Frontier Insurers Transform Their Operating Model with an AI-Intelligent Foundation

Denise Garth: Hi everyone, I'm Denise Garth, Chief Strategy Officer at Majesco and you're listening to the Future of Insurance Industry Leaders podcast series. Follow along as I interview the best and brightest leaders in the insurance industry and insuretech landscape to bring you the latest in digital transformation, innovation, industry trends, challenges and opportunities as well as next gen technologies. We use our experience to anticipate what's next without losing sight of what's now. Stay tuned to find out your next now. Hi everyone, I'm Denise Garth, Chief Strategy Officer at Majesco and you're listening to the Future of Insurance Industry Leaders podcast series. Follow along as I interview the best and brightest leaders in the insurance industry and insuretech landscape to bring you the latest in digital transformation, innovation, industry trends, challenges and opportunities, as well as next gen technologies. We use our experience to anticipate what's next without losing sight of what's now. Stay tuned to find out your next now. We're thrilled to have Sabine here with me today and what we're going to be talking about is a topic near and dear to our heart, around the frontier insurer. So Sabine, welcome and this is going to be a fun conversation.

Sabine: Yeah, thank you so much Denise for having me. It has to be a fun conversation. We are going through what we call a frontier transformation and I look forward to diving into that transformation with you today.

Denise Garth: Agenda for today, we're going to kind of talk about some of the challenges facing the industry and what is the frontier insurer and the way forward in an action plan that each of you can be thinking about and taking back to actually begin that path towards the frontier insurer. To get us started here, let's just talk about few key points here. Legacy core systems are capping ensure growth at exactly a moment when AI demands are requiring a new operating architecture. Insurers that replace legacy systems grow 1.37 times faster. Those that are embedding AI are seeing a 1.67 uplift and the gap is compounding where leaders are outpacing their peers by 20 to 80%. This just doesn't reflect differences in investment. It's really a leadership and a visionary, uh, difference in how the future is going to look for insurance. These stats are from Majesco Strategic Priorities Research out into the insurance industry. This really provides, I think, um, a foundational kind of perspective on how we see a mapping architecture and migration path to AI, native intelligent core and what you can be doing over the next 90 days from a plan perspective and also from a strategy perspective going forward. Sabine, any comments?

Sabine: I mean I love your stat when you think about that. Denise and we have had this conversation already last year. I think for me the leaders outpacing their peers is the number we need to really focus on.

Denise Garth: Right.

Sabine: I remember we talked about 10 to 50% look at those numbers, 20 to 80% and if you look at any research also from IBM, uh, Institute of Business Value, those numbers are double digits and companies which actually taking that very seriously across the operating model are going to see uh, compounding uh, results around that transformation and the ability to drive success.

Denise Garth: Couldn't agree more. I'll let you kind of take this one as to starting off Sabine.

Sabine: Sure. So when we think about the transformation we are going through, AI is not another technology wave. Actually it's highly strategic. When I talk to Fortune 500 insurers I tell them often it is actually a cultural change, it's a behavioral change as the people change. And some of the statistics we are finding out there and these numbers, some of them come from Microsoft index from last year and I hope a new one is going to come out in April. So next month of this year 82% of insurers believe AI will dominate the industry futures. It's a big numbers right. It's not any different from other industries. 40% are fully integrated into their operation. This is a very small numbers because there's so much work to be done. Governance and ethics being part of the challenge as well as creating the guardrail. 34% fully adopt AI in insurance. I mean the one who are doing it, see, I mean results which are really astronomical, astronomical. But actually when you look at the number here, this is jumping from 8% in 2024 I saw some numbers around when uh, you start looking at core transformation compared to last year, 7% of investment were uh, going into IT transformation. 7% in life in PNC, 8% in life and pension. This has doubled 13 to 14% for both sectors. So Jenny I is improving everything from risk and safety to a personal profit, uh, being able to understand the use cases which are there and actually making sure that we are doing this across the operation is going to be really important. Now the question is changing. It's not how do I use AI, how do I prompt and all the things we heard two years ago. It is about how won't we use AI in our operation and how do we do it in the right way. Those are the questions which are coming more and more from executive out there.

Denise Garth: I would say that one of the things, because we all are Attending conferences. You know, we're entering into conference season again and everybody's going to be talking about AI and agentic AI and we're doing this and we're doing that. And one of the challenges here is that it can't be kind of a bolt on, uh, thought or a bolt on capability. You've really got to think about it across the entire insurance value chain and how do you create value and business outcomes that are really going to substantially change, uh, the strategic direction of the company, really impact the financials that can really have tremendous business outcomes.

Sabine: And you know, the gap is because many insurers are still treating AI as a separate IT project rather than a core business strategy. And that is a problem. They are layering AI on top of fragile legacy architecture. And I'm sure you are going to dive into that. M. Denise Fragmented systems that were never designed to run modern AI native solution. And that is a big problem. Right, because that creates legacy debt, actively, um, inhibits growth while early movers are building intelligent cloud foundation and pulling ahead. And that is important to understand. The whole stack needs to be completely redefined and reconsidered right now.

Denise Garth: Couldn't agree more. Go ahead and start this one and I'll jump in Sabine, because you kind of pulled some of this data together.

