Now that Elon Musk has finally begun a robotaxi service, after nearly a decade of hype, fans are declaring that we've entered a whole new world that will, among many other things, mean the phaseout of personal auto insurance. 

The stock market seems to agree that what one analyst calls the "golden age of Tesla" is here: It carries a market cap of $1.09 trillion, and analysts say some 75% of that valuation stems from projections about the company's driverless technology. 

I'm unconvinced, including for a reason that has been ignored in all the coverage I've seen. 

I'll explain. 

Let's start with the piece I think has been overlooked: the operational complexity of running a network of what Musk has said will be millions of Teslas owned by individuals who have made them available to function as robotaxis. 

Even if you assume that Tesla's autonomous driving software works perfectly (which I'm not at all prepared to do), ponder for a minute all the work that has to go into managing a network of millions of cars that you don't own and have to essentially borrow from their owners. 

I spent several months doing that sort of pondering with two colleagues as part of a consulting project in 2017 for a major company that was considering a big move into AVs, and potential problems popped up all over the place. 

If a car needs to be recharged while in service, where does it go? Who plugs in the charger? How do you position cars so they can get to those hailing them as quickly as possible? How does rush hour complicate that positioning? How do you know when a kid covered in sand from a trip to the beach has shed in the car, or when a couple has sex in the back seat? Who cleans the car? What if it's used in a drug deal or other crime? How do you keep a group from carjacking the AV by having someone stand in front of it and behind it, knowing the car won't run them over? And on and on and on.

And those were just the problems facing a company that would have owned all its robotaxis. What Musk is promising is far more complicated.

What if I've declared my car available as a robotaxi for a stretch but want it back? What if I don't maintain my car as well as I should? How does Tesla enforce standards? Who is responsible for the depreciation on my car based on the miles spent to position it for ride hailers? How does Tesla deal with the fact that most rides are hailed during the same times of the day when owners are most apt to use them?

Basically, Tesla will have to build the equivalent of an air-traffic control system but on a far bigger scale. Musk is talking about coordinating tens of millions of rides per day, vs. 45,000 plane flights a day in the U.S. Airplanes travel point to point at assigned times, while Teslas will have to be able to go anywhere at any time. And automatic pilot software on airlines doesn't have to worry about pedestrians and bicyclists. 

That system can be built, but it won't be easy and will take years to develop. 

That timeline, alone, argues for dismissing the hyperbole about imminent disruption to personal auto insurers.

There's more, too. Tesla is years behind the competition. While Musk has long pointed to the inadequacies of competitors' capabilities, the Tesla rollout puts it about where Google's Waymo was in 2017. If you want to be charitable, you could say Tesla is where Waymo was as recently as 2020. 

Tesla has about 10 robotaxis that have been operating in the wild since Sunday, while Waymo has more than 1,500 and has been offering autonomous rides for years — Waymo operates about 250,000 paid rides per week. Waymo's rides are fully autonomous, while Tesla has a monitor sitting in the passenger seat. The informed speculation is that Tesla also has someone remotely monitoring each car, with the ability to intervene if it makes a mistake; Tesla hasn't commented, as far as I can tell. Waymo operates in large areas of many cities, while Tesla is limited to a small section of Austin, Texas, away from downtown and other complexities (even though Musk has long said a car can't be considered autonomous if it's limited to a "geofenced" area that has been carefully mapped).

As I've written previously, I believe Tesla also faces an insurmountable technology problem. Musk took the cheap route on sensors, relying only on cameras, while Waymo and other competitors also use lidar, radar and high-definition mapping. 

Musk fans argue that he has a massive data advantage because he has so many cameras on the road capturing data and has been running what is essentially a huge pilot for years, based on drivers who used early versions of his autonomous software. But early results haven't exactly been promising. Tesla vehicles being operated by that software have been involved in quite a number of accidents, including fatal ones, and Tesla's defense has been that it told drivers they couldn't trust the software. 

Videos from the robotaxi rollout show a Tesla stopping abruptly twice for no apparent reason, once in the middle of an intersection. (Apparently, the robotaxi saw police cars in a parking lot adjacent to the roadway.) Other videos shared by riders showed robotaxis speeding (though moderately) and, in one case, getting confused at an intersection and driving into a lane for oncoming traffic. 

That's just in the past two days, with only 10 cars on the road, operating in a tiny, uncomplicated, well-mapped area between 6 a.m. and midnight. And those sharing the problems are hardly critics; they were among the big fans selected by Tesla for early rides.

I'm not saying the robotaxi launch was a disaster. It wasn't. As Reilly Brennan, a prominent analyst in this space, says, "This wasn't the unsupervised dream realized, but if it wasn't Tesla I think people would be saying this was a solid mini launch."

Some go much further, especially on Wall Street, as this article in Quartz details. (If the surname in the byline looks familiar, that's because my daughter wrote it.) Goldman Sachs went on at length about the impact on insurers, saying auto insurance costs would plunge by 50%.

But some are even more cautious than I am, as the Quartz article also details. And if you want to get the really negative view, read this piece in Forbes, which dismisses the Tesla robotaxi as "not ready."

I come down on the side of Amara's law, as I usually do. It observes that technologies tend to be overhyped in the short term but underhyped in the long term. I firmly believe in the long-term prospects for autonomous vehicles, which will, among many other things, shift auto insurance from individuals to the makers of the software and the operators of the vehicles. But I see no need to hyperventilate about Tesla's robotaxi mini launch, no matter what Wall Street says.

As Phil Koopman, an expert about AV safety, wrote: 

"This is an important first step for Tesla on the road to robotaxis. But as other companies have learned, this is the end of the beginning, and there is a very long road ahead to scale up to a viable product."

Cheers,

Paul 

The one-quarter mark of the 21st century offers us a chance to reflect on the past – assessing the technology that has transformed insurance, recognizing how our industry has changed in the digital age, and striving to understand what the rise of insurtech, AI, and automation have taught us.

It's also an opportunity to look forward, using the insights of the past to better understand where the industry is headed in the future.

Over the past decade, digital transformation has redefined nearly every facet of insurance, from policy underwriting and distribution to the way claims are processed and managed. This rapid digitalization has primed insurers to embrace deeper cross-industry collaboration, adopt smarter and more streamlined claims processes, and balance innovation with compliance and customer trust.

As insurers look to predict the state of their industry by 2030, they're now well equipped to ride the next wave of disruption – whatever it may be. Those that invest in intelligent automation, personalized engagement, and flexible operating models will be best positioned to thrive in a dynamic and data-driven marketplace.

AI: A New Operating Model

By leveraging AI's ability to automate tasks, personalize offerings, and streamline workflows, insurers now operate in a reality where underwriting is up to 36% more efficient, customer service teams are over 30% more productive, and claims are processed up to 50% faster. Consider that 70% of simple claims are now resolved in real time – a rate of service that might have seemed unimaginable merely a decade ago.

