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Moving the Needle: Sparking Non-Incremental Change in Insurance Technology Solutions and Business
How do we think clearly as insurance business leaders, especially when it comes time to change?
The decision is not always cut and dry. There is an analytical portion. What do the numbers tell us? There is the “expert forecasting” portion. What do the trends tell us? There are analogies we can draw from our previous experience or other industry experience. And there are feelings — which can sometimes help us and sometimes hurt us. They may go beyond simple gut instincts into the implications to our own survival or the plight of others who will have to live with our decisions.
This is what can make business decisions tough, especially those decisions regarding rapid change and development.
Yet, what makes executives valuable is their ability to address crucial decisions in spite of their uncertainty and dizzying variables. The valuable executive does the research, listens to advisors, looks at the trends and considers what is best for the company and its people.
Majesco is a business advisor. We provide thought leadership, market insights, and technology leadership that help executives with their research, their strategy, and consider options that align to their business and the future of the industry. We help business leaders think clearly on what is needed today, but more importantly in the future to remain competitive and relevant in a fast-changing market.
To do this, we often call upon those who have expanded industry expertise to help us look at common issues and the impact of them operationally and strategically. In our recent webinar, 2026 Trends Vital to Compete and Accelerate Growth in a New Era of Modern Insurance, we had a round-table discussion including some of today’s most sought-after industry experts.
Our conversation included:
Myself, Denise Garth, Chief Strategy Officer, Majesco
Rob McIsaac, President and CEO at RPM Ventures NC, LLC
Lisa Wardlaw, President and Founder 360 Digital Immersion
Jim DeMarco, Insurance Advisory Lead and WWFSI Insurance Strategy Lead, Microsoft
Denise Garth
So the first topic is high-performance insurance operating models. Many insurance operating models were crafted over decades ago around a myriad of constraints and different business assumptions. But there are a lot of micro and macroeconomic environmental impacts to this operating model today. How does the operating model need to evolve to support modern insurance?
Rob McIsaac
You know, in my career, I don’t think we’ve ever seen this much change happening this quickly, impacting so many people and the technology and operational decisions they have made or will make.
We are beginning the second quarter of the century. Significant demographic shifts will take place which impact the people inside insurance companies. Distribution networks will be impacted. It will impact consumers and the products that companies bring to market.
Because of the net long liability nature of the products on the books, companies need to be thinking in a barbell fashion.They need to ask themselves, “What do we need to do in order to effectively manage the things that we already have, which are paying the freight and keeping the organization alive, but also allowing us to make investments for the future?”
There are consumer shifts that will have a material impact on the products that need to be taken to market. How will people consider things like home ownership or family formation, or even vehicles that they drive or don’t drive? How will people be able to access those products in new and different ways?
Historically, (working at places like Prudential, Guardian and Nationwide) we would find the answer to a particular problem statement and then pursue that with all our resources. But broadly speaking, that led to one-size-fits-all solutions. Today, that approach could lead to a world of one-size-fits-none. Companies need to think very differently about their operating model as they go to market. It has implications for the products and implications for the technology and the technology relationships that companies want to build out.
Denise Garth
Insurers need to change the economics around a lot of their key metrics — loss ratios, expense ratios, risk selection — and they must release themselves from dependence on investment returns that sometimes hide what’s really happening and the inefficiencies within the operating model.
So, if insurers need to change their operating models, what do they need to change? How can they move to a new operating model that creates greater value and that can achieve their strategies?
Lisa Wardlaw
I think we fixate perhaps too much on the expense ratio and managing the expenses and operational efficiency. Yes, you have to be efficient and operationally savvy with how you manage an insurance company, carrier or reinsurer. But economics that move theneedle don’t typically sit in the General & Administrative (G&A) operational expense line items. They sit in much bigger things.
For example, with Property & Casualty, things like frequency and severity, replacement cost, repair cost…how the price of supply and lumber is exponentially going up after a major event.