Sabine: Yes. So one of the big themes when you think about frontier transformation and frontier firms. So a bit of a definition. A frontier insurer or a frontier firm is an organization able to drive and deliver intelligence on tap, where human and agents are, uh, collaborating with one another. So think about the project you may be setting up into your generative vehicle panel. Well, you can actually interact in this project with your colleagues and actually question the system together. Now when we start looking at uh, what true frontier is about is human are leading the project. They are making the decision, they are orchestrating things and the system is autonomously operating. So that is the baseline definition. But here right now we have a big challenge. We have a capacity gap. And that capacity backup is not a math problem. It's actually a culture and problem. And as uh, we found out when we dove into Microsoft study and I call it the manifesto around what a frontier firm should be. About 82% of leaders say they are going to rethink strategy and operation this year. So 12 to 18 years, 12 to 18 months from now, organizations are going to rethink everything because it's not just about, uh, the technology, it's about the operation, it's about the infrastructure, it's about the design of the operating model, 53% are realizing that demand productivity has increased. So we are going to see organizations wanting to do so, so and so much, but people not being able to actually to follow because there's too much work and not enough ability to deliver on the demand. 80% of the global workforce lack the time and energy to meet daily demands. I'm sure you are distracted. Every two minutes you have an email coming in. Every two minutes you may have a sleep or uh, MST message coming in. So the ability to concentrate and deliver on our activities is very difficult nowadays. And 82% expect AI agent integration within those 12 to 18 months. And so this is a lot of things happening in the same time. So demand, right, business demand is not actually being able to meet by human capability. And we estimate around 30%. And this is where 70% of the job is going to be still done by human and 30% will probably be done by agents.

Denise Garth: Well, there's another aspect to this capacity gap that we often talk about is specific for this industry. It is expected that somewhere between 40 and 50% of the employees are actually going to be retiring by 2030 or shortly thereafter. And that is going to create another level of capacity gap. But it's also a knowledge gap. It's going to be very difficult, you know, to try to kind of fill that in with people who are at a demographic that they're used to using the technologies, they're used to using a ChatGPT, a cloud or whatever it is in the way that they do their work today or the way that they kind of live their lives. And that gap is going to have a further pressure on the existing people that you have within your organizations. And we've got to find a better way to take and allow that knowledge and that expertise that they have to be able to rise to the top and take away some of that work that really doesn't add value that can be done through automation from an AI perspective. Sabine.

Sabine: Yeah, I mean, you know, I remember reading this study recently around the fact that in US there is a 16,000 gap in claims adjusters. So we need 16,000 claims adjusters. The industry need those to actually deliver on the customer demand, but they are not there. So we have a talent gap. We are losing decades of potentially institutional knowledge as experienced talents retire. And also here that current employees lose up to 60% of their time working data across banking systems.

Denise Garth: Exactly. So one of the other issues that we face as an industry is really this issue of a protection gap. It's really become a financial imperative. And in some, um, industry research, it's estimated that there's a $9 trillion global protection gap out there, of which 70% of that is around life annuity and health, uh, types of products, whether it's, you know, medical insurance, it's, you know, disability, it's life insurance, pet insurance, whatever it may be, and then a 30% on the PNC protection gap. And what's happening is, is that consumers are really struggling at finding the financial resources to be able to pay for some of the increases. Just look at what's happened with property insurance over the last few years, given all of the massive events that we've had from a natcat perspective to other types of events that have raised the cost of insurance, and even on the LNA and a side similar type of thing. And so people are trying to figure out how do they kind of balance their financials and be able to provide protection. What's happened is people have cut back on coverages that they've got, or businesses have cut back to be able to kind of manage through that. And, and at the same time, we've got a different level of expectations. We've just finished up some consumer research, Sabine, and we kind of looked at it from both a Gen Z and a millennial perspective, as well as from a Gen X and a boomer, um, the two different kind of generational groups. And while there's common one there from a home insurance cost standpoint, there's a real difference in the types of products that they're really kind of thinking about that will really kind of focus in on helping them, um, um, meet the needs from a financial perspective. So the older generation, they've got second homes, they've got to pay for that insurance, they're looking at their investments. And how do they create that into a revenue stream from a retirement standpoint where health, uh, healthcare costs are, some of them are living in areas that they want. Parametric earthquake, obviously, and there's the identity theft. But the younger generation are thinking, how do I plan for retirement? So I've got money in retirement, cyber insurance and all of those types of things. And so we've got kind of this gap of insurance needs. And part of the problem is, is that our insurance costs, uh, have risen so high because of things that have happened, but also because operationally we're not very efficient. So if we could find a way. And Sabine, you'll remember this, I made a prediction last year at ITC that, uh, we will see sometime by 2030 an insurance company that will reduce Their expense ratio by 20 points. If you were able to do that, imagine what you could do for your pricing of your products, how you could become very competitive and still profitable and the growth that you could see and more importantly we'd be able to help close this protection gap for customers. Thoughts Sabine?

