work let us know right was that because you took the wrong approach approach is that because you don't understand it is that because we didn't set something up you know cuz we're still putting things in the other thing is we you know which a lot of firms are doing we did a book club you know and it was like look get the executives reading and understanding this world um have some dialogues where you're talking about practical examples share things that are occurring and help people see we built this grid that was like um patterns you know and we said hey you know this is a Knowledge Management pattern and so if we solve one knowledge management pattern you know there's probably 50 different ways you could Implement that pattern in different parts of the org so we can say hey we got this thing but I bet you have five examples kind of like that that work for that and how do we get that out in the Forefront but I think at the at the same time I believe we have to start laying out A playbook for how do we go live in a world where you know right now if it's just helping us do work that feels very um useful and familiar right ah it's a tool it's helping me when it starts doing the work we're going to need to start getting people to say well how do you manage it and pay attention to it and monitor it and understand you know what it's doing so how do we teach managers well how would you manage AI right would you manage it exactly the same as you manage an employee uh and can we put the same controls in place or do you have to manage it differently um one of the things we've talked about is you know you can manage it like an employee but the speed at which AI can go do something you know it doesn't sleep right so you know I gave you a task and I wake up tomorrow morning and you did that task to the thousandth degree a person would have done it to the 10th degree um does is that going to create an issue if it goes that far that fast and gets that far ahead of you so H how do you think about that um and then again as we continue to mature down so I think your the workforce Readiness aspect is how do I get people comfortable and going now and start to get their understanding experience uh reduce Their Fear um and then um you know again start to look at hey how are we managing controlling and looking at things to help with that fear but but I look at it in terms of you know I think AI is we can call it the fourth Industrial Revolution or whatever but the third Industrial Revolution automated the factories and I think one of the things that management has to think about not just the worker is we sit in a room and have this conversation we have X number of employees and we believe 10 years from now we will be three times bigger and we will still have X number of employees um and that all sounds good until you break it down and say well but that X number of employees might not be the exact same people that are the X number employees today right and I think about a factory and I'm like if uh if you look at a factory there's just as many people working in factories as there probably was before all the robots and Automation in them they just do different things but if you're the person that was bolte on nut B that bolte on nut be job's not there right right and so we can't lose sight of the person who wants to do bolt a on nut B how do we deal with that because we're not going to have bolte on nut be work at some point in the future right um so again I think doing that as you mature and making sure you're making those adjustments uh are going to be important but but I think all of that has to be considered right you got to get people in you got to get them going we've done kind of a book club for associates which is you know the you know here's why you shouldn't fear it but here's also how you should think about uh maximizing value right you know it's like think about the work you're doing and and let AI do the work AI can do and you start figuring out what it can't do today and start doing that right add value where you can add value let AI do what AI can do well uh and be and build that symbiotic relationship with it that allows you to become a better a better employee a better associate a better manager because you're leveraging the power of it to make your job better so again a couple examples in there of things that we're looking at I I think this is an area where my goal in 2025 is to build that Playbook and that framework out because I haven't found it yet I was kind of hoping I could find it and and leverage and I haven't so we're really going to burn a lot of energy in the first part of the year what exactly is that journey and how do I set that Journey up so that I'm paying attention to the maturity and making sure I have a Workforce that can live in that world world work in that world and function in that World um and I know we we may talk a little bit more about it but but yeah

Jay (Overjet VP): this is great I think I love the book club idea this is I think there's lots of things that we can do at in a kind of relatively lowrisk manner to kind of start uh really getting the word across point across and like you said kind getting started uh the book club is great uh one thing that we've done so even though we're building AI we want to be able to use AI ourselves to do our jobs uh whether it's in product management whether it's in engineering whether it's in no matter what right and uh so we actually created a goal in 2025 for all of our functions to really turbocharge their efforts through AI so we are each of us is covering the uh the toolkit right that's been developed for AI and figuring out how can we use different things to do things differently uh how can we Define products faster and better through AI how can we do market research faster and better through eii things of that all so each of us I think there vibrant ecosystem of tools being built so we can all start figuring out like how can we actually start doing stuff doing our jobs FAS and better the other thing is the patterns part of it this is great I think the whole thing about saying let's actually look at that grid and figure out like what are the patterns of things that we can do it reminds me a lot of like at Nasa they have like a when Engineers they actually have a wall full of like prior designs that were made just to inspire people on what they could do so just the visibility of what others are doing to to the organization at large will motivate people to think about like what else can be done uh so that's I think the whole art of the possible what can be done right I think can be really inspired

