Insurance has always been about adapting to uncertainty, but the pace of change sets today’s risk landscape apart. Economic volatility, behavioral shifts, geopolitical tensions and technological disruptions now evolve in real time. Insurers aren’t just assessing risk anymore — they’re trying to keep up with it.

That’s where artificial intelligence steps in. More than just a technology investment, AI is a response system; it can help carriers adapt at the speed of risk itself.

However, AI’s impact isn’t uniform across all lines. How AI adds value depends on whether an organization’s goal is efficiency or effectiveness.

Personal Lines and Small Commercial: Boosting speed and accuracy

In personal lines and small commercial volume is king. Profitability is highly dependent on a number of factors including speed, accuracy and consistency across thousands of transactions each day. For these carriers, AI delivers measurable results by streamlining operations. By automating repetitive tasks and enhancing decision consistency, AI enables personal lines insurers to boost throughput, cut costs and elevate service levels without compromising accuracy.

A U.S.-based digital insurer recently deployed AI across policy issuance, claims and customer service. The results were dramatic:

• Policy turnaround times dropped by more than half, allowing near-instant processing.
• AI-led fraud detection improved claims accuracy while accelerating payouts.
• Chatbots reduced call wait times by 70%, freeing up human agents for more complex needs.

These changes didn’t just boost efficiency — they reshaped the customer experience. AI helped the insurer achieve scale without sacrificing precision, turning standardization into a strategic advantage.

Large Commercial and Specialty Lines: Sharpening human expertise

Unlike low complexity, fast issue lines, large commercial and specialty insurance operate not on speed but rather on insight. Whether it’s large property, marine, energy or cyber risk, each policy is unique, high-stakes and data-intensive.

An Australian specialty insurer integrated AI into its workflow, reducing underwriting cycle times by 35%, improving pricing accuracy across multi-jurisdictional portfolios and accelerating regulatory reporting with automated compliance tracking.

Rather than replacing human expertise, AI sharpened it, aggregating disparate data, modeling complex scenarios and providing context-aware recommendations. The result was not simply faster decisions but smarter ones, making complex risk more manageable and measurable.

The new equation: Efficiency + effectiveness

The real transformation in insurance won’t come from choosing between efficiency and effectiveness. It will come from knowing when to lead with each and support with the other.

• Efficiency ensures scale, speed and consistency.
• Effectiveness ensures sound judgment in complex, high-stakes decisions.
• AI’s true potential lies in bridging the two, creating systems that adapt to both.

As governance and compliance frameworks evolve, insurers must ensure that AI-driven acceleration doesn’t outpace accountability. The leaders of tomorrow will be those that use AI to enhance human decision-making.

The future of insurance is adaptive

The next generation of insurance will be defined by who enables smarter decisions. Personal lines and small commercial will continue to harness AI for operational leverage. Specialty and large commercial insurers, including brokers and MGAs, will rely on it for analytical depth and precision. But the real winners will be those who blend both approaches, creating hybrid models that can flex between speed and sophistication as the situation demands.

The goal isn’t just faster insurance: It’s smarter insurance built on systems that think, learn and evolve alongside the risks they’re designed to protect.

Partnering for intelligent ops

For insurers seeking to harness AI without overhauling their internal infrastructure, Cogneesol offers a scalable bridge between innovation and implementation. Our insurance solutions support everything from underwriting and policy administration to claims and analytics. By combining data, automation and industry expertise, Cogneesol helps insurers reduce operational friction, enhance compliance and turn digital transformation into measurable performance gains.

About the author

Ilya Filipov is a strategy-driven insurance and technology executive specializing in growth, partnerships, and operational transformation across the P&C and legal ecosystems. As Head of North America at Cogneesol, he leads go-to-market, alliance development, and client success for brokers, MGAs, carriers, TPAs, and law firms — helping them modernize operations through AI-enabled intake, back-office automation, system integration, and scalable BPaaS solutions.

With more than 15 years of experience spanning carriers, insurtechs, and distribution networks — including leadership roles at Total Expert, Talkdesk, and Westfield — he brings deep expertise in product strategy, commercial partnerships, revenue operations, and complex service delivery. Filipov is known for simplifying operational chaos, architecting data-driven transformation, and building durable growth engines for mid-market and enterprise clients.

Sponsored by Cogneesol

Robert Marshall is the founder and CEO of Whisker Labs. Whisker Labs, a spinout of Earth Networks, delivers next-generation home energy intelligence technology to realize the full potential of the connected home. In 1992, Marshall co-founded AWS Convergence Technologies, the company that would become Earth Networks, by pioneering the networking of weather sensors and cameras using the internet. By developing groundbreaking technology to find "signals" — valuable, meaningful intelligence — in big-data "noise," Marshall improves people's lives and protects their livelihoods. He has appeared on CNN, BBC World News and ABC Nightly News and has been quoted in major news outlets that include the New York Times, the Washington Post, Nature and Scientific American.

Paul Carroll

One of my goals for the Predict & Prevent movement is that it will be able to lay out a clear economic argument, showing that the savings are greater than the cost of the investment in prevention. You and the Insurance Information Institute, the Triple-I, recently reported on a study that found significant savings from installing your Ting devices in homes. Would you start us off by telling us what you found?

Bob Marshall

We document that Ting prevents 0.39 electrical fire claims per 1,000 home-years. If you multiply that by the severity, which has gone up considerably over recent years, then you get to $81 per year per home in savings from Ting. 

That's obviously greater than the cost of a Ting, and that's why insurers love the idea. Not only does it protect their customers and create a great experience and good engagement, but it delivers a clear ROI, paying for itself and beyond.

