Episode 24: Putting Customers First In The Age Of AI, A Conversation with Rick Chavez, CustomerFirst Leader at Oliver Wyman

Speaker A: Hi everyone, and welcome to Oliver Wyman's Reinventing Insurance podcast. I'm, um, your host, Paul Ricard. Welcome to Reinventing Insurance. Today I have the pleasure to welcome Rick Chavez, partner and leader of Customer first at Oliver Wyman. Welcome, Rick.

Speaker B: Thank you, Paul. It's great to be with you.

Speaker A: Well Rick, you're uh, no foreign to the Reinventing Insurance podcast. I think you recorded an episode with uh, my colleague Mick Maloney a little

Speaker B: while back that was fun. That was fun.

Speaker A: So we're going to look to top that today.

Speaker B: Okay.

Speaker A: For those, uh, who haven't listened to it, uh, Rick previously talked about customer led reinvention, his uh, experience with the Microsoft transformation from the inside and many other themes. Uh, and we'll have a few callbacks to these as we talk today. Uh, but today our focus is going to be about being customer first in the age of AI and uh, where insurance goes next. But before we unravel what we're about to discuss today, we'd love for you to briefly tell us about yourself, Rick.

Speaker B: Well, I mean the place we're in now is so fascinating to me. I actually dabble and what was then called an arpanet and now the Internet before it was even a commercial phenomenon, if you could imagine, I'm that old. But, and I was also dabbling with early AI and early is another one of these curiosities because a lot of the algorithmic innovation that we are able to enjoy now in terms of its activation and applicability was actually pushed really hard in the 80s and but it was back in the time when we were so completely wrong about how to use it and our theory about um, using these algorithms for good was not wrong. It just was simply, ah, mistimed. And so watching things evolve through the years and seeing evolutions of technology, I think has, number one, first sobered me and still, I would say broadly encouraged me and made me. I'm still an optimist, Paul. Um, it's sometimes hard to maintain optimism, but I'm still a glass half full, um, kind of person. But in terms of my story, stumbled into management consulting out of college and I found that I was reasonably good at it and I liked it. Um, but what was the m most interesting thing about it for me was that it was a great vantage point to see things in the world that you want to fix or that you think just don't make sense. So I jumped out, did a startup, sold that, then went back to consulting to detox, found another idea, jumped out and built a company at the time of, I call it the Great Happiness, you know, Internet one. Oh, all, all boats were rising. But it was actually not a time I predicted I was just building a great company that was hopefully going to do great things. Uh, and then the dot com bomb I think was quite painful at the time, but incredibly informative, like an incredibly important learning experience for me. And I took some of the ideas that I just couldn't let go and they stuck with me as I went west. So I was on the east coast for a long time building the startups and, and then I went west and got, uh, to work very closely with Jeff Moore, who many people know as the guy wrote Crossing the Chasm and is often thought of as the father of innovation. Very well known on the west coast in tech companies, completely unknown in the east coast but very well known in the west. And we, uh, both got very interested around the same time in innovation at Scale. Me from having been a startup fellow and Jeff from having been a venture investor. And we were really interested not in the challenge of being a startup when you're being incented and pushed to grow with no existing stakeholder commitments. Right. That's what startups are. What happens when you're Cisco or SAP or Yahoo, which was a client, Adobe, another client, where you'd grown to a place and then growth had kind of stalled out. How do you reignite the engines of growth? And I tell you that because that passion or that interest became a passion and it stuck with me to the present. It took me through two tours of duty, one at Adobe launching what was then we called customer experience management and morphed into the marketing cloud business, uh, of today, which is amazing. And then I was, as you mentioned, I was part of the sort of transformation effort at Microsoft as bomber hand of the keys to satya. I got there by having had friends at Yahoo who had repotted themselves as the search team at Microsoft. And, and I brought that thinking about dealing with disruption and living through transformation to my work at Oliver Wyman. And Customer first to me is that it's really all about dealing with disruption with a very strong view that if you start at the end point of a demand chain where people either in a workflow or people at home or on the go have big pressing problems to be solved which could be solved better with digital experience powered by data. So that essential thesis of dealing with disruption by starting customer and working back has been, as you know, a passion. Um, and I'd argue it's been a passion pre Oliver Wyman. But certainly been a passion as I've been here.

Speaker A: And so you're basically threading the needle with, uh, also what we're about to discuss. You're basically helping large incumbents dealing with disruption and with innovation at scale, which, uh, I think you're starting to allude to it. There is a method to the madness.

Speaker B: It's a method to the madness, yeah. I do like to say that the best entrepreneurs, the best innovators are the most disciplined people you'll meet. Um, and it seems to be a conundrum because I think many people think, well, innovation, that should be, that's fun. And truthfully, if you're doing it in its truest form, it probably hurts. And that's probably just about right because it should be a very systematic, thoughtful test and learn discipline approach. So I think the doing of it and doing of it right is, um, critically important and something I think a lot of our clients are still developing and working on.