Richard Werbeck: and I think one of the other things that that helped us with it was also where is it being done so go ask them yeah right just go over and talk to that group right and and it it helps my org not become the traffic cop for all of that it's like we're I like to say I want to free the Enterprise to go you know get as much progress as they can on their own and so if they see hey we've got this example in our life insurance division but our Dental Group looks and says God you know I got something similar it's like well go why don't you go talk to them and then you know then come engage us and we and we can help so I I think it also helps you know kind of free people to to start moving down that path on their own

Jay (Overjet VP): got it in terms of uh uh organizational like structure uh what are your thoughts on that I know it's still quite like nent and we still figuring it out right now but uh I mean there's one point of view potentially to have one centralized AI group that is then supporting the various functions um or there could be a model where you have a centralized group but you have folks embedded within different functions who are essentially the AI experts within the function helping their turbocharge efforts there um any thoughts in terms of organization structure or is it too early to say

Richard Werbeck: uh well I mean I think some of that's also so where are you in the journey right so um I I look today and say uh when you're early stage and you really got to start to build capability expertise and make sure you've got good practice and process and talent and ways to get things done you probably need to use a little of that I'll call it centralized kind of Coe structure to make sure right um that it's not completely the Wild Wild West and you're not off you know uh taking uh taking uh Phi data and shoving it into an open AI chat GPT right you know I mean even though you would expect nobody to do that right if you're not trying to build a little containment in there to do it um so way we look at it is and there's some specialized skills we call it AI engineering those are the people who are actually helping you think about how you use the AI um and and whether or not that becomes Federated or pocketed out and more focused we've actually put a team that focuses on our life Insurance business a team that focuses on our group business a team that focuses on our Enterprise Services functions a team that focuses on our retirement plans business because getting a team of AI Engineers that actually understand the stakeholder entity that you're dealing with you know is helpful but they're all still working very tightly together as we as we advance and mature um and so today we felt that was probably the right answer I think as we uh as we get more volume and things happen and more occurs the other side is the respon responsibility for what we're doing the processes we've implemented those fall on on the actual business area that's doing them so we didn't want to create a scenario that said everything is controlled and running through Rome um you know almost like I'll use a a bad example but your claim system I I got a business owner of the claim system who says hey all those claims processes I own and you got a tech owner that says I make sure there's a system there and it's parameterized and coded and function and up toate and you know got the right death debt and risk tolerances around it and and we think whatever we're doing with AI so we have a team that makes sure that the technology stack in the geni and it's actually setting up to do what it wants to do but the team that says I'm doing attending physician statements or I'm managing um you know provider networks uh processes I'm looking at um you know how I'm doing provider management or network management all those things or I'm doing Dent those are still right the business people who understand that process who understand that result so I think that that structure is probably still the right structure um and and how you build the support team uh and then if you look at my team again not to create Shadow it but infrastructure architecture data all of that that's all it so I've got a set of it that's in working with me and then I have um all my management support right so my cost diagnostic team comes from you know the Finance and Accounting area my uh you know my compliance and Regulatory group comes from there my leg so we're always trying to put that together and I do think it's important we do have an AI Council it's basically a subset of our executive team who gets up every day and says how are we handling how is all of this occurring are our policies staying in lined with our maturity is our um is our responsible framework and guideposts all in play is our maturity advancing where are these things occurring so we do have a little of that um kind of you know uh management body that's caring and paying attention uh and gets up every day and works with me to do that so I think you really got to go do this in a a very collaborative fashion and a very kind of intertwined way um but you can't lose sight of getting something done right so we also have a scorecard and that scorecard says we intend to go get 200 so I'll give you this number 240,000 hours we want to shift from Human work to AI work in 2025 so you can math that out right two 240,000 hours is 48 FTE worth of work we're going to say AI is going to be doing for us um and that's a very important uh piece of the puzzle right to not lose sight of you've still got to go make sure things are happening uh and you're pushing and you're driving them through even though you're off trying to make sure everybody's in the boat working with you to go make that happen so I don't know if I you I mean I don't know if I gave you the perfect Playbook but I do think when you're starting this kind of Coe concept that is working with the stakeholder groups and bringing everybody together feels like the right way to go after it it certainly felt like the right way for us um and you know I think if somebody came to me and said but my company looks like XYZ I might put on my old Consulting hat and say well then do one of these and structure it like that but but I still feel like that basic structure is probably a good place to start