Paul Carroll

And the benefits are actually greater than the cost savings on fire damage, right? Preventing a fire keeps a family out of danger and saves them from a huge amount of hassle and dislocation.

Bob Marshall

A fire is often devastating for the family. You could lose pets, you could lose lives, the whole thing.

The savings on the insurance side are higher than what's calculated there, too. There is also the cost to the agents, who often have to work with families every week for a year or more to try to itemize all the losses and damage from a catastrophic fire and help them recover. 

The best claim is one that never happens. To the extent we can prevent fires, it's good for everybody.

Paul Carroll

You’ve said that people who install a Ting may become more open to other Predict & Prevent initiatives. I'll share a Triple-I blog on the topic, but would you briefly explain how that works?

Bob Marshall

Homeowners have an innate fear of fire, so when a carrier partner offers them Ting, they're very motivated to say, “Yes. I want that.”

We've worked really hard to deliver a simple and seamless experience for the homeowner. You just plug the Ting into the wall. Setup takes two minutes. Then we deliver valuable information every week with summary reports, power outage notifications, and other beneficial insights.

If you lead with Ting and the homeowner opts in and has a great experience, then when you follow with, say, water, they're much more likely to say, "Hey, I like this fire thing the carrier offered me. I think I'll do the water thing, as well."

Paul Carroll

What’s the latest on the number of homes you’re in?

Bob Marshall

We currently have over 1 million active homes in our network. We're consistently adding 40,000 to 50,000 homes per month, so we're growing very rapidly.

The ROI report was super important for us. Gathering enough data to document results is never easy when you're dealing with low-frequency perils such as fire and even water damage. You have to have a lot of data to properly document the loss prevention, but we have that now. We overcame a number of obstacles with that research and paper to make the results really clearly documented, which is awesome.

Paul Carroll

If you do the math, based on the current number of homes you serve and the prevention of .39 fire claims per 1,000 homes, you’re preventing some 400 fires a year. And the number will only grow as you expand your reach.

The last time we talked, a few months ago, 30 carriers were working with you to provide Tings to their customers. Where do you stand now?

Bob Marshall

I think we're at 34 now, and obviously going up. At this point, it's pretty clear most every carrier is going to work with us because Ting is proven to work. 

We're trying to make the experience more seamless and easier for the carrier, because partnering and distributing loss-prevention devices isn’t something they naturally do. And I think we're pretty much there. 

Paul Carroll

I assume it’s important for insurers that you automatically verify that a Ting is plugged into a wall socket and active, not just sitting in a box, unopened. I know home insurers struggle to not just know that an owner has a security system but that it’s activated.

Bob Marshall

Yes, absolutely. The way we structure our partnerships with carriers, Whisker Labs doesn't get paid if the Ting is not installed and active. We're structured in a way where we're 100% aligned.

Paul Carroll

What progress have you made in your international expansion efforts, and what challenges are you encountering given the different electrical standards globally?

Bob Marshall

We are working on opportunities to expand outside North America, though I can't talk about it too much. I think I'll have more to say on that in the coming months.

The electrical problems and fires are worse in many parts of the world. The electric codes are not as rigid. The buildings are older. The homes are older. The wiring is older. The voltage is higher, which creates more potential for the arcing that can cause fires.

The opportunity for us to prevent fires is even higher outside North America than it is here.

Paul Carroll

How does your technology help monitor electricity quality, particularly for data centers and other situations where reliable power is critical? I’ve read that increased demand is degrading quality.

Bob Marshall

We are doing a ton of work in that regard. Bloomberg actually did a comprehensive analysis a few months ago using our Ting data along with a database of data centers. What's clear is that the power quality for homes in the vicinity of data centers is materially worse.

With bad power quality, your large appliances like air conditioners, water heaters, refrigerators—anything with a motor—their energy efficiency is materially reduced. Air conditioners are half of the energy used in a home. If you reduce their energy efficiency by 15% or 20%, that's a material cost to the homeowner that is hidden. We also see that other power-quality problems—outages, power surges, brownouts—happen much more often where the grid is stressed in the vicinity of data centers. Our preliminary analysis suggests that costs to homeowners from poor power quality can be up to $1,000 per year. 

It's not exclusively near data centers. In general, with the grid becoming more stressed because of the demands and complexity, we're seeing a decrease in the power quality that is very clear and unambiguous.

Paul Carroll

Your network of sensors is proving to be useful in pinpointing grid problems that could lead to wildfires, such as the Lahaina and Eaton Fire disasters. What progress have you made in delivering this critical information to utilities ahead of time rather than retroactively?

Bob Marshall

We are working extraordinarily hard on solving the problem, and we are making some progress.

One key issue is trying to pinpoint the exact source of any given fault that could cause a wildfire. We can do that reasonably well, though we still have work to do. 

When you look at cases like Lahaina and Eaton, our data shows that the entire grid was under incredible stress and was experiencing a high frequency of faults for many hours in advance of the wildfire ignitions. Faults occur when tree limbs touch a wire or wires touch each other, and each incident can produce a spark that ignites a wildfire. Most don't, or we'd have wildfires everywhere.

What our data could help utilities with very quickly is seeing when their grid is stressed and making better decisions about shutting off the power. If you shut the power off, there's no energy to create the spark that causes the fire.

For some of these devastating wildfires, the only solution is to prevent the spark, because when you have 70 mile-an-hour winds and dry brush, there's no way to stop a fire once it starts. There's no amount of water or firefighters that can contain it. But that's a tough decision to turn off power to any community, and utilities have for decades focused on keeping power on essentially at all costs.