Speaker A: It's not just the free soft drinks and the sneakers in the open space. It certainly seems like there's a lot of technologic shifts that are happening. And, uh, I know you like to talk about the collision of megatrends, and it feels like this is something that is continuing to happen and accelerating. So can you tell us a little bit what's happening and what feels different?

Speaker B: Let me start by first saying some of what's happening now was predictable. Any sort of disruption, if it truly is disruption, and you mentioned this is a collision of megatrends, you need shifts in behavior along with maybe societal, political, regulatory things that are happening. And then technology. I like to think of it really more as a tailwind as opposed to, uh, the main event. And the reason is that if you stare at the technology, as is the case right now in this AI moment, no matter what we say about what will be three months from now, we would be completely wrong. But if you look at that collision and you say, all right, what's in enduring about humans, um, in their work, in their attitudes and, um, approaches to digital, to technology that either allows more of what they want, less of what they don't, to be part of their lives. And I would say, first of all, that's enduring. I'm going to come back to that. Secondly, that's what's so radically different about now versus then. We've never had as much digital familiarity. If you think about it, you have extraordinary familiarity with all things digital. We carry around supercomputers in our pocket. They're connected to like, as if they're another finger and appendage. Second thing is connectivity, pervasive connectivity. If you think about what's happened in evolution after evolution, we have 5G, we have fiber, uh, these things really, really matter because it means that those edge devices can do more and they can do more. That then helps us be more. So you have this context of pervasive connectivity that allows for very rich experiences which we expect and we actually want them to be intelligent. And I will assert that most of the experiences have not been intelligent and most of what we say about smartphone is frankly more dumb than smart. I'm sorry to say that, but the reason I say that is now that intelligence can be pushed out in the AI ifying of the economy. You have people hungry for that thing and having expected it already. So I think that's why this meteoric adoption of all things chat, whether it's OpenAI or Claude or Gemini or OpenClaw or all these things, why it looks like instant. I think it's because people have been expecting this kind of engagement with the world for a very long time. Think about it this way. You and I have been taught to use a keyboard, typing, and we've been taught to use our thumbs. All right? Now, both those things are not particularly human. We're okay with them, but they're not particularly human. So I think in this world that's showing up. The other thing that's happened with the adoption is making it human and making it natural. Like, you know, the interface is my voice. This too, to me is such a stunning thing because I actually, in 2001 or two, I was actually CEO of the first multimodal company that invented Multimodal actually. And we thought then too that it was going to get dispersed quickly. Um, think about how long it took. So I think it's this nlp, natural language interaction, uh, model with deep intelligence embedded in the fabric of the world and its ability to be dispersed and then onboarded into our lives so quickly. Completely different, right? That is a phenomenon that is unique to this moment.

Speaker A: You're saying that it's all enduring and people are experiencing this at scale in their day to day life. Uh, what is interesting is there is an expectation that if a company is going to engage with me either to solve my problem, to sell me something, to interact with me, et cetera, that it's going to feel the same way these things have felt. Uh, I would love your take on this. It feels very similar, for example, to the iPhone moment when the iPhone came out. Now suddenly, if you were not engaging with, uh, someone through an app, you were dead on arrival. The Web 1.0 interface was.

Speaker B: Became the mobile app. Exactly 100%.

Speaker A: And, uh, so that's one thing. But at the same time, and I would love your take on this, what is also interesting is the pace of change is so rapid that if you got used to something two months ago, it is very, very different now. And so I'm also linking this to the expectation you would have from a corporate, where you need to get up with the program more and more quickly as it's happening.

Speaker B: Yeah, the cycle time change. Yeah. Well, let's take those two things because there's a conundrum in there. One is that some things are enduring, which is to say that they're not changing. What does that mean? And then there's enormous amount of change. And the cycle time of change has never been faster. And so, uh, you know, so we have both these things at the same time, I think. First, let's take the enduring one. I do believe that the big vexing problems in the world are largely still underserved. So let me put my marketer's hat on. Let's pretend I'm back in the ad tech days that I came from. One of the nirvanas was, well, if Paul's driving along home and it's been a long day and you were expected to be the dinner preparer, but there's no way you're gonna be able to do that in time. Well, but I know that Paul takes the certain route and has a certain expectation. He's a little late actually getting home. I wonder if I could surface an offer to him to stop at some really interesting place that, you know, has the cuisine that he can pick up and take home. That would feel like magic to you, that it not only knows you and your habits, but that in fact, you're nervous and you're kind of anxious and a little bit upset at yourself that you're getting home late. So now that is an example of intelligence serving to you a thing that might make a lot of sense that you can then wrap around, uh, that moment to do something you would otherwise not have been able to do. That is the solving of a problem. And that's been a marketer's nirvana for a very long time. I think there's a whole range of problems like that that the new intelligence environment, the ambient intelligence, should be able to unleash. Um, but there's still a lot of these big problems that are not solved. Like we've talked about this A lot like how do I solve for retirement? And in my case it might be very complex. My spouse might have one idea, I might have another. We might have to think about our kids. Maybe we're the sandwich generation. There's all these different kind of considerations and so no one is exactly the same. There are patterns that may rhyme but they're not explicitly the same. And so if I look at like that problem, I would say, geez, some intelligence around nudging me in one direction or another or alerting me or even making it simple to have a unified view of my financials. These are non trivial problems. And so I think if I look at what is the undiscovered country and the potential for new customer value, I would say lots. Uh, and you know this too because I've used the example of other companies that have really gone after the problems that you said versus selling the products they want to have. So like them or not like them, um, Tesla really isn't a product seller. I mean there is a thing called a Tesla and it's got different models and such. But the problem it solved was this sort of sense that some people had about being electric, not you know, petrol. That might have been a preference. But then also I don't want to go to a dealer to buy a car and I'd actually not like to go to the dealer to get service either downloadable uh, software while it's sitting in my driveway charging. That sounds pretty darn good. So it's the complex of those needs I have, uh, that they were able to capitalize on to create this extraordinary value.