Jay (Overjet VP): yeah and I think uh the key key Point here that he also brought up is that the the final outcomes of what happens it is important for the business owner to own that uh because uh that's where finally the rubber hits the road uh it it's very strange if you have an AI engineer kind of owning that piece right or some explain because they don't have the domain kind of knowledge and you need to be very nuanced about impact and that's very right

Richard Werbeck: yeah we have this interesting scorecard where we call uh uncommitted benefit to committed benefit and the only difference between uncommitted and committed is our business partner signed off and said I agree and I'm willing to I'm willing to back that number right and and it's just it's a subtle thing but it's amazing now the dialogue is well what do you have in the committed column right because that says everybody agreed and signed up and then it's also the challenge of how do I get you to Ink right it's almost like I need your I need your management ink on paper um and and those are real organizational challenges that I think any leader has to go lean into and step into

Jay (Overjet VP): yeah I think it's it's one of the big things that we don't uh talk enough about is the leadership muscle that we have to build and build up more uh in the context of AI there's so much change going to happen uh really it requires very strong cross functional leadership because no one team can do all of it it has to be a combination of multiple teams going of bring block together to make the make it everything kind come to life um I want to just zoom into an individual right so if I'm a an employee right now in a dental plan company and uh i' be hearing a lot about AI um I know parts of it would be essentially around how do I can learn about what's going on but any any tips for um just an an employee to essentially think about how to retool themselves in the context of this this Brave New World

Richard Werbeck: uh yeah and again depending on where where your company is we before we put our own um in-house kind of uh ai ameritus ai together we did encourage people to go out and learn learn on whatever it was Claude chat GPT go get some exposure we gave him a lot of guidance please don't least don't use ameritus data out there right so you kind of got to guide him a little bit please don't put anything out there that you wouldn't want in the complete public domain um but we did get encourage people to kind of get started before we handed them kind of an in-house tool and then once we gave an inhouse tool was like now come do it um so I again I think it's back to that comment of just continuing to encourage enage him find ways to have it do it we have what we kind of call Liaisons which is kind of people in those business areas and so we're outworking with them and kind of going into those teams and saying here's areas where we think we can find a significant uh Improvement in quality of work amount of work getting done volume of work so in some ways you know you can't go hit everybody at the same time you can you can deliver Communications to get people comfortable um but I think when you're down on the individual level again it's getting that use case and then calling that out uh and we do do top down Diagnostics on use cases right because I I really don't want to go you know I got a process that's currently costing me $150,000 a year total cost of the process um and I'm going to go burn you know a lot of hours to get a 10% Improvement there or I got an entire end process that's costing me you know $20 million and I can go get a 10% Improvement there like well let's go get the 10% Improvement there and this one will will show up so uh I think it's just continuing to engage the organization around those types of things get pull people involved we're trying to do a little bit of the pull model to start um and and I think uh again trying to use some of those success stories to get people to say wow I could do it at the same time and this is the this is back to the bolt day on nut B how do we get messaging out that says use it and understand it don't be afraid of it but the world is going to change right and and if you're not starting to develop you know so we think of some of the skills are you know hey critical thinking and and how do I get work done and because AI is picking up and so you know there's a lot of uncomfortability around if your personal value proposition was you know picking up this piece of paper and moving it here and and scrubbing it you know the AI is going to handle that really really well and and how do we try to make sure we're creating the dialogue somewhere that allows you to walk up and say well if but that is all I do how do we then start to embed into the individual development plans and all of that something that says then let's start looking at what else you can do right if you want to if you want to grow I I love the three Circle analogy needs of the company needs of the artwor department you're in needs of you if you're not interested in that it's really hard for the org to force you to go want to do something different and change right but if you're interested we should create the opportunity to to drive that dialogue so I think there's a little bit of working with HR to say how do we get them to help managers think about individual development plans differently how do we get Associates to think about owning that as well right how do you start to create that joint ownership of where you're going um and I feel like like you know we can all have like I've seen all the TED talks on all the new generation of workers and and it does feel like a little bit of that I own my career and I'm respon I'm equally responsible for it than my company is is AI is put going to push that dialogue back in again right because I really do think it's hard and maybe I'm an old school leader but it's hard for me to get more excited about your career than you are but if you're excited about your career then I am equally excited about figuring out how to help you navigate some of those those zones does that make a little bit of sense there I know I took some liberties with personal preference there but