Paul Carroll

Any closing thoughts on the industry’s move toward a Predict & Prevent model?

Bob Marshall

We're excited, and we really appreciate that The Institutes, Triple-I, and the insurance sector are embracing the Predict & Prevent future.

I think that vision is so key, and the direction that you all have helped establish is truly taking hold. We're pleased to be able to make our contribution to it and hopefully help drive it forward.

Paul Carroll

Thanks, Bob. I always feel more encouraged after we talk. 

Almost exactly one year ago, we published our thought leadership article "Embedded Insurance: Major Disruptor Can Bridge Huge Coverage Gap."

We pointed out that embedded insurance isn't new and that the wide-ranging, "at point of sale" opportunity is significant. Purchasing life insurance at the airport before flight departure was a perfect example of "version 1.0" of embedded insurance. We also shared a Forrester forecast that "the embedded insurance market is expected to grow from $156.06 billion of gross written premiums in 2024 to more than $700 billion by 2029, a CAGR of 35%."

It now appears that its growth is even greater than expected. 

The embedded insurance market is now forecast to reach $1.1 trillion in global gross written premiums (GWP) by 2033, representing about 15% of the total GWP.

"Embedded insurance is becoming a growth engine for global financial services, a trajectory which reflects a customer- and technology-driven reshaping of how protection is bought, sold, and experienced," according to the latest Open and Embedded Insurance Observatory Report.

The report says the opportunity does not belong to banks and fintechs alone. Competition from adjacent industries is intensifying. Regulatory attention is beginning to focus on these models, which will require flexibility. Legacy IT systems are still a limitation for many incumbents, while data privacy and trust remain mission-critical.

A continuously evolving segment is auto insurance, added at point-of-sale together with a car purchase or lease. Although not a new concept, real-time insurance quotes are new and ease of adding or switching easily fits alongside financing and other add-on offers — all right at the dealership before driving off the lot. Numerous and growing insurer/car brand alliances, whether with or without driving data sharing, have popped up throughout the automotive industry. Such household purchases are major life moments, with an opportunity to switch insurers, hence the constant attention.

Embedded auto insurance

Of the many categories of embedded insurance, auto insurance represents an ideal opportunity and the most effective and frictionless delivery model. Consumers seek simplicity and one-stop purchase experiences, and their loyalty to auto insurers is eroding quickly in the face of continuing premium increases. Auto insurance is now a commodity, and switching is more frequent than ever.

According to Polly's Q2 2025 Quarterly Embedded Auto Insurance Report, the connection between insurance engagement and dealership profitability grew even stronger. Dealers who introduced insurance quotes into the sales process saw an average 20% lift in finance and insurance (F&I) gross profit — an extra $313 per deal.

When customers went a step further and purchased a policy, the effect was even greater. Those deals delivered a 31% lift in F&I gross, or $501 more per transaction.

The takeaway is clear: Whether a customer simply views quotes or binds coverage, insurance engagement is one of the most reliable levers for increasing dealership profit. It creates trust, keeps deals moving forward, and consistently raises the ceiling on F&I performance.

Technology-enabling embedded insurance

Insurtechs and integrations are the primary enablers and drivers of embedded insurance. This partnership benefits both customers and businesses by offering convenience, new revenue streams, and personalized coverage options powered by technology.

Selected insurtech companies specialize in enabling embedded insurance solutions for various industries:

• Cover Genius: Designs embedded insurance platforms for large brands like eBay, offering diverse coverage from shipping protection to rental car insurance.
• Clearcover: Has an embedded insurance strategy that includes partnerships with companies like Experian to offer bindable quotes to consumers when they are shopping for auto insurance.
• Roamly: Offers software tools and a platform that allows non-traditional insurers and other businesses, like car dealerships and marketplaces, to embed insurance into their workflows using APIs.
• Extend: Focuses on modernizing warranties and protection plans for e-commerce retailers.
• Wakim: Provides white-label, usage-based liability coverage for the gig economy and equipment rental.
• Zego: Uses application programming interface (API) technology to offer flexible commercial insurance to platforms such as Uber and Deliveroo, providing "pay-as-you-go" coverage for drivers.
• Bolttech: Provides a platform to embed tailored insurance products directly into existing customer journeys, from car dealerships to fintech apps.
• Matic: Offers an embedded insurance platform for financial institutions, allowing partners to offer competitive auto insurance options at the point of sale, particularly through partnerships with mortgage lenders.
• Tint Embedded Insurance: Helps brands embed insurance directly into their platforms, aiming to increase conversion rates and profitability by making insurance a feature, not a standalone product.
• Openkoda: Provides an open-source framework for building and deploying custom insurance applications, including embedded forms for quoting and policy sign-ups, with a focus on speed and control.

Auto insurance focus

Polly enables embedded auto insurance by integrating its digital insurance marketplace into the car-buying process at dealerships, allowing customers to compare quotes from multiple insurance carriers and purchase coverage at the point of sale. This seamless integration uses technology to connect the dealership's existing software with the insurance marketplace, so customers can get instant quotes and choose the best policy without leaving the dealership or going through a separate, time-consuming process. 

Embedded auto insurance partnerships

Carvana and Root

Carvana and Root have a partnership where Carvana sells auto insurance, underwritten by Root, to its customers during the online car purchase process. Customers can get an insurance quote and bind a policy from Root directly through the Carvana checkout, streamlining the process of getting their new car covered. While Carvana is the seller, the actual insurance policy is with Root Insurance.

Stellantis and bolt

Stellantis has partnered with bolt, an insurtech company, to provide embedded auto insurance for its Chrysler, Dodge, Jeep, Ram, Fiat, and Alfa Romeo customers in North America. The partnership aims to simplify and personalize the insurance purchasing process by allowing customers to buy insurance directly through Stellantis brand websites and apps, with future plans for usage-based options using telematics data.