Sabine: Yeah, I mean I'm thinking about some of the numbers you have here, right? Gen Z vs Gen X and boomers. I mean you know Gen Z is looking for a different set of products, right? They are seeking cyber insurance whilst boomers looking at health and vision coverage. So that means you know, when you start looking at your ecosystem and uh, the insurance companies products, well you have a new demand, right? And so you need new portable products and services to actually provide to those customers to meet their demands and need to do that at scale. And uh, that means we need to actually start looking at innovation in a new way because we are not just doing pilot and sandboxes, we need to go into that execution and so we need to have the right platforms to do that. Now looking at your protection gap, I tend to talk a lot about the protection gap from a uh, PNC viewpoint. Finding ways to do micro insurance products and looking at metrics, looking at new ways of uh, serving the customer where he or she is because they are often uninsurable individuals and sometimes unbankable. So we need to find new ways to actually enable them to access product. But all this when you think about it, it's not just a financial imperative, it is a societal one. Customers are uh, actively seeking those products because we have you know, inflation, rising health care costs and so being able to understand that generational uh, transformation and those needs is going to make I think some insurers better at uh, serving the customer than others and actually better on differentiating themselves than others.

Denise Garth: Well, kind of continue that conversation. You know we're also seeing, I highlighted this in My Trends for 2026 report earlier this year. We're seeing some uh, additional demographic shifts that are really demanding these new products. I call it the silver economy. Sabine? I've got some white and gray but I kind of keep it color so I don't really kind of try to fall into this category. But it is really this generation, particularly in the US of ah, uh, people uh, 65 or older. And it's estimated that by 2030 one in five individuals in the US will be in this silver economy. And we are seeing a growth here and the retirement age is growing but as they retire from their place of work many of them lose some of Their insurance, you know, whether it's dental and vision or medical, obviously government Medicare will come into play. But they need other types of products now and they want a uh, product that they can take their 401ks and put it into a fixed annuity for revenue stream as an example. These types of things are really driving the need for a different set of products that are going to really target and meet the needs of that demographic. At the same time as these people retire, we've got a whole new set of individuals coming into the workplace. And this demographic, many in this in the 20s and even into the 30s, it's now extending beyond that. They are shifting in that they're moving from job to job more regularly. And so as they kind of shift away into these different jobs, the desire or the need for a true group product that's priced on a group basis which is, you know, cost effective, they can't take that product with them very effectively even when it's a benefits product that they might have taken because it would have to be underwritten on an individual basis. So there is this new kind of movement happening of looking at supplemental but more importantly individual products that are offered as part of a benefit plan that when people leave their workplace they go work for somebody else. They can take those easily and continue the payments with those, but they have the opportunity to buy it when they're young where the cost of the insurance is much less. We begin to help once again to close that protection gap. And so the need of this and having data and using data be able to meet the needs of these two divergent demographics I think is really driving a uh, need to kind of look at things differently. Sabine, thoughts?

Sabine: Yeah, I mean what I hear is we are needing new products and services, right? Whether it's medical ones or any uh, products. And at the same time it feels like the employee demographic shift is reshaping work side benefits completely. I think we are moving from employer centric group product to portable individual solutions. It sounds like Denise and let me know if that's not the case. But it means I want products which are fit for purpose and align to my needs. So that means that product needs to be completely redesigned to truly meet those evolving needs. And these needs means that uh, the new product, new models, all these need to be actually completely redesigned and we need the right capabilities to do that.

Denise Garth: Yes, exactly. Back to a couple of the stats that we talked about at the very beginning. We want to talk about a uh, strategic perspective and execution advantage. What we found in our strategic priorities Research, Sabine, was that what is really interesting when we began to kind of separate out how certain companies were really focused on the strategic priorities and really executing on those and how that drove this kind of differential between them leaders and followers and laggards. And what we found is that strategic activity has to be kind of thought about as a continuous type of uh, thing. It's not an optional thing and it's a continuous thing and uh, it is fundamental to driving growth. Just doing tactical things and one offs and patches on this or let's go try this type of thing without a kind of a strategic visionary kind of view of where you're heading, it's going to be very difficult and you're not really going to get the value for the investments that you've got. And I think the multipliers that we found by those that really focused strategically and executed that they had strong growth from a premium standpoint and profitable growth was that they did replace core systems. They saw that 1.37 times more for those carriers, those that were focused on new products and business models saw it again at 1.43 times and then those focus on innovation at Ah, a 1.67 time. Now how do those all come together as we begin to talk about the frontier insurer? It's really about rethinking your business model and your operating model and it's what technology, a different set of core technology that you need to have that underpins that and then it allows you to kind of focus on that innovation and bring products to market that help close that protection gap, that help close and address the changing demographics in the marketplace. And as people retire and as we deal with the weather events and natcat types of things on uh, a P and C perspective this all fits together and it really is based on a foundation of uh, a new technology foundation and operating foundation. Sabine, thoughts?

Sabine: Well I think the key word here is a growth multiplier for strategic leaders because you have to use all those numbers and it becomes compounding if you actually uh, do the right transformation internally. This is strategic, right? It's not a one off boost, it compounds over time and this hopefully will create a widening gap between those who act now and those who do not.

Denise Garth: Yeah, totally agree. So Sabine, why don't you take this one, give your perspective on this.