On the sales side, AI is helping carriers boost conversions and cut acquisition costs, while freeing agents and brokers from time-consuming admin so they can focus more on providing the human touch so many clients desire.

That's just the beginning. AI and machine learning are maturing rapidly, poised to become even more foundational to underwriting, pricing, fraud detection, and service. These tools can process large amounts of data, assess risk, and design products, allowing insurers to optimize workflows across the value chain, enable seamless claims processing, automate policy issuance, and reduce administrative overhead. Personal AI assistants are also gaining momentum, guiding customers through purchasing decisions, answering policy questions, and offering recommendations based on life events or behavioral data, all in real-time.

These technologies won't just improve efficiency: They'll reduce costs, improve accuracy, and allow human teams to focus on higher-value interactions.

Customer-Centricity and Personalized Offerings

By 2030, successful insurers will be able to anticipate customer needs and deliver frictionless, individualized, omnichannel experiences. Leading insurance carriers are already prioritizing customer-centric approaches, developing innovative operating models that fundamentally drive value for insurers while constantly improving the way they interact with policyholders.

When insurers incorporate AI into claims processes, they not only enhance efficiency but infuse greater empathy across the customer journey. AI-powered systems can now analyze tone and sentiment in real time – such as detecting distress in phone callers – allowing insurers to ensure more responsive and compassionate customer interactions. Additionally, by freeing human agents from menial tasks, AI allows them to spend more time serving customers with the care and attention they deserve.

Insurers will also continue using data to offer more tailored policies. Consider the hyper-personalized underwriting possibilities of auto insurance based on driving scores. A 2024 survey from CMT, for example, found that 92% of respondents either agreed or strongly agreed with the statement that "Every driver in the U.S. should pay insurance based on how safely they drive."

The result isn't just greater customer satisfaction. It amounts to deeper, more profitable relationships across a lifetime of engagement.

Unlocking Speed and Resilience

Data-driven decision-making, supported by cloud-native infrastructure and AI, are allowing insurers to reduce the process of testing and launching products from months to mere weeks. This level of automation will streamline service, reduce cycle times, and ensure dynamic compliance with evolving regulatory standards.

It can also enhance workforce capabilities, re-skilling employees to work alongside AI tools and take on more consultative roles. A dual investment in both technology and the people who know how to use it will be key to fostering resilience, innovation, and long-term growth.

Insurance will also continue to be deeply interwoven with adjacent sectors, from banking and healthcare to energy and transportation. By integrating and partnering with insurtechs, digital platforms, mobility providers, and health services to expand value beyond the policy itself, carriers will deepen their ecosystem partnerships and expand what they can offer to customers. As enablers of long-term resilience against risks of any kind, insurers can reinforce trust and stability in an era of seemingly endless disruption.

Ensuring a Safer Future

Incremental adjustments won't be enough to keep carriers competitive.

The winners will be those that embrace change not as a threat, but as an opportunity to redefine their role – from reactive risk managers to proactive partners, dedicated to adopting whatever technologies and strategies are necessary to improve the lives of their customers.

In January 2025, fires in Los Angeles killed at least 29 people and destroyed over 18,000 homes and buildings, marking one of California's worst disasters.

Insurance offers one mechanism to support individuals who have suffered catastrophic losses, but insurance companies are now more cautious than ever when covering wildfires and other weather-related risks. Last year, insurers worldwide paid out more than $140 billion in claims relating to natural catastrophes, the fifth consecutive year with losses exceeding $100 billion.

Major natural disasters that cause substantial insurance claims, including storms, wildfire and flooding, are anticipated to become more severe with climate change.

But even for those perils for which recent spikes in payouts have been down to factors such as economic inflation and population growth, climate change still provides an unwelcome boost to risk and, therefore, premiums.

Typically, insurers used past claims to predict future losses from the same perils. So long as there had been no major unexpected disasters or big shifts in risk or exposure in a specific area, insurers could be confident that the premiums paid by the many would be enough to finance the claims of the few.

But in 1992, destruction from Hurricane Andrew in the Gulf of Mexico exposed the fragility of that approach by causing insured losses three times higher than expected by industry insiders in Florida alone. Insurers switched to sophisticated catastrophe models — tools that combine the physics of specific natural hazards with details about building construction and insurance information — to estimate possible financial losses. And in the past few years, as the imprint of global warming on natural hazards has become more obvious, the insurance industry has been recruiting climate and Earth scientists to reduce the likelihood of being taken by surprise.

Today, insurers have more-realistic views of their customers' exposure to weather- and climate-related risks and the scale of potential claims. Inside the limits set by government regulators, insurers decide how much risk they can tolerate across their portfolio, raise premiums for owners of more-exposed homes and purchase reinsurance to prepare for losses larger than they could normally afford.

Bankrupt insurers can't pay claims. Policyholders therefore benefit from risks being estimated correctly so losses can be paid by charged premiums. But insurers also use the latest catastrophe modeling and climate science to justify higher premiums, which are fast becoming unaffordable. Too many people are forced to choose between paying more for the same insurance, accepting lesser coverage to keep premiums manageable or letting their insurance lapse.

Continuing to ratchet up insurance premiums to keep up with mounting losses from hurricanes, wildfires and other perils might make financial sense — but it is also indicative of a growing crisis facing the industry. In many countries, including the U.K. and the U.S., the average cost of home insurance is more than twice what it was a generation ago. Yet, paying higher premiums doesn't make homeowners any more prepared for disaster. And despite charging higher prices, many insurers are still losing money through home insurance because they are paying out record-setting claims relating to natural catastrophes.

When insurers can no longer afford payouts to high-risk properties in a region, or even entire jurisdictions, they often withdraw coverage. In doing so, they make individuals more vulnerable, less able to recover from a disaster.

And they also create a diminished market for insurance products and higher geographical concentrations of risk. This upward spiral needs to be reversed. Insurance has typically served to transfer the financial costs incurred by disasters away from homeowners, not reduce risks of them happening. Now, approaches to push down both risks and costs are needed.

U.K.-government-backed Flood Re has been designed to make flood insurance more affordable for high-risk areas, with some insurers offering discounts on insurance premiums for homes with flood gates in flood-prone areas. Meanwhile in the U.S., Strengthen Alabama Homes pays people to stormproof their homes and has been shown to lower insurance premiums, and some insurers offer discounts on insurance premiums for homes with impact-resistant roofs. A number of states in the U.S. are also considering legislation that would require insurers to tell their customers how they can reduce weather-related risks to their properties and offer discounts for individual-, community- or state-level mitigation efforts.

All of these actions are helpful. Yet they still treat the symptom, not the disease. Adaptation without mitigation is not enough. Ultimately, we need to reach net zero, to prevent any further increases in global temperature and return risks of catastrophes to a lower level.

Falling short of that, many individuals and communities in the U.K. and the U.S. and worldwide might soon be priced out of home insurance and therefore financial protection against the consequences of natural disasters, leaving them unable to recover.