OEM role in embedded auto insurance

While auto manufacturers (OEMs) do not directly sell auto insurance at their dealerships, many major insurance companies partner with dealerships to offer insurance options on-site, and some financial services arms of OEMs offer insurance-related products.

OEMs like Tesla and Volvo are changing the game, making insurance part of the car ownership experience itself.

Insurance companies that partner with dealerships include Travelers, Zurich, and Ally, with some having a strong history in the auto industry. Dealerships often facilitate insurance by having agents or brokers available to help customers with insurance needs at the point of sale.

• Partnerships with insurance companies: Dealerships frequently partner with major insurance providers like Travelers, Zurich, and others to make insurance purchasing convenient for buyers.
• OEM financial services: The financial arms of some manufacturers, like Ally, have established insurance divisions specifically for the automotive sector, including dealerships.
• On-site agents: Dealerships often have insurance agents or brokers on-site to help customers who don't have current insurance or are unhappy with their existing provider.

Other noteworthy embedded models/partnerships

• Liberty Mutual partners with Jaguar Land Rover North America to provide tailored auto insurance solutions for Jaguar vehicle owners in the U.S. during the car buying process
• Tesla comes with built-in insurance features
• Toyota Auto Insurance is underwritten by Toggle, a digital and embedded insurance company that is part of Farmers Insurance
• INSHUR formed a partnership with ride-sharing service Uber in 2018 to embed insurance directly into Uber's platform, providing on-demand drivers with streamlined, personalized insurance coverage that adapts to driving schedules
• Turo, a peer-to-peer car-sharing platform, collaborates with Liberty Mutual to offer embedded insurance for its users
• Chubb just announced the debut of a new AI-powered optimization engine within Chubb Studio, the company's global technology platform for embedded insurance distribution partnerships. Sean Ringsted, chief digital business officer at Chubb, said the new tool lets digital distribution partners enhance engagement, improve conversion, and support financial resilience with relevant insurance protection. 

Looking ahead

Implementing embedded insurance distribution channels is not a trivial undertaking, and there will be several technical, regulatory, business, and cultural obstacles, so you need to get started.

Whether you are an insurer, insurtech, agent, broker, MGA, retailer, wholesaler, or anywhere else in the insurance ecosystem and supply chain, you must invest now in learning how your business can participate in the embedded economy of the future.

This week's newsletter is really just an excuse for me to share a cool story about sensors so tiny that they're being used to track the migration of hundreds of individual Monarch butterflies as they travel from Canada to winter in Mexico.

I've been banging the drum about the importance of ever-shrinking sensors since at least 2013, when Chunka Mui and I published "The New Killer Apps" and listed ubiquitous sensors as one of our six technology megatrends to exploit. I've been fascinated by Monarch butterflies since coming upon a traffic jam on a country road in Mexico in the '90s, stepping out of my car and realizing that the "leaves" on trees up the hill were actually millions of Monarch butterflies. So I just couldn't pass up this week's story of Monarchs being outfitted with sensors that include a solar panel, a battery, a radio, and an antenna--while weighing six-hundredths of a gram.

Oh, and there are plenty of implications for insurers, where ever cheaper, ever more powerful, ever smaller sensors are already enabling the move to a Predict & Prevent model and where, as the butterfly story shows, there is still loads of room for progress. 

An article in the New York Times says about 400 butterflies have been fitted with the sensors and tracked, via a phone app, as they made their way south. Some were tracked for as long as nine weeks as they headed south to the winter colonies where they and their ancestors were born. One was tracked as it blew out to sea from Cape May, NJ, to the Bahamas and then flew west to Florida. As you might imagine, only about one in four survives the arduous journey. 

Even at 60 milligrams, the sensors add 12-15% to a Monarch's body weight, and they aren't cheap; they cost $200 apiece. But Moore's Law has been taking care of size and cost issues for electronics for some 60 years now and let the inventors get the sensors to the point where they're practical. The inventors also took advantage of the billions of Bluetooth devices that are already out there: If a Monarch flew within 300 feet of a Bluetooth-enabled device, the device would pick up the butterfly's radio signal and share its location with the tracking app.

Moore's Law and the spread of "mesh" networks like the one Bluetooth allows the butterfly sensors to access will continue to benefit the Monarch trackers--and insurers that choose to take advantage.

Telematics in auto insurance shows what can happen as technology moves down the size and cost curves. When Progressive pioneered its Snapshot program in 2008, the company quickly gained market share, but success was limited by the fact that Progressive had to pay for dongles and that drivers would then have to figure out how to insert them under their dashboards. When motion sensors became cheap enough that they were routinely embedded in smartphones, Progressive rolled out an app that not only had almost zero marginal cost but that was super-convenient for drivers. Its market share soared from fourth among U.S. auto insurers in 2015 to second this year. Its combined ratio in 2024 was more than six percentage points below the industry average. 

While other uses in insurance haven't had the same sort of dramatic success, some are getting there and enabling the move to Predict & Prevent. 

Whisker Labs's Ting device, which plugs into a wall socket, has now demonstrated that it prevents so many home fires that more than 30 insurers are giving the device to customers for free. Water leak sensors keep shrinking in size and increasing in capability, to the point that some insurers are at least experimenting with giving them away to policyholders. Nauto's windshield cameras -- one pointed at the road, one at the driver, with AI monitoring and warning the driver of impending danger -- is reducing accidents by 60-70%-plus in truck fleets. Roost sells batteries for smoke detectors that contain sensors and communication capabilities so they can send an alert to your phone and let you know of a problem when you aren't home. Home security systems now let you just affix inexpensive sensors to windows and doors that can communicate wirelessly to you or a monitoring company, without all the wiring that used to be required.  