Sabine: So yeah, I think the traditional response for the industry has been to harm more people and I think now that model hits the wall simply because mentioning uh, earlier the capacity gap organization have an expectation to deliver let's say 140, um, percent of activity this year, but the business can only do 100. Right. And a study shows there is a 39% gap right now. Organization will need to start leveraging agents, AI agents, autonomous agents, to start fulfilling their needs and addressing that gap. But here, the statement we are making is, you cannot hire your way out, uh, of this. It's not a math problem. It's actually now an exponential problem. And it's going to become bigger and bigger if we do not apply the right metrics and the right strategy around the business. So earlier, uh, I mentioned the definition of frontier insurer, intelligence on tap, uh, human agents working together and us human becoming agent bots. So we are being augmented by technology so that we are able to make better decision. We are history think things. We are able to be more creative and, you know, are becoming more system thinker and potentially architects. But behind that there is also a number of dimensions, and those include governance and ethics. We need to do it the right way with the right, uh, guardrails. There is also a need for ecosystem partnership. We cannot cross the frontier alone. There is also a need for AI integration, leveraging the right platform so that our experience moving from old environment, traditional environment to an hybrid and a frontier environment is done in the right way. That requires a lot of change management, that requires a lot of leadership, that requires a lot of flexibility and adaptability. So it's not a linear solution to an exponential problem. We need to look at it in a different way. As you said, Denise, people are retiring and we have decades of industrial knowledge inside the organization and we still need to harvest which is still in. You know, I was talking to nature recently. You know, a lot of that knowledge in people's mind is intellectual knowledge, right? Which is not being captured into systems. So we just need to think about how we are going to have that knowledge, leveraging the system and also create that safety, that safety net for the employee to want to be part of this transformation.

Denise Garth: Denise, the piece that I love, um, is this, that legacy processes were designed for a world that no longer exists. I think we've got to recognize that the way we've done business in the past was at a time risk was different, customers were different, demands were different, technology was different. And how we, the metrics that we use to determine business success are different in many ways. And we've got to step back and say we can't just bring all of that forward when we try to transform with a new technology. Don't bring that old stuff forward. Just a fresh start. Here to really rethink where this industry is going to be and where you want to be. It's kind of like the hit it towards the hockey puck, headed towards it instead of just kind of uh, doing the same old thing all the time.

Sabine: Yeah, I mean, you know we have talked about this in the past, Denise. Fragile AV customization, exorbitant system to maintain. You know, these are nearly impossible to upgrade and today I think you cannot afford that.

Denise Garth: Right.

Sabine: You need to think about your AI direction, you know, within your business strategy and you need to think about, you know, the vendors you are working with, you know, are they going seals to be able to operate in the future. I mean, you know, technology that organization, uh, implemented three to four years ago may not be still suitable with the new environment. Right. You need to do all this stuff to ensure they have the right operational resilience internally.

Denise Garth: Yeah.

Sabine: So bolt on may not be the right answer. And so that legacy process, you know, that world of transformation, it's not about just, you know, looking at the existing process and doing the same thing. It's completely redefining your operating approach.

Denise Garth: Exactly. One of the things that we talk about is, uh, we've been mentioning it throughout is really this replacement of core legacy and the impact that can have on growth, business outcomes and success. Many insurers are living with what we call you and I have called it spaghetti architecture. Sabine. It is a combination of legacy and it's different. You know, you got mainframe, you've got some stuff in the cloud, you've got bolted on solutions, you've got some wraparound stuff. All of this is highly customized and it's just an intertwining of a lot of legacy stuff that creates not a very clean architecture that really makes it very difficult to apply AI, let alone have really good data that's even the more important thing because that's what's really needed from an AI perspective. But it's fragile. Every time you make a change, something else breaks. And so it's very difficult to really rapidly move the business forward forward or bring new products to market when you've got this technical depth that is trapping the organization. And quite frankly I like to say it's poisoning the organization, it's pulling it down. At the same time we've had uh, a great set of new insurtechs that have come out over the last 10, 15 years. Out of insurtech we've got additional ones coming through, but we also have some zombies in the insurtech space that create some risk for insurance companies, we've got some insuretechs that are lacking the capital to uh, be able to invest in the product, in the business, to support customers. Make no mistake, when we're looking at AI as organizations, uh, there's a capital investment that has to be made both in the infrastructure as well as in the solutions that you have, but also in the people. Because you need those data scientists, you need those people that can really kind of do some of this stuff. And as a result of all of this, we may have had some preferred vendors that were pre AI period that now may be at risk. Think about a lot of the document ingestion. There were some technologies out there that now with AI, those insuretext really are pretty irrelevant at this point in time and I think we'll begin to continue to see that. So selecting the right partners, partner with and to create that technical foundation really needs to be really strategically thought about so that you're not in a place that, oh my gosh, now I've got a partner that can't continue that level investment and you can't keep the organization moving forward to this era where AI is going to be a really foundational element in how we really run the business. Thoughts on that, Sabine?

Sabine: The only things I'm going to uh, add to what you just said, Denise, and it's just extending what you said, is when your most experienced people are retiring and taking decades of institutional knowledge with them. Right, and we already talked about that. When your team are spending the majority of their day navigating fragmented system. Well, adding more people is not going to close the gap. It does add to that cost base. Right. And this problem is compounding, by the way, architecture that many insurers built many years ago.

Denise Garth: Exactly. So what is the way, uh, forward? Sabina, let's take the lead on this one.