Speaker A: Yeah. And it is interesting because to your point, drawing the parallel, it's in a way, uh, Tesla as an example has solved multiple problems at once, broken through the entire value chain.

Speaker B: Exactly.

Speaker A: All the way from the dealer to the car manufacturer to uh, now even the entire ride sharing industry as well.

Speaker B: 100%, absolutely. By the way Paul, just to tap on that value chain is a construct of a supply side world that says this is the way I build a product, I get it to market. Demand chain disrupts all that because it's how I think and want. And that's what you just described that Tesla did. And as a result, look at all this, this disruption.

Speaker A: And so building on this and thinking about our insurer friends in a way there is a very interesting parallel here. Retirement is one thing. Financial wellness, financial security, not only for one's financial wellness, but one's entire family. And the way the industry has solved this for a uh, huge amount of Time has been, yes, more product selling than problem solving. And even in the cases where it was problem solving, it was. Let me solve that one sliver of problem.

Speaker B: That's right.

Speaker A: Versus all these things, to your point, are so interconnected. And I'll go back to something I was saying earlier when I was saying AI is moving so quickly and I'm being very cautious because I don't want to make it sound like it's this magical solution. It's very complex. But one of the questions, for example, is these things are so complex. You do need a human in the interaction, maybe. And for the time being that is probably the case. But even if that's the case, the way the human is engaging, uh, with a customer, uh, the breadth of the needs that they're able to understand, the individual customers, uh, their family, is it a point in time or is it over, you know, decades? Ah, and obviously the breadth of solutions that they can provide and hyper personalize and customize. I think there is a radical shift that is in the process of happening. Yeah.

Speaker B: Ah. And I would say happening and at much lower cost, so much more as sort of accessible and affordable. And I can actually start with customer value, work back and do it more efficiently and effectively with greater cycle time. So I wanted to make sure that I completed a thought, which I didn't. I got excited about only one, one part of my, of my answer, uh, to your prior question. I do think that there's this, you know, there's also this adage, never confuse a clear view for a short distance. I think what you just talked about, the family, you know, financial wellness triggered by life events through a period of time that is potentially a point of arrival, a destination that says I'm going to do more of that and I'm going to do it with um, maybe more of this available sort of smarts that exist in the fabric of the world now. What are the set of experiments and how do I test my way to get to that different future? I think this is where in picking up the cycle time of change. So we talked about things that are enduring and then things that are really changing. I think the best path to dealing with uncertainty and volatility in the environment is to stare it in the face and say, I have a hypothesis. It's a belief about how things are heading now. I could be wrong, but I'm going to be in the game and actively engaged and learning as I go and I'm going to learn as fast as I can because the faster I learn, the better Off I'll be. That agility thing I think is hyper critical as the world changes faster, uh, the ability to then not so much meet and master it, but master it for your own hypothesis about where you're heading and why you should be winning in that future.

Speaker A: Diving into this, I would love to get into your playbook.

Speaker B: Yeah.

Speaker A: For what this looks like, I think you're calling it the AI trifecta. What does this look like? And you know, I'm also reflecting, uh, before we shift to this, what I find interesting is again, I was talking about the iPhone comparison. I remember, um, I'm old enough to know, to remember when the iPhone replaced the Blackberries in corporates. And uh, you know, it was very much employee or individual push was I have access to this, therefore I don't want to have to use these tiny keyboards. I want to have a richer interface. And interestingly, as a customer now, and we've done some research around this, the majority of individuals nowadays are using AI for some form of financial advice. Now, is it the full picture? Is it fully regulatory compliant in terms of the type of answers you get? Is it as sturdy as proper? Uh, well, accredited financial advisor will provide you, probably not, but it is priming the pump for, to your point, what it can look like. And also it's a very different cost structure, it's a very different cycle time, etc. It's uh, another shift. Right. That's customer led.