So when we think of technology foundations, we need to think more on the interoperability of our derivative, our treasury, our ALM skills — in tandem with what we’re pricing, the products we’re serving and how we drive the economic yield down. That’s where we get billions on the balance sheet and not a couple of hundred thousand dollars.
What we have to go after is less incremental optimization. We have to ask ourselves, “How do we drive different products that can be priced and optimized much more efficiently?” And I think that comes into a much higher level of technology foundation.
Denise Garth
If we’re looking at a different operating model and the financial metrics that Lisa and Rob talked about, obviously, that technology foundation must be very different.
Majesco made a shift back in 2017 and 2018 to move to cloud native and three years ago to AI-native. We’re now in a world where we must go to cloud native and AI native. Legacy debt is poisoning and pulling organizations down with the inability to bring new products to market that will drive that optimization.
How do we address the impact of legacy and move into this new world of cloud and AI-native technology that can really create value?
Jim DeMarco
Right. Peter Drucker said, “There’s nothing so useless as to make more efficient that which should not be done at all.”
That is exactly where we are. We have been “incrementalizing” our improvements on existing processes for years. Yet, we’re still constrained by legacy processes as much as anything else. Legacy process was originally sort of a problem because we, if we wanted to put in a big piece of tech, we put in a big piece of tech and that tech had a well-defined process and you just adapted your company to whatever that process was. We got really good at saying, “I have a piece of tech for this particular type of offering or product. I have a different piece of tech for a slightly different product.” And now we have two different processes. Multiply that times hundreds or thousands.
With the evolution of AI, we’re seeing the opportunity to radically change that. Instead of looking at what our process is and then making it slightly more efficient, we can actually understand what the outcome is we are trying to seek and let the tech take care of itself on the process.
The challenge we have is that we’ve spent a lot of money on that tech, and there is a very huge sunk cost argument that we’re facing in inside of our operations model. The reasoning, “I spent so much money on this. I don’t want to actually change it.” is as much a cultural problem as it is a technology problem. Honestly, tech debt is usually a cultural issue.
Now we’re seeing a change. The ability to rethink how we deliver offerings or deliver outcomes faster, better, stronger, only occurs if we can rethink the process itself.
Denise Garth
There are a lot of reports out now about the impact of AI and how it’s creating real business value. But, for many, it’s an over-promised and under-delivered technology. Value, of course, has to be tied back to strategy. Insurers have to ask themselves, “How are we going to operate differently?” When companies say, “Let’s go play with AI over here,” instead of looking at the technology foundation, they can never really unlock the compounded benefit of it.
How do we solve this AI value issue from a strategy an execution perspective?
Lisa Wardlaw
We’re trying to solve problems that we shouldn’t be trying to solve for. We are trying to incrementally improve things with AI, which I call the proof of concept (POC) pilot trap.
We, as business leaders know this is a fundamental business problem. The pervasive root of the problem has been that the technology was not, on the whole, an enabler. Our technology was, in fact, a constraint because we could only go so far. We could only afford so much.
We should’ve been asking, “What does the business want? What does it need?”
Reimagine that you have technology that can achieve anything, because we’re not that far off from that being a truth. Assume that all we want to do can be done and then ask, “How do we do it in a way that is organic and natural instead of by using 20 reverse-engineered, bolted-on processes?”
You then partner with your tech team and bring in the AI and foundational technology that optimizes things like dynamic, rapid processing of decisions, real-time communication, and aggregating, and it does them all much more quickly.
What we need to do now is use interoperable systems that allow us to reimagine strategies and execute them.
Denise Garth
How is AI going to reduce friction within processes and drive optimization? What are you seeing from a level of operational optimization that will change the economic dynamics within insurance companies to drive down costs and make them more competitive? And where do you think the focus needs to be for insurers over the next 12 to 18 months?
Jim DeMarco
An old friend of mine in insurance says business said the three ways we make money:
- Sell more policies.
- Pay less on the policies we have.
- Make some money on float.
We have spent an awful lot of time in that second bucket. “Let’s just optimize, optimize, optimize!”