Sabine: So I already introduced this concept, so I'm going to repeat them because I think they are very important for everyone listening to both of us. They need to really understand the definition because it's going to redefine the way we do things. A frontier firm is powered by intelligence on tap, run by human agent teams and defined by new role. Every employee within the organization is an agent boss or an agent manager. That means that as individual we become orchestrator. If some of you have looked at the recent MIT study which looks at the future of business model, well, a lot of insurers still sitting in this existing box, right? Existing process. But those who actually evolve in their business model are going to become true orchestrators and when you think about that frontier firm, well this year, and usually the studies say it's a 5 to 10% of organizations that dramatically outperform peers in every single industry. It's not just insurers, it is all single industry are going through that frontier transformation. So what are they doing? They're integrating AI into their core operation. Not learning on um, top right. They are redesigning workaround outcomes. Uh, so we are not thinking about function, we are thinking about outcome. Uh, when you put something on ChatGPT, it wants to produce an outcome, it cannot stop. It has to give you an answer. What that means is we are going to move from org chart to work chart. And one great analogy one executive gave me a few months ago is we are going to start working like the film industry in terms of projects. You know, we are going to work on projects we want to the next project. We are not really going to m be aligned to the org chart within the organization. That means we need to start understanding how to build human agent teams where every employee become an orchestrator. Some research talks about that human agent ratio and I'm going to do a bit more work on this because all of us have seen the announcement from kinsey. There are 40,000 employees, there are 25,000 agents. When M you actually start looking at that ratio, it's 1 to 0.6 agents. This is actually nothing. When you think about the exponential transformation we are going onto, it might be 1 to 10 or 1 to 100. And earlier today someone mentioned what about 1, 2 million? We don't know. I know for complex activity like some of the commercial lines claims process it might be 1, 2, 3. But you know, for some of the process which are highly repetitive, highly mundane, it might be more than that. But for that to be successful we need to have governance and ethics embedded into the system, embedded into the process, embedded into the core of the environment we are working with.

Denise Garth: I, uh, totally agree. And I think one of the really important points is that redesigning work around outcomes, not functions and that is really kind of breaking away from our traditional views of how we organized internally into functional areas rather than organized around how work could be done, leveraging the technology and really freeing people up to do some things. At the end it's the customers. It's almost like taking an outside in perspective from the customer view instead of how we've um, always organized internally. And I think one of the things we'll talk about is that this really sets up that this is not just a technology initiative. This is really to something you said earlier, Sabine. This is really truly a leadership and cultural, uh, initiative that has to be driven from the top down.

Sabine: Absolutely, absolutely. No doubt.

Denise Garth: All right, first up, intelligence on tap. I'll start with this in just a little bit and then you can pipe in. When you look at intelligence on tap, you know, AI, um, becomes embedded. It's a part of being able to provide the information. When we think about where some of the activity is going that M. Sabine mentioned earlier, we're thinking a lot about, you know, there are insurers that are doing some things around AI. Maybe they're using it to try to develop code, but maybe they're using it to do some other things, you know, within a claims process or whatever. Some of those initiatives are separate projects that it only gives you isolated value and really isolated business outcomes rather than really kind of rethinking and looking at the entire process. That's the difference between, you know, a legacy insurer and a legacy insurer thinking versus a frontier insurer. And that is, is that they want to have AI embedded across the entire end to end value chain and, and across that core to be able to allow at any point in the process that you can have intelligence information and data that comes up or an agent that can do some things that will help them actually do their jobs better and serve the customer in a much better way and ultimately get better business outcomes. This requires real time access to data because all of this stuff is happening in a real time, uh, basis. So what that means is that we're once again seeing a shift in the foundational technology that we need. As insurance companies, we saw that shift when we shifted from on prem to cloud. Now we've got to go from cloud to AI native and uh, that is on the cloud because you need to have those technical architecture foundation from an infrastructure standpoint of cloud and to be able to have access to all of that real time data that you can kind of serve up and leverage across the agents that are working across the core. And it is built in, it is not layered on top of. You may have some point things that you want to do from an AI perspective, but ultimately you've got to think of a way that it can be built in across the value chain, that it creates that accumulative, uh, value. And without that it becomes very difficult to see the real potential and the real business, um, value of AI. Sabine?

Sabine: Yes, I mean the point I want to focus on is covering the outcome here. So the results, you know, business users, complex competing complex tasks in 30 seconds. These are the type of mentality we need to start rethinking, right? Because the Frontier insurer is not a traditional insurer that bought some AI licenses. It is an entirely new enterprise architecture. Uh, they need to think about. The model rests on the script killer. So we are going to digitize this on top right now. But some of the conversations I'm um, having is how do you do that? For example, uh, when you are building an ecosystem of partners, then you start implementing a framework which is called the venture client model. When you start looking at the venture client model, you need to be able to iterate um, your experiment with all your live testing to go into execution with your partners. I said 333, three months to validate, three months to adopt, three months to scale. It's a very different mindset than the 12 to 18 months process we've been used to. So it's about um, redefining completely the way we do things. And the old operating model, distribution, marketing, product design, operation finance, all this is going to be completely reshuffled because you may be orchestrating across departments, across function to achieve a very spec.

Denise Garth: So pillar two of uh, the frontier in cherub. Over to you Sabine.