Speaker B: Right. There's tremendous uptake. And one thing you and I have learned together, right, on some prior work we've done, is money is emotional.

Speaker A: Yeah.

Speaker B: That has lots of implications, including I don't want to be embarrassed by what I don't know.

Speaker A: Yeah.

Speaker B: So where I think the AI engagement around money matters is kind of interesting, um, is AI is not a judging judger, doesn't judge me. So if there's a lot of things I don't know, it's not telling me, you idiot. You should have known all these things so I could be kind of private in my ignorance and potentially close that gap. And so financial literacy continues to be an incredibly pressing problem and I can see some advantages. Uh, I think the dark side of that though is if you're not really good at prompt engineering, what do you do with it? And so I think there's a lot to be said for domain specific advice and guidance.

Speaker A: There is an insane amount of opportunities for incumbents to take on that challenge and offer something that is a lot more valuable. How do you see the big questions that incumbents need to think about, as they think about AI led customer transformation.

Speaker B: Yeah, yeah. Well, I think that in times of great change, you know, if we don't have a plan, don't be surprised that you show up, um, underwhelming. I mean, I think having this chat with you about, um, the whole creation of robotics, you know, for example, in China, I'm fascinated. I'm just a student, I'm a learner. But what's fascinating to me about that plan that really created robotics industry, uh, particularly around manufacturing, is it was a very long view of where, how things might develop, including how cultural shifts would occur and what jobs people might and might not want, or what that would mean for a workforce on a, you know, manufacturing assembly line versus not. And so it wasn't just that it was extraordinary, it's been extraordinary innovation, but it was kind of a plan thoughtfully. Now, I don't know exactly how it was done, I wasn't there. But I think one of the most important things to do in times of real change is to have a view about where the, you know, what m. I'm going to say here, where is the puck? Heading, course and speed. Take a position. It doesn't mean that you're going to be right. So this is interesting. It's not the illusion of infallibility or that you have a crystal ball, but I think this sort of notion of collision of megatrends, the megatrends actually already are observable. And so the idea is play them forward, be thoughtful and rigorous in saying, what do we think is going to happen in 2030 based on what is already observable. Now let me stand there and look back to the present and understand what crown jewels do I really have? What differentiates me? What am I doing that could eventually be a crown jewel? Should I accelerate it or not? But stand in that future, look back and then say, what capabilities? If I'm heading into that five year horizon with some velocity, with some competitive separation, what would I need to do over the next 18 months? And does my current plan of record position me to be doing those things? Because if not, you better start to challenge it and shape it. And I think play number one is really to do that. I think it's so important, and again, not to pretend to be right, but that the leadership team is aligned and saying the same thing with the same words that have the same meaning.

Speaker A: So, uh, as you figure out where to grow, where the puck is headed, there is an element about being clear about what trends we're going to see potentially what's also going to become extinct. Right. And so if you are as an example serving the populations that are in their 20s and 30s, but the population is structurally getting older, then you can see that your own market suddenly dwindling and you can see at the same time that there's greater needs in the longevity space. That's why I liked the example you were saying about robotics of saying, well look, given the policies and everything in China, we could see the manufacturing workforce dwindling over time. So it almost becomes a necessity to work, uh, on robotics.

Speaker B: If you decide that you're going to compete and be differentiated, then this is a thing, a, uh, bet that you really have to place. We like to say make the asymmetric bet, a bet that others either cannot do or will not do, which certainly happened in that case.

Speaker A: Want to pressure test this with you? There is an element of where are you going to play? And therefore how are you going to further build your competitive modes and potentially starting to think about what's likely going to become over time, either deprioritized or

Speaker B: commoditized, no longer part of the future. Yeah, well, I'm glad you brought that up Paul, because I think that's probably the most difficult thing to do. Uh, when you do that, sort of play it forward. Let me see where, you know, am I heading on the right path and the right speed is to look at the portfolio of businesses and say, well, some of the things that took us, you know, to now, um, are just simply not going to be a big part of our future. This was my learning about the Microsoft experience that desktop Office was simply not going to be part of the future. It just didn't give us any insight on what humans really wanted to do. So we then said, well, we better like let that go. Put on life support and race to build Office 365. And I think every company has these moments, they call them cash cows or they'll use whatever words they use, but they know what things they've been hugging that have been big but aren't growing and aren't part of the future trajectory. And I think being honest and then saying I'm going to open eyed and clinically and dispassionately manage it into obsolescence and maybe even divest of it because I've got to let it go that fast, um, I think that is one of the most important decisions because unless and until you do that, it's hard to fund the future because you can't carry forward a cost structure where you keep anding everything like and this and that and the other. You have to be able to fund the future.