Jay (Overjet VP): uh no this is great so I think if I had to like paraphrase this in the context of like an individual employee uh in a dental plan company it's really about learning more about what's happening get started right use cloud I love Cloud uh I love chat gbt as well all of these tools have their own little nuances it's important for us to get familiar with that just like we got familiar with mobile phones the internet all of that stuff right it's just a matter of getting get your hands dirty that's one part of it the second part of it is really if there's something out there that that the company is doing that uh is uh is use involves AI try to raise your hand and say I want to help right uh so Define your career the career I mean um you can manage that and you should start pushing for it and it's upon companies to give opportunities to able to have people of pull people in into initiatives as well right so yeah

Richard Werbeck: I mean do do you want to be the person that you know AI showed up and did it to you or do you want to be the person that said I figured out how work is going to look different in my world and I'm now a leader right I'm now leading and I'm an example of let me show you how I just rethought the way I did work you'd love to see those examples and and I get look there different personalities and different people have different Comfort zones but I would encourage you know every employe to say well which one of those two do you want to be and then lean in and go do it there's so many things to do I would also say listen to where your firm is going like for our firm it's like we've started cutting off hey please don't use chat GPT and Claude use our in-house right because that you have the freedom to put our data in it and you don't have to worry about security over here but over here you do so we're you know think about where your firm is in terms of giving you access to tools that you can use and help those grow but yeah

Jay (Overjet VP): and also the point that you brought up about critical thinking I think is an important one because uh I think there's a bit of like a nervousness about uh of these jobs that were there in the past kind of going away or being repositioned some way um but it actually unlocks a lot of potential for us to think about again the patient outcomes and how do we really think about how do we make the the patient Journey oral Wellness Journey kind of much more uh much more smooth and much uh have a kind of impact on that there's a lot we have to think about there that we haven't able to because we've been burdened with all all the other baggage from a process standpoint that might not no longer be there and so it unlocks a lot of capacity for us to really start thinking about things from that perspective which requires a lot of critical thinking as well

Richard Werbeck: yeah I think again as you your frame was the the actual kind of employee individual contributor and I think the challenge there is right now they're probably worried about what does my job look like yeah and they're less worried about what's this greater Village opposition out the doors much as I hate to say it so I think you you know the conversation with management is make sure you understand that's what's happening I do believe as management we should be hey if we can free this up and help our uh employees get through it we have this opportunity to really go uh make an impact on oral wellness and and patient care right uh and if we can get people to see how they do that I think they'll lean into it people like to lean into things that have uh purpose and meaning uh you know you know on average I I'm a firm believer that people really do want to do good things um I'm sure there's folks out there that will prove me wrong all day long but I'm I'm going to stay in my little happiness bubble and continue to look for those uh those wonderful people who want to do great things

Jay (Overjet VP): yeah know definitely I think across the board I think uh doing right by the patient is one one General theme that it binds all of us and I think everybody really wants to do something there but I think one point is uh again just to reiterate if you feel that there's a part of your job that's repetitive that is most likely going to go away so just be aware of that um if there's a part of your job that requires critical thinking that's going to get more and more important so stop on that right and and also the third part is whenever you have an opportunity to jump in and start helping out with a with an initiative like an AI Le initiative um jump in and start getting your hands dirty so those some of the kind of key um kind of takeaways I think um did I miss something there

Richard Werbeck: perfect

Jay (Overjet VP): so uh there's there's always uh I know we've spoken quite a bit about a few other things and we want to open it up for questions afterwards but I wanted to just have some closing thoughts from you about um if there's any leader who's still skeptical about AI I think things have been moving over time but AI has been also evolving a lot over time as well in the past few years um and so um any piece of advice that you would give to to an executive in terms of how to get past the skepticism of a and how to start embracing it um so if you had a just a one-on-one chat with an executive saying uh you really need to stop being skeptical or maybe you are right in being skeptical and you need to do things differently how would you kind of how would you quotes that ex get to a