Sabine: Well that is where human and agents are teaming together to redesign completely the way things are done. So in this world, right, human professionals focus on complex tasks, not the simple one. We are actually giving the mundane and repetitive task to the agents. We are focusing on empathy. This is becoming one of our core skills, right? We are sensitive to, to people's skill set or to people's um, needs. Another things which are very good in insurance is relationships. So we are actually also optimizing on relationship development. Corporate brokers, right, are um, focusing on those relationships more and more. Then when you start looking at the underwriters, it's about looking at the portfolio of risk and building strategies, but also about exception handling. So when I look into what that future looks like, what you find is a lot of the roles are completely going to be redefined. For example I said marketers may become sales enablement strategists, uh, underwriters will become, as I said here, portfolio risk strategists. And when you think about claims adjusters, it would be empathy, um, organization providers. When you start looking at how the technology augments the individual, the role is going to change. And what I can see also from the research is, you know, upskilling and reskilling is going to be critical. 4 out of 10 of the skills we have today are going to disappear completely. Four out of ten of the skills we have today are going to disappear completely. So we just need to be mindful of that human agent ratio and where the technology is going to support the human to actually deliver more complex activity. And us, uh, actively behaving as, uh, strategists and orchestrators.

Denise Garth: Yeah. And I think in this process of redefining what that human agent individual and the teams are doing and redesigning the work is really thinking about what does that mean from a job standpoint and the skill sets that you're going to need for employees going forward, it could be very different than what you have today. And those are some of the real kind of cultural shifts that we've got to start thinking about and talking about as we're kind of doing some of this work at redesigning how we're going to be leveraging this technology.

Sabine: Another thing that comes to mind, actually, Denise, is think about what you said earlier. In the legacy term, AI is a project.

Denise Garth: Right.

Sabine: They're looking at it experimentation. It's in the corner. But when you think about Frontier.

Denise Garth: Right.

Sabine: Frontier insures, it's where the intelligence is embedded in the foundation of what they do.

Denise Garth: Right.

Sabine: And the other day I was talking about the first and the second industrial revolution where we, uh, have steam power and moving to electricity. We need to think of it like electricity. You do not have an electricity strategy. Electricity is just there powering everything you do every day. But it requires a cloud native intelligent core where AI is built directly into policy admin, billing, claims and writing.

Denise Garth: Right.

Sabine: So only there, you know, you start moving from an operator to an office trader, and then you are starting building strategies in very different ways in seconds. So that is something we all need to consider as part of this redesign.

Denise Garth: Yeah. And I would just say, you know, there's such a huge opportunity because insurance companies are sitting on a lot of information and data. It may be in lots of different forms and stuff, but imagine the power that exists in being able to pull that information together, to provide insight and to provide knowledge and expertise to the organization and the work that they're doing. It's really exciting to see that because it's really a transformative opportunity. All right, pillar, uh, the next one, the AI divider. You know, I think I'll get this one started because once again, this kind of it comes from our Strategic priorities research, where we asked some questions this year on both what insurers are doing from a gen AI standpoint and also from an agentic AI perspective. And we categorize it again once between leaders, followers and laggards and there's a lot of activity. Obviously the early movers or the leaders are really focused in on both Genai and agentic AI, but across the whole value chain it's not just oh, let's try this little thing here, this little bolt on over here. And they're really looking at how they're going to build this out and expand upon it with a cloud foundation across their core. They really need uh, they're also really focusing on how they're getting access to all of their operational data, being able to have access to that and use that as they're building out these different agents, um, or using it from a Genai standpoint. Just think about the opportunity within some of the solutions. You're bringing on these new employees that are replacing some of the retirees. Imagine if you could actually ask Jenny, I how do I do, uh, an amendment to this policy and it would come up with the steps to be able to do it. Imagine how quickly we could get people up to speed to be able to do some of that and then expanding upon that with actual agents that are going to help them actually do some of the work, the monotonous stuff that you mentioned Sabine, and be able to really add value to that. I think what's interesting is that when we saw the difference between leaders, followers and laggards, there is some real gaps once again emerging here. And it is really the gap tied back once again to legacy debt and legacy core systems. But it is that it's still an experimental rather than a strategy. And so those that hold on or hang on to their old legacy systems are only going to put themselves further and further behind because the exponential pace of change and adoption of this is only going to grow. And what that's going to do is have a wider gap between the financial and business outcomes of insurers that are leveraging it versus those are not and moving towards this frontier insurer, Sabine. Thoughts?

Sabine: Well, I mean this slide shows the stark reality of where we are now.

Denise Garth: You know, a digital agent and all

Sabine: the operational mechanisms just in the claims extracting data via computer vision for example. We've seen a lot of startups focusing on that in later years, you know, with verifying policy status, detecting fraud markers, preparing settlement. That's where you know, I think the human provisional now focus on that complex appeals. You know what I was saying earlier, empathy being at ah, the core when you start dealing with sensitive claims data, uh, uh, broker relationship, ethical oversight. So the I then start Ending with volume, the human and also value. And that is where the things is changing, right? Volume versus value. Optimal balance between the human oversight and agent efficiency.

Denise Garth: Pillar three. Over to you Sabine.