Speaker A: And one of the big challenges that you and I have spent a lot of time um, discussing is uh, it's not even just dollars, it's also management attention.

Speaker B: Oh yeah. The hardest, the scarcest of all. That's exactly right.

Speaker A: And how it is extremely easy to overalllocate management attention to your call it productivity zone or cash cows while under allocating to what could be the bets for the future that are not quite yet at the scale that you need but deserve that attention and that funding at the same time.

Speaker B: Yeah. And I think now you're getting at the whole management discipline that it takes. Uh, because I do think that this m continuing to honor stakeholder commitments in the present, downshifting from things that aren't going to take me to the promised land. But then a muscle about systematic tests and learn. I'm um, such a believer as you know of these four zone notion. Performance zone is bau. The productivity zone is like I'm going to manage things into obsolescence, make things extraordinarily efficient, divest. And then the incubation and transformation zones are where I'm going to place bets about reinvention and or growth. But probably in a portfolio of 10 bets, probably six or seven of those should be reinvention and maybe a couple um, on growth. And then I'm going to push one and only one bet bet at a time to materiality because I don't want to find myself in this place where I'm trying to push two or three things that get sort of mid size but never quite break out and get escape velocity. Let's get everybody focused on making a thing material and if we can do that then let's do two. Once I do one, let's do two. I think that notion that all those zones take the right management attention to your point, each of those zones has unique metrics. Each of those zones requires a certain temperament of leader. So if you don't have great optimizers who are managing the productivity zone, don't be surprised if it's very difficult for the applied innovators and deployers to be successful. It's because you're asking them to do things that are just simply unnatural and not, not possible. So I think honoring all of those uh, management archetypes and really having the right metrics zone by zone is so critical now that's I think a new thing uh, for many companies it's not necessarily so New in tech. This is why I have a certain passion having seen it in tech. In the tech sector you're rewarded for growth and you're rewarded to go find the next big growth opportunity where that's not necessarily been the case in insurance. So I think, you know, building the muscle that says it's about low growth to high growth categories and I'm going to actually start to do both things right. And be expert. Um, that I think is, is an interesting and important challenge but I think an essential one when the world is changing quickly.

Speaker A: And so building on this, so we talked about where to grow, where the puck is headed and therefore where do you want to go as we go into the where to play. And uh, uh, I'm going to set you up here a little bit and I know you like to talk about demand aggregators, ecosystem orchestrators, component suppliers. If I look at insurers, they've typically been more of a component supplier, um, in a broader ecosystem, sometimes in their own ecosystem, if they had the front door, sometimes in somebody else's. Things are evolving. We just talked about this how to think about that where to play. And my inherent bias from the outset is being a component supplier may not be the right place to be, especially if it's almost the by default decision.

Speaker B: Yeah, yeah, exactly.

Speaker A: There might be some elements where actually you choose to be a component supplier that has these advantages. Um, and that has a very clear view into how the broader ecosystem is playing. But I'm curious, you know, where do you think are the opportunities on this stack? Yeah, yeah, no, and um, what advice would you have for.

Speaker B: Yeah, yeah. I think that, you know, the word of play is so critically important. I do believe that there are these three, you know, we can give them whatever words we want but there's this demand aggregator notion of I am going to solve problems for Paul. Whatever Paul's problems are, I'm going to solve them and I'm going to do it in an increasingly intimate, personalized AI powered way. Uh, that doesn't mean I have to own the ecosystem or even orchestrate it, but I'm going to be that front door or front door is not really even a good way of thinking about it, but it's almost the Persona who's your person. Right. It's your go to around a set of needs. In this case financial wellness. Right. And I think that this notion of where to play is important sort of sector by sector, demand space by demand space. You don't expect that the demand aggregator for medical purposes are going to Be the same as your. But I think that's one. I think then there is the component supplier and you made a really important point which is, I think defaulting into that is not a good decision. I'll come back to it in a second. There's a third place which I think is really interesting is ecosystem orchestrator. My job is to begin to get the hyperscalers and the cloudifiers or the vertical solution players together to actually push a solution into the demand aggregator. And I'm going to source the components from component suppliers in an incredibly, you know, efficient, modern way. I think these three places, demand aggregator, ecosystem orchestrator and component supplier, you can make money in all three of these, but they are an explicit choice and there's very different skill sets across them. So for example, that ecosystem orchestrator, a lot of. I'm in a lot of conversations with companies who eye that think of that as a path to value. Uh, it often takes, I hate to call it biz dev because it seems to make it so pedestrian, but it takes the ability to actually actively engineer these relationships if it's going to be apiable. Figure out what that is from a business standpoint before you go to the technology. What I mean by that is what are the give gets and are those give gets reasonable and are there adequate decision rights? All these really gnarly governance questions around that, that becomes actually an incredibly important differentiating skill and capability. And then the component supplier. If you're trying to be a component supplier and you feel like your product can go into multiple ecosystems and serve many demand aggregators, that's awesome. Think about monetizing things, multiply. That's great. But then should you have direct sales, should you also work hard to own distribution? Is that a sensible thing to do? When what you really need to make sure is that your product is unbeatable, it's unmatched, uh, in terms of its economics and its ability to plug in and all these other things. So I think being very clear about those and it could be business by business, making explicit choices is going to be critically important, especially in the age of AI. Especially in the age of AI.