FitBit, Oura and other fitness trackers are riding the sensor cost/size curves to keep adding capabilities. My first FitBit, which I bought maybe 10 or 12 years ago, just tracked my heart rate and my time sleeping. My Oura ring now tells me about my heart rate, my heart rate variability (which I didn't even know was a thing until Oura told me about it), my blood oxygen level, body temperature and more. Separate devices can track blood sugar, blood pressure, etc., and many of those sensors will find their way into the devices we wear on our fingers or wrists, much as motion sensors and so many other capabilities have been absorbed into our smart phones. That's just how technology works: Everything gets cheaper and gets absorbed into a dominant platform.

Insurers will also be able to benefit from the sort of "mesh" approach that the Monarch butterfly trackers use. The basic idea is that a device doesn't need to communicate directly with its host. It can just "mesh" with another device, which can then connect with the host or can even just keep passing along information to other devices (in this case, using Bluetooth) before reaching one that can connect with the host. 

Bluetooth is available to insurers that want to collect a signal from a sensor in a home, in an office, in a factory, in a car, on a person, or whatever. Amazon also offers a mesh network called Sidewalk, based on Echo and Ring devices. If you have enough power to get a signal to one of the hundreds of millions of those devices, you can collect that information. There are surely other mesh networks available, too, if not on the Amazon or Bluetooth scale.

Cost and size will still be an issue for some potential uses of sensors by insurers, but today's issues won't be tomorrow's. Moore's Law will keep shrinking devices and slashing costs, so if you can see a plausible case for use of a sensor, you need to be thinking about what the capabilities and costs will be like a few years from now and, perhaps, start experimenting today.

The real issue is just one of creativity for the insurance industry: What information can we imagine gathering via sensor that will let us prevent or at least minimize a loss, so we can protect people and limit claims?

If we can track a single butterfly from New Jersey to the Bahamas to Florida, what can't we do?

Cheers,

Paul 

Guide | Beyond Legacy Tech: A Modernization Guide for the AI Era

The insurance industry is at a crossroads. While many carriers are exploring AI, few have achieved true transformation. Nearly two-thirds remain stuck in pilot projects, held back by outdated, siloed systems that fragment data and slow innovation.

In this new guide from Origami Risk, discover why modernization—not experimentation—is the foundation for AI success. Learn how modern, cloud-based SaaS platforms enable insurers to move faster, scale smarter, and compete in an era defined by intelligence.

Download the guide to uncover:

1. Why AI adoption has stalled, and how to break free from legacy drag
2. How modern, multi-tenant SaaS platforms accelerate AI deployment
3. A side-by-side look at build-versus-buy modernization paths
4. Tested frameworks to align technology, finance, and operations stakeholders
5. Strategies to turn modernization into a growth engine for underwriting, claims, and customer experience

AI is no longer a pet project—it’s the next stage of insurance evolution. But only those who modernize their core systems will harness its full potential.

Don’t let legacy tech hold you back.

Download the Guide Now  

Sponsored by: Origami Risk

The insurance industry is facing pressure from all sides. Customer expectations are rising, as they expect the same sort of nearly instant responses they get when shopping or viewing bank balances online--creating problems for carriers that still rely on manual, paper-driven workflows. Yet regulators are requiring fairness and transparency even as the pace quickens. And newcomers with modern tech stacks are capturing market share.

This is the reality of today's insurance industry. Research published in Frontiers in Artificial Intelligence shows that AI is already transforming underwriting, fraud detection, and claims management. At the same time, customer churn is accelerating due to yearly rising rates, claim severity, and cost increases.

The stakes for success could not be higher. The technology to achieve success already exists, and its adoption is accelerating. Forward-leaning carriers are already leveraging it, gaining efficiency and customer loyalty. If organizations choose not to act, they risk being left behind by both the industry and, most importantly, the policyholders.

Reimagining Insurance in the AI Age

AI brings with it the unbound potential to elevate the way insurers operate. At the core is the ability to extract valuable insights from years of unstructured data. Take underwriting. Traditionally, it has been a data-heavy process; however, when an underwriter is augmented with AI, they can make faster, more accurate risk assessments. This accelerated process is enabled in part by the insurer's expertise and AI's ability to analyze vast datasets and identify emerging trends and patterns that may have otherwise remained buried in their records.

Claims processing is another area that can experience an efficiency boost by leveraging AI. Automated systems powered by AI can analyze claims data more efficiently, speeding up decision-making and reducing the time it takes to settle claims. In an industry where customer experience is paramount, a quicker claims process is one of the keys to both maintaining and improving satisfaction and loyalty.

Some major insurance carriers who have adopted this approach include:

• Lemonade: Using its claims handling AI agent, aptly named AI Jim, Lemonade can resolve simple property claims in seconds or minutes. While there are still claims that will need human intervention, Lemonade makes funds available one to two days after claim approval.
• Allstate: The claims process is often complex and riddled with insurance jargon. To avoid these complexities, Allstate automated communications with AI to improve efficiency, customer experience, and bring empathy back to the industry.

Another financial impact of AI-enhanced systems is their ability to help identify fraud by flagging suspicious patterns and anomalies. This detection ability is critical in protecting insurers from hemorrhaging profits due to fraudulent losses.