For many of us working in the property & casualty (P&C) insurance world, the very ground beneath our feet feels like it's shifting. Here in Canada, we've seen it firsthand: the terrifying roar of wildfires sweeping through communities like those in Fort McMurray, the relentless deluge of atmospheric rivers causing historic flooding in British Columbia, or the icy grip of eastern Canadian winter storms that cripple infrastructure. 

These aren't just isolated incidents any more; they're increasingly common and often more intense. And if you look beyond our borders, the story echoes globally – from super-typhoons devastating coastal cities in Asia to prolonged droughts turning landscapes into tinderboxes in Europe. These aren't mere headlines; they're direct, escalating challenges to the very promise of protection we make to our clients.

Catastrophe modeling has long been our steadfast companion, our indispensable compass in this turbulent environment. It's the science that helps us quantify the seemingly unquantifiable, to make sense of the immense, unpredictable forces of nature so we can price risk fairly and manage our portfolios responsibly.

But let's be honest: Even with our most sophisticated models, we've always been running a sprint against time, trying to extract insights from an ever-growing ocean of data. How do you keep pace when the climate itself seems to be "innovating" faster than ever? How do you make strategic decisions when crucial information is scattered across countless unstructured sources – every tweet from a storm-chaser, every drone image of a damaged rooftop, every local news report, every scientific paper on permafrost melt? Trying to sift through all that manually is like trying to catch water with a sieve.

This is where the story truly gets exciting. Large language models (LLMs) aren't just another buzzword or a fleeting tech trend. They represent a groundbreaking, fundamental shift. These powerful AI tools promise to profoundly change how we, as P&C insurers in Canada and across the globe, gain foresight, operate with efficiency, and build true resilience in an increasingly volatile world.

Yesterday's Playbook Won't Win Tomorrow's Game

"Business as usual" is a dangerous illusion, especially when it comes to managing natural hazards. The climate's relentless evolution means that historical data alone is no longer a perfect predictor. Urbanization pushes more valuable assets into vulnerable zones, from Toronto's burgeoning high-rises in potential flood plains to sprawling suburban developments near wildfire-prone areas. And in our connected global economy, a localized event – like a hailstorm over the Alberta prairies or an earthquake in the Pacific Northwest – can have immediate, cascading economic repercussions far beyond its initial footprint.

Our traditional cat models are incredibly powerful, providing precise probabilistic assessments from the structured data they ingest. But their "blind spot" has always been the sheer volume of unstructured, real-time information. Imagine a prairie hailstorm: the frantic social media updates from affected towns, the rapid updates from emergency services, the nuanced observations in a local building inspector's report. Or an Atlantic hurricane brewing: the subtle shifts in sentiment on local news channels, the firsthand accounts of coastal erosion. This constant torrent of informal yet vital information often gets missed or takes days of painstaking, manual effort to properly analyze and integrate. The real challenge for us now is to evolve beyond static risk assessments to dynamic, living insights that guide our decisions, minute by minute, whether we're managing a local Canadian community's exposure or a sprawling global portfolio.

Catastrophe Modeling: Ready for an Upgrade

Cat models aren't going anywhere. They will remain the analytical bedrock that allows us to manage immense risk. They elegantly break down complex natural perils into understandable components:

• Hazard: What's the storm doing? How hard is the ground shaking? What are the projected paths and intensities of wildfires across our vast Canadian forests?
• Exposure: What exactly is insured in this specific area? Every single building, every vehicle, every piece of infrastructure – from the gleaming high-rises in Toronto and Vancouver to the rural properties across the Prairies or the remote communities in the North.
• Vulnerability: How will these specific types of assets fare against those specific perils? What's the structural integrity of a building in Calgary against a severe hailstorm, or a coastal property in Nova Scotia against rising sea levels and storm surges?

By running countless simulations, these models provide us with the probabilities of loss. This crucial information informs everything from how we accurately price policies and manage our portfolio aggregates, to how much reinsurance we judiciously buy, and how we intelligently allocate our capital. They truly are the unsung heroes of our financial stability, both here in Canada and across our international operations.

Giving Our Cat Models a Voice and a Memory

Here's where the transformation gets truly exciting. LLMs, the same technology powering much of the generative AI revolution, are masters at understanding, interpreting, and generating human language. Their superpower is processing the unstructured data – the very information stream that has historically challenged our traditional analytical tools. Imagine the possibilities when we bring this extraordinary capability to our catastrophe modeling and the wider insurance ecosystem:

1. Unlocking the Deluge of Unstructured Data: From Noise to Insight

• Beyond the Numbers: Picture this: LLMs can instantly sift through mountains of news articles, scientific breakthroughs on the thawing permafrost in Canada's North, real-time social media chatter during a widespread power outage in Ontario, emergency dispatches from a flood-stricken town in Quebec, even subtle contextual notes attached to drone inspections of wildfire-damaged forests in Alberta or B.C. They pull out crucial, real-time nuggets about evolving dangers, localized damage, or hidden community vulnerabilities. No more missed signals, no more slogging through disparate reports.
• Policy Language, Instantly Understood: We all know how dense and regionally specific policy documents can be. LLMs can quickly read through vast libraries of policies, identify complex peril exclusions or specific coverage triggers – perhaps related to overland water coverage, wildfire smoke, or even specific seismic zone endorsements. This ensures our exposure data feeding into models is precise and accurate, minimizing ambiguity.
• Adding Richness to Properties: Imagine automatically enriching property data with nuanced details like "a heritage brick house, built in the 1920s, with a newly reinforced basement, surrounded by mature trees in a high-wind zone" – all extracted from casual notes, historical records, or even public property descriptions. This adds crucial layers to our vulnerability assessments within the cat models, whether for a home in Vancouver's urban interface or a sprawling farm in rural Saskatchewan.

2. Models That Learn and Adapt in Real-Time: Dynamic Foresight

• Dynamic Intelligence: LLMs can constantly scan the horizon for the latest scientific research on climate patterns affecting Canadian winters or global monsoon seasons, building code changes in coastal regions, or even subtle demographic shifts affecting urban exposure. This means our cat models can be updated almost continuously, reflecting the very latest understanding of risk, rather than waiting for scheduled, often less frequent, refreshes.
• "What If" Scenarios, on Demand: Actuaries and risk managers won't be limited to pre-packaged scenarios. They can simply ask in plain language: "What's the projected loss if a Category 4 hurricane makes landfall north of Halifax, combined with a 100-year flood in the surrounding areas, taking into account recent infrastructure upgrades and projected sea-level rise?" LLMs help translate these complex, nuanced questions into precise model inputs, allowing for tailored risk analyses for specific Canadian regions or global markets.