Speaker A: Yeah. It's interesting to take a couple of examples. It's not about can you do one without the other. It's more again about in terms of management attention, in terms of focus, in terms of the capabilities you need to build. Uh, you know, it takes a lot of effort and you know, being a component supplier is not, uh, an unrealistic place to be. No, but being able to say, I'M going to upgrade my insurance products once a year. I'm going to just make sure I have the right economics, maybe I have the right investment solutions behind this. That's not enough anymore. And you want to be able to hyper personalize two individual customers or different customer Personas. I don't like that Persona, uh, term but archetype. Even if you're a component supplier in insurance and financial services, the product could be more right. It uh, could be the insurance product, the economic promise to the customer, but also the digital engagement that comes with this or a series of services etc. We're talking about retirement. That's where you can start linking a lot of different things. If this then that.

Speaker B: That's right.

Speaker A: And that is something where for the majority of companies it's going to require a massive shift in the operating model.

Speaker B: Sure.

Speaker A: And so back to your point. Are you committed to this and are you committed to building all the right capabilities to build that competitive mode so that you do not get commoditized?

Speaker B: That's right. As you decide where to play business by business, then really think from the customer archetype. Right. The family unit contemplating retirement sandwich generation issues. Work back from that and say now what would the set of solutions need? Can I source some of those pieces, uh, from the ecosystem using agentic orchestration as opposed to having to do everything myself? Does that liberate me then to be excellent at the products where I am truly differentiated to the point of competitive mode and then let me light the way to the core sort of shared capabilities that should be present and only do those and or re engineer or rebuild or reinvent those in modern technology as opposed to you know, dealing with all of the tech debt that I might have use that proposition and what we know customers want to pay for to light the way to how I'm going to go about delivering against it. So it's thinking about the operating model of yes, but outside in and using that as a lens to figure out what is in fact needs to be modernized, how to modernize it. This is where I think that notion of new value plus efficiency and cycle time to me actually is almost most important. Cycle time improvement can you can get both right? It's not an either or but a both and done properly. Done properly.

Speaker A: If I look back to the last couple of years, a lot of players in insurance and financial services and beyond looked at AI and I feel like oftentimes it was more of a on

Speaker B: the fringes or it's a tech thing

Speaker A: or a tech Thing. While the way we're talking about this here is a. You need to start from the business problem and the customer problem back and there is a very active choice to be made about how you are going to be using AI to accelerate the build of your new capabilities. And to your point it's a, uh, both end.

Speaker B: It's both end. Yeah.

Speaker A: And growth. Uh, I'm going to go back to my component supplier example. To me using AI should be in service of. We have decided that we want to be a component supplier that's going to be providing the best solution that's tailored to the exact need of each person given their situation, given their family needs, given where they've been and where they want to go on their um, financial uh, roadmap and so on and so forth. And non financial roadmap by the way, it's not about just financial needs and therefore everything we want to do is around better understanding all these needs and tailoring. And so therefore any AI investment we'll do is in support of that.

Speaker B: In support of that. Yeah.

Speaker A: And it's not a once and done thing.

Speaker B: I want to pause on it or underscore it because right there lies all the difference in value from AI or insulating from the turbulence around AI. If I stared at AI and said what could I do with it? You wouldn't do what you just described. If you started with a solution, say how do I make it better? How do I make it unmatched? Oh, by the way, there's three more vertical LLMs and you know, another sort of, you know, new cahooser that no one's thought about. But I can adapt and adopt it to do more. Right. Then I should do that. So then it diminishes this fast evolution of the tech.

Speaker A: Yeah.

Speaker B: And says I'm actually putting it in service of doing more for the customer. That's my job. My job isn't tracking the tech, my job is doing more for the customer. And it makes I think things clearer and decision making more focused when you adopt that kind of logic.

Speaker A: Uh, so playing back your trifecta, uh, how do we build our entire business model and our operations around this? And to your point, it's cost and growth. How do we continuously evolve this? It's not a one time injection of AI or something like this or tech. It's how do we completely reinvent the way we operate.