Richard Werbeck: yeah I think you know I I would probably start with uhy uh a AI is as worse as it's going to get today it's only going to get better it's only going to get better it's only going to get smarter and the capabilities are only go Advance right um I do believe as a lead so to me as a leader to sit back and say say I don't believe it I'm just going to wait that that feels like um a very uh a very dangerous move because you're going to miss out on anything it can do for you I don't think I would encourage someone to say well just jump all in willly neilly go wherever I think again it's it's be thoughtful be purposeful uh but get going get in get started start to learn figure out where it can bring you value today where it can bring you value tomorrow uh and continue to push for that Journey as a leader I would also say go get educated on the the future potential of this because you want to be you don't want to be just dealing with what it can do today you want to be dealing with where this thing is going and right the skate to the puck how do I start getting out there and and getting ahead of this and making sure I'm thinking about the things I need to lay in to go to go really take advantage of it right whether that's you know right go create more operational efficiency whether that is complete significantly rethink um the way a function Works um leaders I believe are responsible for making their companies better making their products and services better making their organizations Better and navigating all of those this tool has so much potential to do that for you that you shouldn't ignore it you should get in and you start doing it but I would also say don't ignore all the other ways that can happen right good old fashion automation can get you there in some places right uh whatever those things are and and you and you're still most of us are still in a business of some form right so you're you're still in a business you still need to not chase you know shiny objects you're going to need to um right uh have a have a decent return on investment um make sure your Investments aren't overweighting your uh your returns kind of thing um but but I would say you've got to you know you got to kind of get started on it and you got to got to get in and do that the hard part to me is we close out kind of the workforce is I think there's a potential future where things very very different than they are today um how do you get your head around that and what those possibilities are and then how do you start setting things up to move towards it right so I mean one of the questions I ask is if if fundamentally all these deep knowledge pieces AI can handle what does that do to professions right you know do you need them do you not need them do they look very differently does AI doing the Deep professional work and people are working across those and still need to have an understanding um and I think you got to start about how am I preparing myself and my uh my org to do that but but I think leaders have got to what an opportunity to lean in and get going right what an opportunity to step forward I would encourage and I have every leader go get in it right whe whether it moves fast or slow for you whether it gets there today or tomorrow get going because you know you're going to want to make those decisions right uh if you're skeptical you're SK most of the Skeptics I hear well I'm smarter than it is or it did this wrong and it's like well you're looking for a reason to not use it I would say look for a reason to use it look for a reason to get value out of it and look for a way to make sure you're getting the value appropriate to what it can and can't do today um and what it will in the future so I don't hopefully that answers you know kind of where you were going with that

Jay (Overjet VP): absolutely this is great I know we can go on and on for for a long time but this really gives a lot of food for thought uh maybe I can open it up for questions Dr killer um any questions from the audience

Dr. Steve Keller: okay well first of all thank you both very much for very thought-provoking and informative presentation uh as you mentioned we're open for questions you can click answer ask a question by clicking on the Q&A box at the bottom of your screen um can we jump into just a few minutes uh the governance question um and what approach do you recommend uh for implementing effective AI governance and uring an ethical uh and compliant use of uh AI

Richard Werbeck: yeah um yes so first under 60 seconds in under 60 seconds so the first thing I would say is uh you know the first the first structure that you have to have is you need to have some ability to sit in the room and say what do I want the AI to do and what do I not want it to do and how do I I constantly come back and test that right um so right now we've said given where we are we do not want to use the AI for customer fa in and we do not want to use the AI it directly in making underwriting decisions of any sort or pricing decisions of any sort um part of that decision is based upon we don't believe we're mature enough to manage that in an effective way right um so I think you've got your responsibility has to do that on the other hand you need to be running around and looking for where are your controls and your monitoring need to change because of the speed at which AI could actually do something and make a decision because it has an objective and a purpose and it's going after it with all kinds of zeal um and so I think it's less about what you're reading in terms of hallucinations and Model Management and training and it's really more about how am I thinking about uh where where do I want to put different mon monitoring controls and stuff in place where do I need to change a control in the company and where is it okay um one of the great examples I use is you know the SAS world that we're moving into AI is showing up embedded in all of them and we're moving from what I call a optin uh culture to an opt out culture so the feature shows up on Monday right you log into Microsoft Office and whatever updates that made over the weekend are there uh and as a firm you have to rapidly have something that assesses what did that just do to me and do am I am I okay with what it just did so that idea of technical change management happening the way that it used to happen you probably have to rethink well do I need a better monitor ing do I need a way to assess that and I can actually probably use AI we've been using AI to read release notes and catch that stuff really fast could probably use AI to help me with it it's almost like I'm using AI to help me with the thing that AI is causing um but that's a that's a very myopic example but think about running across your organ looking at all of those pieces and just asking yourself the question does AI showing up in this world make me have to rethink the way I'm I'm looking at something the way I'm monitoring it the way I'm managing it or are my control processes um at risk here um and I think that's that's an important thing to go do there's a lot of responsible AI Frameworks out there that you can pull from we kind of took an amalgamation of all of them built them together and said let's go work it we're still on that Journey but I think there's a lot of Frameworks you can leverage out there uh that'll help you