Sabine: Yes. So then we uh, have all of us becoming agent bosses where we start orchestrating an environment. So as orchestrator we are orchestrating what we call digital labor, digital workers. So all these little AI agents now, um, becoming your digital workers. So mid level claims handler manage a fleet of AI agents processing thousands of claims. What I'm saying, you know, when I think about the human agent ratio, we don't know yet what it's going to look like, but it might be 1 to 100. You might focus on an exception, edge case and uh, institutional requirement and judgment. That may be one to three. So neurals will emerge, right? AI trainers, AI data specialists, intelligent resource teams, you know, underwriting portfolio managers. And so we need as organizations to start reconsidering what this means from a biblio debt. We've seen a lot of announcements amongst insurers who are reconsidering how to rely on employees to the work when they actually move to this human agent environment. And what they are going to try and do is to reduce that behavioral debt to make sure that they are actually working with a team. An environment where everybody is able to make mistakes, right. Working with those agents, but also are part of the transformation and feel comfortable to actually make sure they can build with the cooperation that frontier environment.

Denise Garth: I'll let you take this one and I'll add in as you go along here. So the six layer frontier firm.

Sabine: Yes. So as uh, I've been doing some research around this operating model redesign, I also realized that when you start looking at an intelligent core and looking at the different ways that businesses have been building operating model design, right. You have the as is and you're into the to be. Well I can actually see that this is going to be completely different when you start looking at the transformation we are going through. So you need to start thinking about agent customer experiences, right? Where every customer managed by uh, a network of AI agents. So it's all about personalization, productive partnership. And this is conducted at scale. Then you need to start um, thinking about intelligent creation engine where agents comprise the full product life cycle. Uh so when you start building products you are going to stand for patterns, trends, white space, opportunities. So the way you are designing products is going to be really different. The third layer is around autonomous value chain where uh, we have our claims underwriting, our um, billing. All this is going to be Supported at the core to workflows by uh, AI agents where actually the human then is elevated into that agent boss becoming an orchestrator, a supervisor managing complex and ah, exceptions. Then you need to think about your cognitive corporate uh core which is where hr, finance, legal sits as well. Then I can see dynamic governance and strategy, strategy and ethics score to build this. And it's not things we need to think after. It needs to be thoughtful from the outset uh, where we have the right guardrail to manage those agents to monitor what they do and making sure that they don't put um, a business into reputational risk. And then you have this intelligent fabric where you have these AI and data meshes which are actually underpinning the way the business is built on top of that intelligent core.

Denise Garth: I think these layers are just absolutely phenomenal and I think that thinking through those and how that, what that means to how you need to really kind of rethink your, both your technology and your business architectures and the solutions that you've got is really, really important from a foundational standpoint because these have to work upon that. And I think what's interesting is in the next couple of slides Sabine is what are some actual things being done that are showing some of those results. So I'll let you take the Simply Health one.

Sabine: Yeah, I mean when you think about CPS and just so that everybody knows that we just done the market research and we wanted to identify the best in class examples which are actually going and be moving towards becoming frontier organization. Simply Health doubled their daily customer capacity without adding a single headcount.

Denise Garth: Right.

Sabine: So they kept exactly the same headcount. 40 to 50% of customer interaction and autonomously claim processing dropped from 5 to 7 days to less than 1 day. 99% of claim satisfaction and average employee pay increased by 35% with zero job loss. As I said they also achieved a 92% reduction in email response time and a 67 percentage reduction in contact volume. This is agentboss paradigm working in real world actually 101.

Denise Garth: I love this. The next one's actually really interesting too from a uh, PNC perspective.

Sabine: Yeah, that is aig right. Turning one underwriting into five with agentic AI. I think it's an interesting case study when you think about it because uh, what they've done by implementing AI agent, they made their underwriter superhuman super powered human and that's enabled them to uh, transform the organization by uh, delivering 26% increase in submission volume uh at Lexiton, 35% improvement in submit to buying ratio and partly for the middle market property. I think a lot of insurers are looking at that middle layer at the moment and uh, trying to find the right automation to serve that customer group. Seven business lines, um, deployed by AIG assist underwriting tools and $1.6 billion uh, achieved within their specialty underwriting practice as well by uh, agentic AI deployment. So all this can be found online. Actually there are great case studies which are talking about those case studies.

Denise Garth: I love those as real life examples. And the next one up, I'll just give you from our perspective from both our NANH intelligent Core and our PNC Intelligent Core, we've actually done benchmarking on the Genai and the agenti use cases that we built into the solution across the value chain from underwriting all the way through claims. Uh, we have some new ones coming out next week uh, that we'll be announcing and it's included in this. This is just one of those benchmarks based upon if you would do it the traditional way within the solution or if you would use it with um, the AI capabilities which include intelligence. It actually includes the three kind of pillars that you talked about Sabine. Uh, within this, I think it's pretty astounding when you look at the number of hours saved and this is just a baseline depending upon your, the volume of the business and the number of people that you do across the different um, uh, uh, uh, business processes or the different business areas. I think what's really important is that this is really operational savings. You know, um, you know we're talking some significant dollars here and it isn't necessarily about removing people from the job. It's that you can do more business with the same number of people. But what that does is it actually drives down that unit cost and that expense ratios and we actually believe that it actually at a minimum will actually impact positively the expense ratios anywhere between 2 and 5% and that's only going to grow. So that target that I put out there, Sabine, for 20, 30 of um, a 20 points, I think it's real and I think the matter of people actually doing it, when you see the two use cases that you did and what we're doing, I think this is real, really is opportunity for really powerful change within the industry.