Speaker B: And I think there, Paul, we would be totally remiss if we didn't talk about humans. And what I mean by that is there's this really important, you know, muscle that you've just articulated. Um, but again, I want to draw it out and underscore it, which is this muscle of rapid course correction and adaptation. This is not a leadership trait or a muscle that is well understood and activated in most incumbent organizations because most incumbent organizations are rewarded for sustaining the moat. M not finding the new moat. And so I think this rapid course correction, doing it in a way that humans can sustain the change. Understanding that if you're going to move an organism from old way to new way to some state, change, old state, new state, that it's going to take a lot of nudging. It's not. You can't whack at it and hope to get it to the new state. You're going to have to be able to say, okay, now you've started to collaborate, cross functionally cross product focused on an outcome. That's great. Now how do we set the next okrs and maybe what do we do to shift incentives to promote more of what you're doing that then leads you to a better future? Again, uh, an example from my Microsoft experience. I thought it was fascinating to see when and how in sequence shifting the incentive system had so much to do with promoting greater collaboration, cross organization, which was critically important to showing up as one Microsoft, which was the watchword, um, but it was all in time. Going straight to incentives isn't the answer, but standing up the right apparatus and I call it an accelerator to kind of test and learn across all management dimensions. Technology, AI and thinking through the lens of customer. Uh, these things require different behaviors and require a space in which people can learn quickly. And then every company's model for how they get to a future is going to be different because it'll be culturally appropriate as you can. There's no one size fits all there. But I just wanted to underscore that we would be really remiss if we didn't call out the importance of change and approaches to change, which I think is different. In other words, you have to change the way you change to move into this AI fied future that we're talking about now.

Speaker A: That's fascinating. I liked again the reference to the four zones where every zone requires, uh, different metrics for success, different leaders and just different motions in general. Maybe shifting to our third act here on what if and big bets, thinking about our insurance and broader, you know, financial wellness space. If you fast forward a few years, what's your view on what will feel radically different? Feel free to go either in terms of how insurers would serve their customers or how generally customers would also engage. What are your big, uh, for the next few years?

Speaker B: Well, Paul, this was a tough one for me because I think for so long I've lived in this world of looking at, you know, many of these gnarly problems that are underserved and insurance. I think there is this challenge of historically been being able to really play the balance sheet and to really make this be about, you know, safeguard the future. If I'm actually going to say I'm going to be a financial wellness provider means that I'm a very different looking company than the insurers of today. I think it's those really difficult decisions around, well, how do I save for a rainy day, how do I reduce my debt, how do I then begin to think of placing bets onto the future retirement? If I'm heading to that age, I care a lot more of that. If I'm early in my career, I'm probably more thinking about a home and a family and you know, understanding those things. That to me is a holistic financial security proposition. Having a company break out and redefine the category, that's what I'm really excited about. I'm always excited about, is there a way to redefine the category you're in? I, um, don't see any reason to stop that or prevent that. And I think AI can be a great vehicle for redefining the category you're in and unleashing a whole next wave of growth along the way. I would love to see that happen.

Speaker A: Yeah, there's some of these big problems that we've been talking about for quite

Speaker B: some time for quite a while.

Speaker A: Right. And you know, retirement is bound to become a greater and greater problem. You know, people are living, are living longer, the birth rates are declining, people have more dependence. So the problem is there. And it's a, it's not a problem that is just changing overnight. It has been building up for a long time.

Speaker B: That's right.

Speaker A: When looking at insurance and the broader financial, uh, services industry. But there is almost that notion that insurers are somewhat safe because it's difficult even for big tech to replicate what it's doing. But if you push forward, what you were saying about demand, aggregator, ecosystem, orchestrator, component, supplier, there is a risk for the insurance industry to get commoditized, uh, to being, I am just the capital provider and somebody else is busting up the value chain and is now reorienting around the customer needs and is taking the lion's share of the profit and the attention from the customer while getting supply from an industry that's dwindling and dwindling.

Speaker B: And I think Paul, we've seen some of the signs of this already. If you think of some of the big captives in the world that are powering growth in problem solving in new spaces. Amazon has bought One Medical, so that's interesting. That's not E commerce, that's not selling cloud services or workloads on the cloud. So you're starting to see movement toward knitting together solutions for different ecosystems and different sets of customer needs if the demand migrates to solving problems. And then the notion of insurance and risk management is, you know, tied to that. Um, what does an insurer do to participate in a world where, where that attention is moving to different ways of engagement powered by different data sets? I think this is something really critically important. I do think the pace with which that uh, engagement has migrated and how fast it can accelerate in an AI world is very, very real. And from a marketer, old marketers, you know, perspective again, putting back on the ad tech hat, we used to think about, you know, strong and weak signals and then building a signal factory to figure out Paul's intent. That's what we were trying to do. A strong signal is a search query. Um, a uh, weaker signal is, you know, time you spent across the engaged web or dwell time on a website or something like that. So we try to infer from that your intent inside of this substrate of chat is all. My intent.

Speaker A: Yeah.

Speaker B: And uh, my intent with memory.

Speaker A: That's right.

Speaker B: And so this to me is really, really important to understand it for what it is and to figure out how do I need to be present in that substrate to be increasingly relevant for higher order problems.

Speaker A: Yep, yep.