3. Clearer Conversations, Faster Decisions: Bridging the Understanding Gap

• Breaking Down the Jargon Barrier: Cat models produce incredibly complex, statistical outputs. LLMs can act as our expert interpreters, translating these highly technical results into clear, concise insights for everyone – from the CEO in the boardroom needing strategic context, to the underwriter assessing a new policy's risk, and the claims adjuster on the ground needing immediate, practical guidance. This vastly improves understanding and accelerates critical decision-making across the organization.
• Reports That Practically Write Themselves: Imagine automating the generation of post-event loss estimates, comprehensive portfolio analyses for both Canadian and international exposures, and even complex regulatory reports. LLMs can pull data from various sources and weave it into coherent, professional narratives, ensuring consistency and remarkable speed.
• Empathetic Communication, At Scale: In the chaotic aftermath of a catastrophe, LLMs can power highly empathetic and personalized communications to policyholders. Imagine instantly providing relevant instructions, real-time claim updates, and tailored support based on their specific policy and reported situation, whether they're affected by an ice storm in Quebec, a flood in the Prairies, or a distant earthquake.

4. Agile Claims Management Post-Event: Swift Response When It Matters Most

First Notice of Loss, Redefined: LLMs can instantly process unstructured inquiries from phone calls, chatbots, emails, and social media, extracting crucial claim details and automatically kicking off the claims process much faster. This is particularly vital in large-scale events that affect thousands across a broad geographic area.

• Instant Damage Triage: When combined with computer vision (analyzing drone footage or policyholder photos from a disaster zone), LLMs can provide immediate preliminary damage assessments, prioritizing and triaging claims for human adjusters, ensuring help gets to those who need it most, faster.
• Smarter Fraud Detection: By analyzing textual patterns in claims narratives, cross-referencing data, and spotting inconsistencies, LLMs can significantly bolster our defenses against fraudulent claims, protecting our integrity and resources across all markets.

5. Sharper Underwriting and Portfolio Strategy: Precision Risk-Taking

• Real-time Risk Pricing: Underwriters can leverage LLM-derived insights from real-time data to refine risk assessments and adjust pricing dynamically, ensuring our rates truly reflect evolving perils and exposures across different geographies, from Canada's unique risk zones to global territories.
• Optimized Reinsurance: With more granular, living risk insights, we can make smarter decisions about our reinsurance purchasing and capital allocation, strengthening our financial position against both Canadian-specific and global catastrophic events.

6. Navigating Regulations with Ease: Global Compliance, Local Insight

• Always Compliant: LLMs can continuously monitor regulatory updates across various Canadian provinces and diverse international jurisdictions, automatically flagging potential compliance gaps related to our cat model usage or data reporting.
• Effortless Reporting: Automating the heavy lifting of compiling data and narrative for complex regulatory filings, significantly reducing manual effort and potential for error, ensuring we meet all obligations efficiently.

Navigating This New Frontier Together

This isn't to say it's easy. Bringing LLMs into our world comes with real, tangible considerations:

• Data Integrity & Trust: We need absolute certainty that the vast amounts of data feeding these LLMs – often sensitive and proprietary – are accurate, secure, and used ethically. Robust data governance is paramount, ensuring compliance with Canadian privacy laws and international standards.
• Bias and Transparency: LLMs can inadvertently pick up biases from their training data. We must ensure model transparency and keep our expert "human-in-the-loop" to ensure fair, explainable, and equitable outcomes, adhering to the highest ethical standards.
• The Integration Puzzle: Seamlessly connecting LLMs with our existing cat models, core insurance systems, and diverse data sources will require thoughtful architectural design and skilled engineering. It's about building bridges, not just adding new components.
• Building New Skills: We'll need to invest in our people, developing new skills in data science, AI engineering, and even "prompt engineering" – the art of asking LLMs the right questions. This upskilling will be crucial for Canadian talent to lead not just at home but on the global stage.
• Evolving Regulations: As with any transformative technology, clear regulatory guidelines will need to evolve across jurisdictions – from Ottawa to Brussels, Washington D.C. to London – to ensure responsible adoption across the industry.

The path forward is about intelligent experimentation and collaboration. It's about launching strategic pilot programs, fostering true collaboration between our cat modelers, data scientists, IT teams, and business leaders. And crucially, it's about partnering with technology leaders who genuinely understand both the intricate world of insurance and the nuances of AI.

Conclusion: Amplifying Our Foresight, Fortifying Our Promise

The convergence of catastrophe modeling and large language models marks a pivotal moment for the P&C insurance industry. 

LLMs are not here to replace the profound expertise of our cat modelers, or the critical human judgment that guides our underwriters and claims professionals. Instead, they are here to be powerful augmentations – tools that amplify our human capabilities, allowing us to see further, respond faster, and operate with unprecedented precision.

By strategically embracing this LLM revolution, we can move beyond merely reacting to risk to truly anticipating it. We can gain deeper, more dynamic insights into peril, exposure, and vulnerability, leading to more accurate pricing, faster claims processing, and more resilient capital management. 

In an increasingly uncertain world, the P&C insurers – particularly those navigating Canada's unique and evolving risk landscape and contributing to the global insurance market – that boldly and thoughtfully adopt this new paradigm will not only strengthen their own foundations but also provide greater stability, security, and peace of mind to their policyholders. 

We will solidify our role as essential pillars of societal resilience. The time to explore this transformative frontier is now – with authenticity, courage, and a clear vision for a more secure future.

Data-led insurance is a necessity, and despite the millions of dollars spent on transformation projects, it is something the sector has yet to make happen. I know what you're thinking, "Sheesh, why doesn't this guy know that insurance already has massive data scale?"

I get it. I really do. But being data heavy isn't the same as being data rich. Certainly, the adage is true: Data is the new oil. However, the issue isn't the volume of data at insurers' fingertips. The challenge is extracting it, refining it and using it operationally in a way that builds massive value in the new economy.

It's this disconnect that I believe has led to a stall zone in insurance, especially in the face of the AI onslaught. It's something that must be overcome to achieve the data-led transformations that are demanded by customers and create the engines to drive the sustainability of the sector.

Data Volume Is Only One Facet of Value

Data is the lifeblood of the actuarial muscle that makes insurance possible. When calculating weather risk, a typical catastrophe model might attempt to use 150 years of meteorological data. That represents approximately 30 terabytes, over 100 million locations, while simulating approximately 100,000 atmospheric and hydraulic scenarios. This, in turn, yields 200 billion records to feed the financial models.

These types of large-scale, elastic computing, on-demand scenarios are where the cloud excels. It's also an example of where we predominantly think about data in insurance.

Collate, analyze, extract insight, build or update the model and then apply the outcomes mostly through underwriting and pricing.

The work is vital but relatively narrow, and massively constraining on an insurer's ability to truly shape propositions.

Data Velocity Is More Vital than Ever

According to IBM, 90% of the world's data has been generated and gathered in the last two years -- a result of the acceleration and velocity of digital services in a commercial world that's recognizing us more as individuals and shaping life experiences to suit specific interests and activities. This trend is set to explode, especially with AI.

Big data has the ability to change the way we see people, which clearly affects risk pricing. But it should also change how we operationalize and use data to create better relationships, to build risk mitigation, to orchestrate claims ecosystems and more. 