Sabine: Uh, no doubt, no doubt. So I think CIO will always ask how fast can we go live when they start seeing those numbers and how fast can we iterate? And then the other things which come to mind is with this power comes responsibility. Denise.

Denise Garth: Right.

Sabine: How do we Go about the transformation. This is going to be super important part of the equation too.

Denise Garth: Yep, uh, absolutely. This is one of those things too that from a speed to value standpoint gets into this defining metric. You know that if you've got core solution that can really try to keep up with the pace of AI, it's more than having the AI built into it. It's the ability to be able to take the upgrades so that you can take these new AI capabilities. And I think one of the things that we've really focused in on Sabine, to really allow our uh, customers to be able to take advantage of the new innovations, the new AI capabilities is that we needed to change how we did upgrades. We really put in a lot of time in that. And so now in the latest release on average it's 10 days to actually upgrade and then you can take those additional new capabilities. Now you're able to do complex configurations using the natural language. That's one of the things that we're working on have focused in on and then you know you've got the ability and when you're on the front line with service people and they're asking a question, you can use copilot, um, go into the claims and give me all the information on this claims so you can be talking intelligently back with those customers and able to really kind of give those service responses and create that trust with the customer and that satisfaction with the customer. So it's really, really powerful to be able to do that. Sabine.

Sabine: Yeah, absolutely Denise. I mean we have to admit that some really incredible number here. It's backed by recognized um, independent outfits. So congratulations with those numbers. Speed of value is not a marketing claims here, it is our virtual reality. So very nice.

Denise Garth: Yep. So being governance, kind of wrap this up here over the next slide or two.

Sabine: Yeah, I mean I was just going to add governance is your way to graduate autonomy and make it functional. Right. There are three stages to do that. First is, you know, think about stage one as being in Copilot, human led, AI assisted. So that's when your AI drives and suggests but the agent boss reviews and approves every output. Your second stage will be autopilot where AI lead and human supervised. They execute within script guardrails. The human manages exceptions. And your stage three is what we call autonomous execute system. Governs swarms of agents handle end to end processes monitored by guardrail's agents. You have to before you run. And so it's very important to think about your governance when you set that up and it needs to be set up upfront. And it's not about just accelerated, it is transformation. And you need to make sure this is safe and sustainable in the long run.

Denise Garth: Yep. And I think you should expect your solution partners to be able to share how they can show that auditability and that transparency that can support this governance aspect too. Sabine?

Sabine: Absolutely.

Denise Garth: All right. The roadmap off to you, Sabine.

Sabine: Yeah. I mean, when you start looking at that strategic roadmap. Right. You need to think as to how you go about doing this, I think. Imperative one, radically modernize the core.

Denise Garth: Right.

Sabine: Not incrementally. Your core must be able to run, uh, agents or the rest of the conversation is just academic. Right. Imperative two, it's about auditing your behavioral debt. And we talked about it. If your teams are still incurred in manual work around, the technology will underperform. So you need to be prepared for that. Imperative three, it's about embracing the agent boss transformation. Invest in your people. People still going to be number one. Do not just think about replacing them. It doesn't work when you think about transformation. It's always about people, process and technology. Imperative four, it is pivot from protection to prevention. Right. We talked about the protection. Use the data stream flowing through your intelligent core to predict emerging risks before they escalate.

Denise Garth: Absolutely. And then finally your migration roadmap. Four phases to intelligent core. You really got to do this strategic assessment and assess what it is your core landscape is and assess how you're going to move away from that and a phase migration away to an intelligent core. You've got to configure and validate and you really want to take as much out of the box as possible. Most solutions have out of the box today so that you really are focused on what your unique areas of competition are. It's always about your product, your pricing, your underwriting and the channels that you're selling through. How you process business isn't necessarily your secret sauce. And so leverage what's out of the box so you can take the innovations in the AI capabilities that are going to change the way that the business is processed. You migrate and go live and then you begin to optimize and scale and put more of your business onto that platform to be able to really kind of fully transform that organization, um, as you go forward. Any comments, Sabine?

Sabine: I think what you just said is perfect, Denise. I mean, it is a roadmap and you need to think about how you are assessing things to actually be able to implement fast. We are in time of velocity. Right. Speed of change and we need to think about that as well as we actually implementing today with that.

Denise Garth: I haven't seen any Q and A come. Um, we must have overwhelmed them and they've got a lot of thinking that they're doing so. Because Sabine. Yeah, what I would tell the audience is Sabine, along with Jim DeMarco from Microsoft and Manisha from Majesco, and hopefully, uh, another individual will have a main stage, uh, session at InsureTech Insights the first week of June. Please, if you're attending, please come in and stop by. But feel free to please reach out to both Sabine and I. Both of us will be sharing some additional information out on LinkedIn. Sabine is pretty, uh, prolific as I am and we'll be commenting back and forth on each other on this whole concept of the frontier insurer. And what does that really mean? And I really encourage you all to really kind of engage with both of us. Sabine.

Sabine: Well, I will say looking forward to interacting and seeing you at ITI New York in June and also seeing you in London on the 18th of June as well, Denise. But thank you so much for welcoming me.

Denise Garth: Yep, thank you. Have a good day, everybody. That's it for this week's episode of Future of Insurance Industry Leaders podcast. Subscribe to our market leading podcast series, available wherever you get your podcast from. Thank you for listening and be sure to tune in the next time.