Speaker B: Not again. Not sky is falling, but boy don't wait. Uh, you know, I think it's somewhere between there and if I look at

Speaker A: the next 12, 18 months, maybe even next six months, what are the big shifts that you anticipate? What are we going to be seeing a lot more? And what would you say executives should

Speaker B: get ready for having lived again through seeing waves of technology? And certainly I learned this in the dot com bomb era. Big things and big shifts actually don't really become big unless there's enterprise monetization. Uh, uh, and I tend to focus my attention on players like an Anthropic or Gemini, not because I like them or I'm saying they're going to win, but because I think they're really focused on solving Enterprise problems. I think the enterprise has mostly been doing learning, I was going to say dabbling, but that'd be wrong because I think giving tools, getting people acculturated, you know, figuring out what we can do with if it's cowork or whatever it happens to be co pilot. I think it's so important to be aware of what's possible for me in this world. Okay. But then I think there's something about the end to end workflows.

Speaker A: Yeah.

Speaker B: And how those could look and could get AI ified and what the outcomes would be if I did that holistically, end to end. I think of that, that more as a reimagining or a reinvention kind of challenge. Um, hearing and sensing more of this. Yes, let's take that on. And I think that will be really critical for unleashing value because it means that what's on the other side of the rainbow is humans who are then amplified or augmented in some new ah, work stream that by the way may have inside the Enterprise, outside the enterprise kind of activity streams. That is what they're going to get to. Um, not replacing people, but having people doing very different work. Augmented, amplified, enabled. I think we are barely there. I mean we're just scratching the surface of what that can be. And so I think looking forward, I would expect that we'll see much more truly digitized and algorithm driven enterprise, um, and enterprise monetization.

Speaker A: One thing we didn't really talk about in the last hour is AI just for cutting jobs, which oftentimes tends to be the shortcut. And it's more to your point, how do you augment. That also means if you're going to be the human that's augmented and enabled, your job description might be completely different tomorrow than it is today. So there is a transformation. You were saying let's, let's keep the human in the conversation.

Speaker B: The skill set has to evolve. It has to evolve. There's no question, and back to the point about an accelerator kind of model and the building of the new muscle. It's not just the learning of the skills, it's the applying of them and the trying them on, the marinating in them, the test and learn. Like last I checked, the pace of adoption is as fast as humans can adopt.

Speaker A: Yeah.

Speaker B: And so how fast can humans adapt and adopt? I, I think faster, but I think ways of work certainly inside of enterprises have been particularly difficult to change. How do we unleash people who now have a sense because of their chat interactions at home and on the go. How do the. How do they begin to think about imagining a very different workplace? And can that allow them to go from M the back foot to the front foot? I was in some discussions with Treasury M functions and in one case being highly regulated and used to basically having to do so much work to just make sure everything's spit spot, um, as opposed to I can be a risk advisor and be on my front foot to what the balance sheet effects might be of some geopolitical um, M development. That's a very interesting thing because it actually creates really interesting work and role that currently is impossible for a whole range of reasons. So anyway, I think that notion of back foot, the front book and new work is really actually quite exciting. But I think we're going to have to invent our way there. It's going to be difficult and hard work.

Speaker A: Maybe just to close, would love to get your final words of wisdom as you think about the AI revolution uh, uh, playing out. What advice would you have for insurance executives? What words of wisdom would you leave them with?

Speaker B: Uh, maybe I'll say three things. First, I think figuring out how to be both bold and provocative and incredibly pragmatic at the same time. Like the example I often give is, you know, when I was doing the startup thing, your venture investors want you to walk in the door and you know, pound the table on how you see a new category and you're going to be the category killer. So then they go tell all their other venture investors over lunch, I've got the and so you gotta check that box. And then you have to be incredibly capital efficient like the proceeds of your money come Monday morning are gonna be. Right. So that bold and pragmatic thing I think is a very difficult thing to be because it's gonna take both. Uh, second is then to be really aligned around we talked about this earlier but that the leadership team sees the future. Not to say that they got it right, but they see it the same way and they are close, clear headed about how fast they need to move, what the risks are and that I think is going to be incredibly important. And I guess the third thing I'd say is over many years we've allowed sort of the strategy and direction setting to live in one place and then the operating model and operationalizing is somebody else's responsibility. It's going to be really important to keep all these things in lockstep and have a very compelling narrative both externally to investors that is also a change narrative and a way of mobilizing people internally you know, those would be my three big hopes and wishes.

Speaker A: Rick, thank you so much for your time. It was such a pleasure having you with us here.

Speaker B: It's always great to be with you, Paul. Thank you so much.

Speaker A: That was Rick Chavez, partner and customer first leader at, uh, Oliver Wyman. I'm Paul Rickard. Thanks for listening and I'll see you next time. For more information about our Reinventing Trends series, you can find everything on our website@, uh, oliverwyman.um com reinventingintrans thanks for listening and I'll see you next time.