It can help us to create experiences that help us maintain our cars and reduce risks, such as brake pad wear. It can be applied to usage-based driving capability, which optimizes the way we drive through tips, advice, and education.

Big data can be applied to commercial building insurance that's connected to a building's management system -- continually feeding in live "risk" data, playing it back to owners, and offering options to adjust the risk profile. Or take flood risk: A Google search combined with insights from Earth Knowledge could trigger services like Flood Flash or Flood Re, providing timely support before disaster strikes.

It can also extend to the claims process, where customers are offered personalized repair options that put them in control of their experience and allow them to choose what's most convenient for them.

The examples are endless. But there's a problem - legacy and modern legacy technology have created a fracture. On one side of the chasm, you have data for analytics, and on the other are operating data models that treat data as a perishable asset, constantly mine it for insight and act on that insight, increasingly close to real time. Insurance can do the former but not the latter. IT silos in insurance are killing mass data models and intelligence.

The New Data and AI Operating Model

Nearly 80% of enterprise data is unstructured. It can be found in the form of emails, text documents, research, legal reports, voice recordings, videos, social media posts and more. For insurers looking for answers, this unstructured data is a goldmine. However, it's far more difficult to analyze than structured data.

Fortunately, evolving technologies, such as natural language processing, can enable insurers to unlock the value. Natural language processing, a component of artificial intelligence (AI) that can understand human language as it is spoken, has evolved to a point where it can be used to understand a user's questions (text or speech) and mine insights from vast amounts of unstructured data.

However, the tech stack and operating model needsto transform to make this and any meaningful use of AI a reality. This new DNA for insurance makes insurers look more like e-commerce businesses in the way they operate and in the way they conceive and build products and experiences.

Here's the DNA:

• Built around the customer and not a policy
• Data fluid and based on event streaming
• MACH based (and that does not mean cloud hosted)
• Capable of high levels of adaptivity at speed
• The ability to operate any line of business in any geography

Operationalizing data requires us to think differently. Insurers can use large volumes of data to improve pricing strategies, streamline the claims process, and make better underwriting decisions. And yet they typically struggle to make any changes to product, services and experiences beyond this.

Make no mistake, insurance is a data product and a data-led service. It just keeps pretending it still produces documents called policies, when that concept is really defunct.

What all of us really buy is adaptive personalized coverage typically adjusted somewhat to our risk tolerances and bank balances. The problem is insurers make this super hard to achieve because they don't fundamentally address the underlying way they operate, and in turn how this allows them to operate around data.

This data mobility requires new core technology foundations for most insurers today -- foundations that shift their ability to drive new value through change, reducing the time and effort required to make change happen. We see that most EIS customers become capable of easily developing and adapting what are often called data-products, from operationalizing AI to digitizing personalized and more effective experiences. It's all under-pinned by operational data centered on a customer.

Data is a big part of insurance today, but it is an even bigger part of insurance tomorrow.

Why should all of us be concerned about solo aging? According to the U.S. Census Bureau, by 2034, there will be more people 65 years and older (77 million) than there will be under the age of 18 (76.5 million). One-quarter of baby boomers (born 1946-1964) did not have children, and about one-third of Americans aged 45-62 are currently single.

If someone has never married, has divorced, doesn't have children or loses a spouse or family support, there is a good chance that person will become a solo ager at some point in their life. A solo ager may not have the resources that people with families or close friends have, and because of this, they need to pay special attention to the challenges of aging.

These solo agers, or those who think they may be a solo ager, need to evaluate their own support network, understand how to avoid social isolation, be clear about financing their retirement (including a financial care plan), have control over healthcare decisions for themselves, and more. Not having a plan can mean going into financial instability or poverty, losing control over choices for your life and your health, and putting a solo ager in unnecessary risk. It can also mean fewer years of independent living as that person ages. With a plan that reflects a solo ager's medical, legal, financial and personal wishes, solo agers can live with more freedom and security.

Who is a "Solo Ager?"

The term "solo ager" refers to individuals, typically in their mid-50s or older, who are aging without the support of a spouse, adult children, close family members, or close friends. If they do have family and close friends, but they geographically don't live close, this can also make them a solo ager. This situation can arise from various circumstances, such as being widowed, divorced, never married, or having no children. Some solo agers may have previously benefited from strong family support systems but lost them due to life events like death, divorce, or estrangement. Despite these challenges, solo agers approach their future with optimism, often seeking community resources and planning ahead to meet their needs [1][2][4].

This demographic faces unique challenges related to social isolation and caregiving, highlighting the growing need for community-based support networks tailored to their needs[8].

Historically, when an aging parent or loved one needed assistance with healthcare and caregiving matters, their adult child(ren) or other younger family members were available to help. As the data makes clear, in the case of the current senior populations, there are fewer adult children to provide assistance. For those who did not have children, ensuring support as they age requires an extra layer of planning to make sure that supports are in place when needed and tat they have control over choices like aging at home or medical treatment preferences.

Challenges Solo Agers Face

Solo agers face unique challenges at each stage of aging. These include physical, emotional, financial, and logistical needs. Here is an overview of the key difficulties a solo ager may encounter and strategies to address them effectively:

1. Social Isolation and Loneliness

• Solo agers are more prone to loneliness and emotional isolation due to the lack of immediate family or close confidants [1][5][8].
• They may struggle to maintain social connections, particularly as they age and face reduced mobility or functional limitations [4][5].
• Many solo agers report feeling left out or isolated, with fewer opportunities for community engagement compared with others in their age group [2][3].
• Solo agers experience higher rates of depression and poor mental health compared with those with family support networks [3][5].
• The combination of loneliness and limited emotional support exacerbates these mental health challenges [5].

2. Health and Caregiving Concerns

• A significant worry among solo agers is losing independence, physical strength, or memory, with many lacking a caregiver to assist them during health crises [2][6][8].
• They are at higher risk for inadequate care or care that does not align with their wishes due to the absence of family or legal advocates [6][7].
• Chronic illnesses and falls are more common among solo agers, yet many do not have plans in place for medical decision-making, a medical alert system or caregiving support [6].

3. Financial Insecurity

• Solo agers often fear running out of money or being unable to afford in-home paid care as they age [2][6]. They often do not have a financial care plan.
• Managing finances independently can be challenging, especially without trusted individuals to assist with complex decisions like estate planning, long-term care arrangements [7] or basic bill paying, if they were in the hospital or in recovery.

4. Housing Challenges

• Most solo agers live alone in houses or apartments that may not be suitable as they age, yet few have made modifications or explored alternative housing options such as senior communities [2][4].
• The lack of planning for future living arrangements can lead to difficulties in maintaining independence or accessing necessary support services [2].
• Waiting lists for subsidized housing are becoming unrealistic, and with anticipated cutbacks in government funding this is going to become an even more serious issue.
• They may have a pet or pets and no plan in place if they are in the hospital or unable to care for them.