Where to Unlock Business Value With AI

For many insurers, daily operations are dominated by routine. This means agents and adjusters spend valuable hours navigating paperwork across siloed and legacy systems, leaving less time for meaningful customer interactions. By embedding AI into core processes, carriers have an opportunity to shift their workforce's focus toward higher-value activities that directly affect satisfaction, loyalty, and retention.

To ensure that this integration is done correctly, carriers should look for areas where AI-driven solutions will provide real returns on investments, including:

• Repetitive tasks: Today, adjusters spend hours on data entry and form processing. AI can automate intake, document classification, and updates, freeing time for customer service.
• Real-time decision support: Adjusters must piece together information from multiple sources while customers wait. AI can surface policy details, claim history, and regulatory guidance instantly during conversations.
• Cross-system orchestration: Staff often toggle between claims platforms, CRMs, and document repositories. AI can connect these systems and present a unified view, speeding up responses.
• Complex pattern recognition: Fraud detection still depends on manual review of anomalies. AI can flag suspicious patterns early, guiding investigators to high-risk cases more efficiently.
• Where humans & AI can collaborate: Employees are stretched thin between admin work and customer care. By handling repetitive tasks, AI empowers adjusters to focus on empathy, trust-building, and problem-solving.

By shifting the balance from routine to meaningful work, AI enables insurers to improve both operational efficiency and customer loyalty.

Meeting Today's Expectations

Customer expectations have reached a breaking point. Policyholders demand instant support, yet too often encounter rigid scripts instead of real solutions. A 2025 study by J.D. Power found that 57% of customers are shopping for insurance year over year, a staggering jump from 49% in 2024.

It's not a complex equation: Insurers with superior customer experience see higher returns by unleashing human expertise for relationships, judgment, and empathy—not by eliminating jobs. To build on positive customer experiences, insurers should leverage AI to instantly handle claims while meeting rising standards for compliance, privacy, and fairness. The path forward is clear: innovation depends on strategic human-AI orchestration.

Artificial intelligence has entered a new era. It's no longer just a statistical predictor crunching historical data. It's now a creator, planner, and autonomous actor capable of generating content, making decisions, and executing multi-step tasks. This leap from traditional AI to generative and now agentic AI has fundamentally changed the risk landscape. These new AI systems therefore demand a rethink of how we measure, manage, and insure the risk.

Traditional insurance frameworks, predominantly built on backward-looking data and well-understood failure modes, are not suited for systems that learn, adapt, and change behavior in real time. As AI becomes more deeply woven into business, infrastructure, and daily life, the question is no longer if it will fail but how and who bears the cost when it does.

To unlock the full potential of AI safely and at scale, the insurance industry must innovate. This is not just about transferring financial risk, but also about creating market incentives for trustworthy AI adoption. Insurers and risk managers will need to deploy new tools to quantify, price, and monitor AI exposure, ensuring that innovation and safety evolve together. This is urgent, as many AI risks are sitting silently inside existing policies, often unpriced, unmanaged, and waiting to materialize. The systemic risk posed by this silent coverage represents a significant, largely unmodeled aggregation exposure for carriers and creates uncertainty for the insured.

In the sections that follow, we explore how the AI risk profile is evolving and why a new generation of assurance and insurance mechanisms will be critical to building confidence in the intelligent systems that will increasingly shape our world.

The Evolving AI Risk Profile

AI systems have gone through three major generations, each more capable and complex than the last. With every step, the risk profile has expanded.

1. Traditional AI: Early AI systems were essentially statistical predictors. They learned patterns from structured data to forecast outcomes -- for example, credit scores, demand forecasts, and spam detection. Their risks were relatively stable and easy to quantify, mostly limited to data quality problems or model misspecification.
2. Generative AI: Generative AI (e.g. large language or diffusion models) doesn't just analyze data; it creates content. This creative power comes with new risk: producing plausible but false outputs (hallucinations), reusing copyrighted material from training data, or shifting behavior as APIs or retrievers change over time. Because these systems are composable (built from multiple moving parts) and dynamic (updated frequently), they can change behavior without warning.
3. Agentic AI: The newest wave, agentic AI, adds autonomy, reasoning, and tool use. Autonomy brings systemic risk: small local errors can cascade across an entire chain of actions, a phenomenon known as compounding uncertainty. When such systems fail, tracing the root cause or conducting causation analysis becomes extremely difficult due to opaque failure modes and information asymmetry.

The critical challenge is that AI can now fail while doing exactly what it was designed to do. Unlike software bugs or cyberattacks, these failures emerge from within due to biased training data, drifting knowledge, or complex feedback loops. Managing such behavior requires continuous, evidence-based oversight rather than static, one-off testing.

From Checklists to Continuous Monitoring

For AI systems to be insurable or trusted in safety-critical domains, they must undergo rigorous, transparent, and repeatable AI risk management. That means moving from checklist validation to continuous monitoring, where systems are tested and challenged throughout their lifecycle. This risk management framework provides the necessary evidence and controls that underwriters will demand to price the exposure.

Best practice frameworks point to four foundations, which should be viewed as future underwriting criteria:

• Governance and Tiering: Treat the whole workflow from data pipelines to prompts and APIs as the governed unit. Tier systems not just by impact but also by autonomy (how much they act without human approval) and volatility (how often components change). Every modification should trigger a change-impact review.
• Design Standards: Start from intent: what is "failure" in business or operational terms? Translate that into measurable technical metrics, justify every heuristic (prompt templates, data filters, reward models), and document assumptions and known residual risks. Build guardrails and fallback plans from day one.
• Validation Uplift: Move beyond static benchmarks. Combine domain-grounded tests with adversarial evaluation and scenario stress-testing. Measure calibration and selective prediction; use red teaming to expose hidden vulnerabilities. Where LLMs are used as judges, demand statistical checks for bias and consistency.
• Monitoring: Deploy continuous monitoring across inputs, outputs, and dependencies. Track drift, fragility, and anomalous behavior. Establish clear service-level objectives for safety and accuracy. Keep humans in the loop for escalation and design rapid rollback and patching playbooks.