Dr. Steve Keller: great thank you Jay did you want to add any uh anything to that

Jay (Overjet VP): no I think honestly it's uh there's a bit of a paradox here because it it seems as if if you have too much of AI governance and regulations Innovation will slow down uh but it's actually the reverse uh the more uh more clear the regulations are and governance is and the more guard reals uh the clear guard reals are put in place the faster we can innovate so we actually do uh we do invest a lot of effort at overjet to kind of lay out a clear AI governance policy end to end uh and that helps us a lot with decision- making because otherwise you know exactly what left turns to make as you go through this whole process that is that that keeps it secure for all of us uh and that's super critical for us so um so we we really think a lot about uh our AI governance policies and things of that sort and it's been really helpful for us to actually speed up our product momentum

Dr. Steve Keller: thank you um Richard can you share any specific use cases or success stories where AI had a measurable impact on ameritus and whether it's in terms of cost savings efficiency improved patient care and then if we do have time afterwards Jaren I'd like you to know any other organizations that any of the same type of things success stories or or cases if time to lasts thank you

Richard Werbeck: yeah and I'm trying to stay within the kind of a dental and and vision frame uh since that's the purpose of the call so I I mean I think we talked about it earlier we've been you know we've been using kind of the algorithmic machine learning AI to read dental X-rays and really help that process go faster we have found that to not just be uh quicker faster more efficient but also more consistent in the decisions that we're making uh and we have kind of still doctor panel reviews that look at stuff and check on it and make sure you know it's working in the within the tolerances that we consider but I think as we've looked at it over time once we get a procedure in and going and working through it we find and we're actually now taking that and part pairing that with what I would call the Gen side where we're looking at all the other documentation and information that we need and then putting the two together and just helping the endtoend process be more efficient and more effective I I really think the two together are giving us both an efficiency play and an effective play we're getting better consistency of result we can defend that result it's very transparent on exactly how that decision uh was made or how those uh parameters were Set uh and so you can you can really feel good about that um and and we spend a lot of time making sure we like uh how that result is coming out uh before we turn it on um so I saw kind of one of the questions on how are you making sure you're transparent in in any of those processes um and we we tend to do that as well uh to make sure we understand that does that kind of get to a couple of in addition to that how are we looking at provider management uh you know a lot of it's just around the work people are doing right now I don't think we're out pushing on maybe uh too many advancements around uh patient care out in the provider area we know that's that's their focus and their job if we can make it easier to do business with us hopefully that gives them more time to um uh focus on what's important to them which which is probably the person in the chair uh and uh and so right now a lot of our stuff is really in just how do we make it easier for our employees just to get the work done that they're trying to get done so and how are we better managing the networks how are we understanding uh the providers uh and and where they are and their practices and what they're doing and just a lot of the regulatory stuff we have kind of used it nobody on this call probably cares about but we're starting to use it help us with rfps you know so as an RFP comes in the door you have to parse the rftt to break it down you have to answer like 200,000 questions throw something back in those things sometimes take three weeks to kind of get going and done and we're trying to get that down to two days so you know there there's some nice places where our ability to just respond to building a good plan and giving somebody a proposal on a good plan and thinking about the right things in that plan or people can spend time on that cuz the AI can handle the you know the documentation Shuffle task um and and move forward with that so couple examples there

Dr. Steve Keller: thank you uh Richard I know that we've had uh more questions than we have actually time allowed to go ahead and answer them uh for those of you who did submit questions uh our speakers have agreed to answer those questions following the uh webinar and the questions and the responses to the questions will be sent out to all of our attendees uh once questions are ready on behalf of the nadp I'd like to thank both you again for a terrific uh presentation I would also like to thank all of our attendees for joining us today uh for the webinar and please stay tuned for our next state and topic uh for our next session thank you all and have a good afternoon