5. Legal and Decision-Making Gaps

• Many solo agers lack designated individuals (e.g., healthcare proxies or executors) to make critical legal, medical, or financial decisions on their behalf if needed [6][7].
• This gap leaves them vulnerable in emergencies and can complicate recovery or end-of-life planning [7].

6. Vulnerability to Scams

• Solo agers are increasingly concerned about falling victim to scams due to their perceived isolation and lack of trusted advisors [2].

To address these challenges, experts recommend planning in areas like healthcare, finances, housing options, security concerns, and social engagement while building strong peer networks for mutual support.

Preparation

The good news is aging solo challenges can be addressed with professional planning and strategies that align with personal preferences. It is possible to live a fulfilling and independent life, even into our 80s or 90s. Here are key approaches to making solo aging easier and more secure:

1. Acknowledge and Plan for Challenges

• The first step is accepting that aging alone requires taking charge of putting a plan in place, including health needs, finances, legal issues, and social connections. It also requires education about these issues, the range of choices available, and how they apply to your life.
• Legal and financial planning: Prepare essential documents such as wills/trusts, powers of attorney (both medical and financial), healthcare directives, and financial retirement and care plans to ensure your wishes are respected and legal. Work with an elder care attorney who is experienced and vetted. Don't download wills or other documents form online sites. If they are legally challenged, you will need someone to advocate for you.
• Plan for future care: Explore options like Continuing Care Retirement Communities (CCRCs), in-home care services, and long-term care insurance to ensure support when needed. While most people prefer to remain in their own homes, that may not always be possible or less costly. Understanding all your options is key to evaluating what is best for a solo ager and the plan that gets put in place.

2. Build a Support Network

• Cultivate meaningful relationships: The sad thing about aging is losing friends and relatives along the way. Isolation can lead to depression and accelerate dementia.
• Develop connections with new friends, neighbors, or community groups to reduce isolation and create a reliable support system.
• Engage in community activities: Join local clubs, volunteer organizations, or hobby groups to expand your social circle and maintain engagement with others. If mobility is an issue, there are online networks.
• Consider different types of senior living communities: These can provide companionship and resources tailored to solo agers. Many communities offer a great lifestyle and are far different from nursing homes you might have visited 30 years ago.

3. Stay Active and Healthy

• Physical health: Regular exercise and a balanced diet are essential for maintaining strength and well-being. Daily walks and weekly meal planning can support better aging.
• Mental health: Practice mindfulness, take up hobbies, or engage in activities that bring joy and peace. Be open to talking to your doctor or a licensed professional, if mental health support is needed.
• Daily structure: Establish routines to create purpose and reduce feelings of loneliness.

4. Foster a Sense of Purpose

• Volunteer or mentor: Contributing your time to causes you care about can provide more quality of life.
• Pursue hobbies: Activities like gardening, crafting, or writing can add meaning to your daily life.

5. Embrace Technology

• Use tools like video calls, social media, or online communities to stay connected with loved ones and access information or resources.

6. Seek Professional Support

• Consult geriatric care managers, counselors, or other professionals for personalized advice on navigating the complexities of solo aging.
• Therapy can help address feelings of loneliness or anxiety while providing strategies for emotional resilience.

By addressing the need for an aging well plan, solo agers can create a life, as they age, that can be healthier, more secure, and more fulfilling. It can also potentially mean aging better and more years of independence.

Resources

• https://www.SeniorFinancialLife.com

• https://navigatingsolo.com/resources

• https://thesoloager.com

• https://www.beaconpatientsolutions.com/solos

• https://theconversationproject.org/

• https://MotivityCare.com

Sources – Who is a "Solo Ager?"

[[1] What Is a Solo Ager & How Do You Market to Them? https://seniorlivingsmart.com/blog/what-is-a-solo-ager-how-do-you-market-to-them/1] 

[2] What is a Solo Ager? | Keiro https://www.keiro.org/features

[3] The Solo Ager™ | Healthy Aging. Together. https://thesoloager.com

[4] No Kids to Rely On? Seven Things Solo Agers Must Do Now https://www.kiplinger.com/retirement/things-solo-agers-must-do-now

[5] Solo Agers Facing the Future Need a Network of Friends - AARP https://www.aarp.org/caregiving/basics/info-2022/solo-agers.html

[6] How to Live Well While Aging Solo - Hebrew SeniorLife https://www.hebrewseniorlife.org/blog/how-live-well-while-aging-solo

[7] Aging Alone Together® | DOROT https://dorotusa.org/agingalonetogether

[8] Confronting the Challenges of Solo Aging - ASA Generations http://generations.asaging.org/confronting-challenges-solo-aging

Sources - Challenges

[1] Maneuvering The Unique Challenges of Solo Aging https://gnanow.org/blogs/maneuvering-he-unique-challenges-of-solo-aging.html

[2] Solo Agers Express Contentedness and Concern - AARP https://www.aarp.org/pri/topics/aging-experience/solo-agers-contentedness-concerns/

[3] Mather Institute report details unique risks for 'solo agers' https://www.mather.com/archives/21863

[4] The Concerns of Solo Aging - Elder At Home https://www.elderathome.com/the-concerns-of-solo-aging/

[5] The Risk for Loneliness and Major Depression among Solo Agers https://pmc.ncbi.nlm.nih.gov/articles/PMC10081956/

Sources - Preparation

[1] Aging Alone? How to Build Your Support System for Successful Solo ... https://thekensingtonwhiteplains.com/aging-alone-support-for-solo-aging/

[2] Navigating Solo Aging: Planning for the Future - Care.com https://www.care.com/c/solo-aging/

[3] 7 Tips To Overcome The Challenges Of Solo Aging https://www.moradaseniorliving.com/senior-living-blog/7-tips-to-overcome-the-challenges-of-solo-aging/

[4] Thriving in Solo Aging: Tips for Baby Boomers Living Alone https://rhythmshomecare.com/blog/thriving-in-solo-aging-tips-for-baby-boomers-living-alone/

It's hard to go a day without reading another news story about how the Trump administration's widespread tariff policies will affect life in America. But amid all that dialogue, shockingly little has been said about how the tariffs will affect homeowners' insurance.

Throughout his second term, President Trump has levied varying amounts of tariffs on imports from around the world. The most notable of these announcements came in early April, when the administration announced what it called "reciprocal" tariffs on all nations, which included a flat rate of 10%, along with higher rates for most of America's trading partners.

Since then, the president has lowered, removed or delayed the start for several of those taxes on imports, although many remain in place.

Meanwhile, home insurance rates rose by 40% cumulatively between 2019 and 2024. With tariffs now increasing rebuilding costs, disrupting global supply chains and potentially stoking inflation, there's a real risk that they could continue to climb throughout this year.

And while the future of those factors may seem unpredictable, insurance providers can still control several things, including how they communicate these changes to consumers. Below, we'll lay out what you need to know about the connection between tariffs and insurance rates, as well as how to manage and mitigate customer concerns.