In this new landscape, model probe systems for blind spots, test procedural reliability, and pressure-test entire pipelines. The goal isn't just compliance, it's resilience: building AI systems that remain safe, and trustworthy even as they evolve. Experience in managing cyber risk means insurers can build on existing practices, but tools and methods will need to be adapted to AI systems.

The Case for AI Insurance: Turning Risk into Resilience

As AI systems become more autonomous and unpredictable, they test the limits of traditional insurance models. Losses caused by AI errors often don't fit neatly into existing policy lines like cyber, product liability, or professional indemnity, therefore creating coverage uncertainty. This often results in "silent coverage," which creates hidden liabilities, unpriced exposures, and uncertainty for both insurers and insured. This unreserved, unmodeled exposure threatens aggregation events and solvency for carriers.

From our perspective, it matters less whether AI risks eventually sit within existing policy lines, emerge as embedded features, or evolve into a new, standalone class of AI insurance. What matters is that AI risks are material and growing, creating significant exposure to portfolios and businesses alike. As such, they must be rigorously understood, quantified, and managed. Businesses adopting AI will need confidence that, when failures occur, clearly defined insurance coverage stands behind the technology if they decide to transfer the risk into the market.

To make AI risk insurable, the market will need innovative tools and pricing mechanisms that reflect how AI operates:

• Performance-Based Guarantees: Policies could trigger payouts if the AI underperforms (e.g., if its accuracy or reliability drops below a defined threshold). This mechanism could be structured as an endorsement on Product Liability or a custom Financial Loss policy.
• Usage-Based Insurance: Premiums can scale with AI activity (e.g., per API call, per decision), creating dynamic, real-time pricing that mirrors exposure levels.
• Premium Differentiation (Bonus–Malus): Safer systems should cost less to insure. Firms that can demonstrate robust governance, transparent validation, and effective monitoring would pay lower premiums. In contrast, opaque or unaudited systems would be priced prohibitively high or deemed uninsurable.

This market mechanism does something regulation alone cannot: it aligns financial incentives with technical rigor. Underwriters will demand strong assurance, continuous monitoring, and clear audit trails to minimize both frequency and severity. Post-incident protocols will help to contain financial losses. Like cyber, insurers and brokers will shape the standards for testing, validation, and operational oversight. By linking AI assurance to premium levels, insurance can become a catalyst for safer, more trustworthy AI adoption, rewarding those who invest in resilience and transparency while discouraging reckless deployment.

This article first appeared on Instech.

The recent VIU by HUB Personal Insurance Marketplace Report and Rate Guide shows how broader economic trends affect premiums. Notably, the findings demonstrate that standard home and auto rate slowdowns are linked to cooling inflation, while rising rates for homeowners in disaster-prone areas stem from the increased frequency and cost of natural disasters.

With that data in mind, let's break down three of the biggest takeaways from our report:

1. Consumer expectations are rising amid rate fluctuations

Consumer expectations for comprehensive, affordable coverage are rising amid continuing rate fluctuations. While rate hikes may be stabilizing, volatility persists. Tariff announcements earlier this year created short-term disruption, but pricing has begun to level out; auto insurance premiums are moderating slightly, with the average increase closer to 10%.

Not surprisingly, on the property side, homeowners in catastrophe-prone areas still face steep increases. Regions at risk of wildfires, hurricanes, hail and convective storms will likely continue to see double-digit rate growth.

Flood policy counts are also rising as both public and private coverage evolves. As risks expand beyond traditional flood zones, pricing is increasingly tied to localized data.

All these factors have contributed to consumers feeling frustrated not only by rising costs but also by the complexity of an evolving insurance landscape. Insurance is no longer just an add-on to a home or car purchase – its cost makes it a major financial decision. This frustration is driving greater demand for clarity on coverage and costs, supported by neutral, expert guidance.

2. Embedded insurance shows customers that businesses care

Because insurance now occupies a larger share of consumer budgets, it's further affecting consumers' ability or willingness to make discretionary purchases. As a result, business leaders are asking: How can we help customers easily secure adequate, cost-effective coverage they feel good about?

The answer: enable customers to access insurance options through a licensed digital brokerage, either at or after point of sale, by embedding that brokerage's platform and expertise into a brand's sales process. At VIU by HUB, we call this brokerage as a service (BraaS). By partnering with a licensed brokerage, businesses can offer their customers multi-carrier solutions, paired with expert guidance, as part of the customer buying journey.

Think about it: when someone buys a car or applies for a mortgage, they're excited about their new car or home - insurance isn't top of mind. They're navigating a life event, and when it comes time to find insurance coverage, they likely need help. Embedding insurance options and expert advice before, during or after that purchase process is a convenient follow-through solution. For example, we recently worked with a top global automaker to integrate a digital insurance brokerage experience into its customer journey, giving customers a fast, trusted way to compare rates and receive licensed guidance across auto, home, motorcycle, renters and more.

The BraaS model places insurance within trusted shopping experiences and supplements it with live advisors, easy-to-understand choices and seamless operations. This doesn't just reduce confusion. It elevates customer satisfaction, increases revenue and brings long-term value to businesses seeking loyalty and repeat transactions.