We started with the use of AI in internal operations and in claims because those go straight to the bottom line and the thesis was that if we can do that, we have won. But, as Rob mentioned, organizationally, it doesn’t change our structures all that much. It does not enable growth.
So we are needing to focus on the answers to new questions. “How do I adjust my appetite? What are the additional services that I can bring to bear that will be profitable? How do I sell more for what I have and sell more accurately on what I have?”
That’s going to be a fundamental shift over the course of the next 12 to 18 months.
Denise Garth
So, then how will we see companies reduce friction in their processes? Why should they take more out-of-the-box rather than heavily customizing, ensuring they can take future innovations and AI capabilities?
Jim DeMarco
It is clear that we have been able to reduce certain amounts of friction with the use of AI in processes that were just bad, but we are running out of processes that are just bad. So the next step might look like this. “Let’s eliminate processes that don’t need to be there in the first place. Let’s rethink the outcome approach.” That’s the next fundamental shift.
BCG recently stated that the insurance industry has adopted AI at a faster rate than any other industry on the planet except for tech. But they haven’t scaled it because they’ve used it on existing projects and existing capabilities.
So the shift isn’t just about reducing friction in existing programs, but shifting towards enabling the company to deliver more. That’s the shift I think we’re going to see going forward.
Optimizations worked. It’s time to start looking at growth, too.
Denise Garth
So, let’s bring this back to a cultural issue once again. We have a demographic shift in insurance employees. Retirements will bring a loss of knowledge and business expertise. We will want to redefine processes to foster insurance knowledge and also allow the use of AI. This brings us to the crux of human-centric AI.
To get the value of AI, we need to tap the knowledge inside organizations that is, in many cases, a rare commodity. How?
Rob McIsaac
Some of those things that need to be done to generate value in the future state will require companies to clean up their data or find data repositories that can actually drive some of the value.
And then you get to the human component.
Strangely, many organizations have actually fostered losing some of their expertise on the business operations side so that they could become more efficient! Companies may be down to one or two people who actually understand certain critical knowledge.
For most companies, now is a real opportunity to consider how their human capital will be realigned and prepared for what comes next. Capturing this knowledge and using it as the basis for creating a better understanding of some of the things that we do would be money well spent — getting ready to prepare for how these new technologies can be used.
Failing to do some of that fundamental work around data and around human capital actually will lead to unfortunate, very expensive work that doesn’t produce much value and ultimately heads towards failure.
One of the things that we noticed with some of our carrier clients in the past year is that the greatest value of deploying some of the AI tooling has been in the finance functions — areas where you can extract that enhanced value. They did it by co-mingling technical resources with business resources.
Business executives drive it so that they can improve their own operations and grasp what the tools are and some of their capabilities. And that can also be a pretty fundamental shift in how people think about the interoperability between technology and business areas.
Lisa Wardlaw
It’s interesting to consider this in terms of training AI models and feedback loops. If I were leveraging one thing to get a “DNA imprint” of the knowledge in my system, it would be to get the most senior people involved in the highest-impact, most sophisticated AI training integration projects.
Denise Garth
Excellent. Thank you so much, everyone.
So, in summary, we need to look at our operating models within a cloud and AI native technology foundation that offers optimized processes via AI, easy upgrades to take new innovations and provides a new foundation that makes insurers relevant today and into the future. We need to use it to drive economic and operational impact. We need to capture high-level institutional knowledge and make sure our data is in order, so that we can use AI to the best of its capability — holistically across the organization rather than as an “add-on”. This will give us results that go way beyond incremental improvements.
This will drive cyclical positive results.
There are estimates that AI within operations could have an impact of 3 to 5% reduction in expenses. That kind of improvement loop will create opportunities to adapt product pricing and other competitive levers. Three to five years down the road, you could begin to see a restructure of who the leaders in the marketplace are based on changes such as these.
So, today we’ve covered the first half of our webinar. Be sure to review part 2 in the coming weeks. If you want to get a jump on hearing the rest of this great conversation, be sure to check out the full webinar, 2026 Trends Vital to Compete and Accelerate Growth in a New Era of Modern Insurance.