The biggest concerns

Because the cost of home insurance is rooted in many predictive factors — that is, what could happen to a particular dwelling in the future — its relationship to tariffs is a bit more complicated than it would be for, say, the cost of eggs.

That said, there are two key factors worth watching above the rest. First is rebuilding costs, which naturally play a major role in determining rates.

Here, the repercussions are already being felt. A recent survey conducted by the National Association of Home Builders found that 60% of builders said their suppliers had already increased or announced coming increases in the cost of supplies.

As of mid-April, suppliers had increased prices by an average of 6.3%, which means a nearly $11,000 increase in the cost of a typical home.

If material costs increase, then rebuilding costs increase, which in turn means insurers have to charge higher rates to cover future repairs.

The other factor, which is heavily intertwined, is how this international trade turmoil will affect supply chains. While most of America's building materials are made domestically, the global supply chain is extremely complicated, meaning even a company that sources nearly all its materials in the U.S. could feel the effects.

Consider this: According to a 2023 estimate, 7% of all residential building materials are sourced abroad. That may not sound like a lot, but over a quarter of those materials come from China, which, despite new negotiations with the Trump administration in May, will still face significant taxes on the goods it sends into the U.S.

Chaos in the supply chain can also lead to delays for repairs and reconstruction, which adds even more uncertainty and, of course, more potential cost.

What customers need to know

The most critical thing for insurers to communicate is that these changes will not be felt overnight. The tariffs are complex, and the details surrounding them are constantly shifting — plus, it will take a while for their impact to trickle down to insurance costs.

Plus, even once providers can raise rates with clarity, they may not be able to act immediately. In many cases, insurers need regulatory approval to increase premiums, a process that can sometimes take years.

Here, providers have a tough balancing act: They must set expectations for the future without fearmongering and tamp down fears in the present without overpromising.

The impact of tariffs will not be felt evenly. Some states, home types and income levels will be disproportionately affected, simply due to the kinds of builders and materials used in each situation.

Places like Utah, Illinois, Arizona and Pennsylvania all saw premiums grow more than 40% between 2021 and 2024, while a small minority — roughly 5% of ZIP codes — didn't experience increases at all. It's a good reminder that stats can be deceiving and that each homeowner's situation will be entirely unique.

How homeowners can prepare

Ultimately, some of these price increases will be both financially straining and difficult to predict, which is all the more reason why providers should help their customers control what they can.

The best way to do this, of course, is to educate homeowners on how they can control their insurance costs elsewhere, such as by bundling policies, working to improve their credit scores and adding traditional rate-cutting features — like security systems and storm shutters — to their homes.

Homeowners can also work to keep their risk profile low. This may mean avoiding so-called attractive nuisance features, like swimming pools or trampolines, which encourage dangerous activities.

Lastly, providers can consider offering loyalty discounts for long-term policyholders. In times of turmoil, these benefits can reassure customers that their concerns are heard, and discourage them from looking elsewhere when rates are climbing across the board.

That's especially important given data from J.D. Power's latest home insurance report, which found that 37% of customers consider shopping elsewhere after experiencing a rate increase.

Ultimately, customers will care more about the bottom line than the reasons behind them, which is why transparency, empathy and careful communication are all important in times of uncertainty.

Despite years of progress in digitizing the front end of insurance claims, the back-end infrastructure that supports these payments remains outdated and fragmented.

Our latest research, based on insights from over 200 senior insurance professionals in the U.S. and U.K., uncovered a clear pattern: The financial infrastructure that supports claims fund management remains fragmented. This disconnect not only delays payments but also creates operational risks and undermines trust.

The numbers tell the story. Nearly 80% of respondents cited internal process complexity as a key barrier to faster payments. 66% reported struggling to access readily available funds, a challenge that climbs to 74% in the U.S., where decentralized funding structures and manual approval flows persist. Only 1% of insurers said collaboration between claims and finance teams is "highly effective," underscoring how siloed operations remain.

All these responses represent a strategic challenge for insurers striving to stay competitive in a fast-evolving market.

The hidden costs of fragmentation

At the heart of the issue is a lack of real-time financial coordination. Claims, finance, and treasury teams often operate in silos, using separate systems that don't talk to each other. This makes it nearly impossible to track the status of funds, forecast liquidity needs, or reconcile payments without time-consuming manual intervention.

For U.S. insurers, the stakes are especially high. Our research shows that U.S.-based treasury teams are more focused on governance and compliance (37%) than their U.K. counterparts (22%), a reflection of heightened regulatory scrutiny and complex operating environments. Despite this focus, many still struggle with fragmented systems that leave them exposed to delays, errors, and compliance risks.

External coordination adds another layer of complexity. 78% of insurers reported delays associated with third-party involvement, whether from brokers, TPAs, or banking partners. 

While these partners play a critical role in the claims ecosystem, the lack of seamless integration and data-sharing slows payments, introduces errors, increases risk exposure and contributes to inefficient liquidity management.

Toward a new model: Real-time financial orchestration

The good news is that the industry is beginning to move beyond patchwork solutions. Insurers are increasingly recognizing that speed, accuracy, and control aren't just about operational efficiency; they're fundamental to customer trust and financial resilience.

This is where real-time financial orchestration comes in. By creating unified financial infrastructure that connects claims, finance, and treasury teams—and extends to external partners—insurers can gain complete visibility into fund flows, automate disbursement processes, and manage liquidity with confidence.

Such infrastructure isn't just about faster payments. It's about enabling insurers to:

• Avoid overfunding and manual cash calls.
• Enhance regulatory readiness through transparent, auditable fund tracking.
• Strengthen resilience in the face of increasing market volatility and regulatory
• scrutiny.

Our research also revealed that early adopters are already exploring smarter fund segregation models, integrated payment platforms, and automation tools that streamline reconciliation and compliance. These innovations are laying the foundation for a claims ecosystem where financial coordination isn't an afterthought, but a strategic advantage.

What's at stake

Insurers can't afford to let back-end inefficiencies stymie them. Rising customer expectations, increased regulatory oversight, and competitive pressure are forcing the industry to reimagine how money moves. The insurers that take steps to modernize financial operations by investing in real-time coordination, intelligent fund management, and integrated platforms will be the ones best positioned to lead.

This isn't just about paying claims faster. It's about creating an ecosystem where every participant, from insurers and TPAs to brokers and banks, operates from a shared source of truth, reducing errors and delays. It's about ensuring that liquidity is always available where and when it's needed, so insurers can deliver on their promises.

The call to action

The future of claims finance is about bold investments in real-time, data-driven infrastructure that connects internal teams and external partners alike. It's about making claims payments a driver of operational excellence and customer trust, not a back-office bottleneck.

As the landscape continues to evolve, insurers must ask themselves: Are we ready to break down the barriers that slow payments and erode trust? If not now, when?