3. The blend of human insight and AI efficiency benefits everyone

Artificial intelligence is evolving quickly and reshaping nearly every industry. Insurance brokerages are exploring how AI deepens understanding of customer needs to improve service, without sacrificing the critical element of human dialogue. We believe that, in the near-term, AI is most valuable when it enhances rather than replaces the human experience. For example, AI can be used to accelerate service by flagging life changes or analyzing documentation. It can also be used to give consumers more options and accessibility, such as after-hours service. But the role of empathy, judgment and trust cannot yet be replicated by algorithms. The future isn't human vs. AI – it's humans and AI. Our interactions use technology to support and enhance the human connection where it makes sense and in a way that consumers prefer.

What Comes Next

There's good news: price stabilization is beginning to take hold across some insurance sectors. Carriers are re-engaging in disaster-prone markets, even as rising claims costs, weather-related losses and increased repair costs remain real challenges.

The biggest shifts are consumer-driven. The insurance experience of tomorrow will be defined not by carriers' direct efforts, but by businesses meeting consumer expectations for convenience, clarity, compassion and capability. Embedded omnichannel brokerages are a powerful way to better serve those needs, enabling customers to access trusted insurance solutions as part of making the biggest purchases of their lives.

To better understand how insurers are addressing climate-related changes, the National Association of Insurance Commissioners (NAIC) requires insurers to file a Climate Risk Disclosure Survey that provides a discussion of how companies are addressing these risks and opportunities and integrating them into their governance structures, strategies and risk management.

We have reviewed many of these surveys. What is quite clear, albeit not surprising, is that insurers recognize that they face increased risks from chronic and long-term changes in climatic patterns but, importantly, they are well organized to deal with continuing and impending threats.

What is also clear from the disclosure, and perhaps less appreciated, is that insurers also foresee transformative opportunities. Specifically, these opportunities are expected to come from policies with risk control and loss prevention services. These policies help clients mitigate and build resilience to physical and climate risks. They also see underwriting opportunities in evolving and emerging technologies and industries.

Since insurers are investors as well as underwriters, they also see opportunities in allocating capital toward the energy transition and decarbonization efforts that occur in response to climate change.

The risks are well known but can be managed

Insurers are exposed to a wide array of physical and transitional risks stemming from climate change.

The physical risks arise from the increased frequency and severity of extreme weather events. These events, in combination with population growth and various socioeconomic factors, are likely to keep payouts climbing.

In addition to physical risks, insurers are faced with potential governmental responses to climate change that create conflicting policies across jurisdictions. This could lead to restrictions on insurers' ability to manage exposures and mandated coverages. There could also be higher compliance expenses, and costs for managing additional regulatory standards, especially those that require more disclosures.

Together these risks cannot be downplayed because they can have significant financial implications for insurers. However, the risks are well known, and managements have the right strategies and tools to deal with the issues.

But insurers also see underwriting and investment opportunities. They are expected to come (1) from policies with risk control and loss prevention services that help clients mitigate losses and build resilience, and (2) from coverages for emerging technologies and industries. Since insurers are also investors, they see opportunities in allocating capital toward energy transition and decarbonization efforts.

Mitigation and resilience

With higher climate-related losses in the future, mitigation will be critical to maintaining coverage availability and affordability. To do that the insurance industry will evolve from one that simply pays claims to one that has a critical role in helping policyholders reduce losses.

Hence, the key opportunity will come from designing policies with financial incentives to change behavior. This will be done not just for individuals and corporations, but also at the community level. Some resilient home incentives we expect to see expanded in the future are fire-resistant improvements, and elevated buildings in flood zones, among others.

In addition to offering products to reduce losses, insurers also see opportunities in designing coverages to enhance the ability to recover and adapt after events occur. Thus, insurers foresee the continued development of parametric insurance tied to climate indices (e.g., rainfall, temperature, and wind speed) that enables rapid payouts post events.

In addition to underwriting products, insurers see opportunities in offering comprehensive risk control and loss prevention services. These services include evaluations, technical information, consulting solutions, and educational resources to help clients reduce exposure to physical and climate risks.

Coverage of the latest technology

Insurers (as well as many others) expect that in response to climate changes there will be a gradual transition to clean energy technologies, infrastructure, and processes which will require insurance coverage.

These are some examples of what insurers note in their surveys:

• Renewable Energy Insurance: Coverage of onshore and offshore wind farms, solar farms, green hydrogen facilities, battery storage, hydroelectric plants, and energy conversion risks.
• Climate Technology Insurance: Coverage for climate technology developers, EV charging stations, and suppliers of solar panels and photovoltaic inverter solutions.
• Green Building & Construction Insurance: Product tailored for LEED®-certified construction, green upgrades in buildings, and construction projects focused on climate patterns like flood control, waterproofing, and fire safety.
• Electric Vehicle (EV) Insurance: Developing products and services to meet EV owners' needs, including specific EV policies, roadside charging coverage, and discounts for hybrid/electric vehicles.

On the investment side, insurers see climate change as an opportunity to generate attractive, risk-adjusted returns by deploying capital toward the global transition to a low-carbon economy, supporting emerging climate technologies, investing in green and municipal bonds, and enhancing community and infrastructure resilience.

Insurers anticipate that opportunities will continue to arise related to innovative technologies and solutions across a wide range of asset types. Among others, this includes support for climate change infrastructure, clean transportation, green buildings, pollution prevention, and sustainable water and wastewater management.

Conclusion

There is a natural tendency to view climate change negatively for insurers. But the world is adapting, albeit at a sometimes inconsistent pace, and the insurance industry has the opportunity to take a leadership role in this transition.

The bottom line is that insurance is a risk transfer business. Greater risks can lead to higher growth and enhanced returns if properly managed.