The commercial property and casualty (P&C) insurance industry stands at a pivotal moment that mirrors the dawn of the internet era. Just as companies that dismissed the internet in the mid-1990s found themselves scrambling to catch up years later, today's insurers face a similar inflection point with artificial intelligence. The message is clear: AI adoption in claims processing is no longer optional, it's inevitable.

For C-level executives in P&C organizations, the question has shifted from, "Should we implement AI?" to, "How quickly can we integrate AI effectively?" This urgency isn't driven by hype but by compelling market realities that demand immediate attention.

Why AI Is Now Inevitable in Claims

The evidence supporting AI's inevitability in claims processing is overwhelming. According to a 2024 Carrier Management study, approximately 66% of P&C carriers plan to use AI for operational decisions within the year, while current adoption hovers around 14%. This gap doesn't indicate hesitation, but it signals a massive wave of implementation about to break across the industry.

Executive sentiment confirms this trajectory. A 2025 survey by Roots Automation revealed that 90% of insurance executives express optimism about AI, with two-thirds being "strongly in favor" of its application within the insurance sector.

Early adopters are already demonstrating remarkable results. Sedgwick, a prominent claims management service provider, reduced claim review times from 15 minutes to just 2 minutes per claim using generative AI. Similarly, CURE Insurance reported productivity gains of 60–70% in their claims operations through AI deployment. These aren't marginal improvements; they represent transformative efficiency gains that translate directly to competitive advantage.

Capital investment patterns confirm AI's central role in insurance's future. According to Gallagher Re's Q2 2024 findings, over 63% of global insurtech funding was directed toward AI-first solutions.

The High Cost of Inaction

While the benefits of AI adoption are compelling, the consequences of delay are potentially devastating. Organizations that hesitate will find their competitors settling claims faster and more efficiently, damaging customer satisfaction and retention.

The financial implications are equally concerning. Without AI automation of routine tasks, loss adjustment expense (LAE) ratios will remain stubbornly high compared with AI-augmented competitors. This hurts profitability and the ability to offer competitive premiums.

The internal impact on workforce capabilities presents another risk. A 2025 study found that 58% of claims professionals using AI report low confidence in available technological tools, often linked to insufficient training. Organizations without comprehensive AI adoption plans will see existing technology gaps widen, leading to decreased employee morale and difficulty attracting talent.

Perhaps most critically, regulatory scrutiny of AI in insurance is intensifying. As of March 2025, 24 U.S. states had adopted the NAIC Model Bulletin on the Use of Artificial Intelligence Systems by insurers. Companies operating without formal AI policies are not only unprepared for regulatory inquiries but are at higher risk of non-compliance.

The Imperative of a Formal AI Policy

As organizations integrate AI tools into their core operations, establishing a comprehensive AI policy becomes foundational for responsible innovation and risk mitigation. This policy must address how AI technologies are developed, deployed, and managed within the claims organization.

A robust AI policy ensures alignment with regulatory requirements, establishes clear accountability for AI-driven decisions, and provides guidelines for responsible data usage. It also creates transparency for stakeholders, building trust in how AI is being leveraged.

Navigating Security and Confidentiality Concerns

For many executives, security and confidentiality concerns represent the most significant barrier to AI adoption, particularly regarding large language models (LLMs). These concerns are valid but manageable with proper governance.

The key is implementing appropriate safeguards, including data anonymization, secure API integration, and clear policies on what information can be processed through external AI systems. Many organizations are finding success with hybrid approaches that leverage both internal, secure AI systems for sensitive data and external tools for non-sensitive tasks.

A Familiar Turning Point

The current AI inflection point bears striking similarities to previous technological revolutions that transformed the insurance industry. In the 1980s, early PC adopters gained significant advantages in data processing. In the mid-1990s, companies that embraced the internet established digital presences that became crucial competitive differentiators.

Today's AI revolution represents a similar watershed moment. Early adopters are establishing capabilities and competitive advantages that will be increasingly difficult for laggards to overcome.

Your Next Move: Strategic AI Adoption

For P&C claims organizations, the path forward is clear: Strategic, governed AI adoption is now mission-critical. This doesn't mean reckless implementation but rather a thoughtful approach that balances innovation with appropriate governance.

Begin by assessing your claims processes to identify high-impact AI opportunities. Develop a formal AI policy that addresses governance, security, and ethical considerations. Invest in training to ensure your workforce can effectively leverage AI tools.

The time for tentative exploration has passed. The organizations that will thrive in the next era of insurance are those taking decisive action today to harness AI's transformative potential in claims.

The global insurance industry stands at a crossroads in 2025. Economic instability, climate disruption, evolving customer expectations, and fast-paced technology shifts have created a market defined by uncertainty and opportunity. For insurers, the question is no longer just about growth—but about resilience, relevance, and reinvention.

In this landscape, winning is not about being the biggest—it's about being agile, innovative, and customer-obsessed. 

Here are five forward-thinking strategies that can help insurers not only survive but thrive in 2025 and beyond.

________________________________________

1. Build Resilience With Real-Time Risk Intelligence

The traditional approach to underwriting and risk assessment—largely historical and static—no longer cuts it in a hyper-dynamic environment. From climate events to cyber threats, risks are changing faster than insurers can traditionally model.

The winning strategy:

Leverage real-time data and AI-driven analytics to assess and price risk dynamically. Insurers must invest in IoT integrations, geospatial intelligence, and machine learning to evaluate risks as they evolve. For instance, property insurers can use satellite imagery and sensor data to adjust policies instantly during extreme weather.

This level of adaptability not only enhances profitability but also builds customer trust—especially when insurers proactively manage risk instead of just reacting to it.

________________________________________

2. Redefine Customer Experience Through Personalization

Today's insurance customers—especially Gen Z and millennials—expect services that are fast, digital-first, and tailored to their needs. Yet many insurers still operate on legacy systems with generalized offerings and one-size-fits-all communication.

The winning strategy:

Use customer data to power hyper-personalized experiences, products, and pricing. AI-powered virtual assistants, predictive analytics, and digital onboarding tools can help offer customized policies in minutes. Beyond convenience, personalization also increases customer retention and boosts cross-selling opportunities.

Additionally, insurers must rethink customer engagement—shifting from a transactional model to one that builds relationships. Think wellness programs for health insurance or safe-driving rewards in auto coverage. The goal is to be present and valuable between claims, not just during them.

________________________________________

3. Operational Agility: Automate, Streamline, Scale

Operational efficiency is no longer about cost-cutting—it's about being fast and flexible in responding to market changes. In 2025, the most successful insurers are those that can launch products quickly, resolve claims swiftly, and make real-time policy adjustments.

The winning strategy:

Adopt cloud-native platforms, invest in low-code/no-code tools, and automate everything from claims processing to compliance reporting. This isn't just about reducing manual work—it's about freeing human talent to focus on high-value, strategic tasks.

Modular product architecture can allow insurers to rapidly introduce micro-insurance products or temporary coverage for niche needs like gig workers, short-term travel, or cyber risk.

________________________________________

4. Embed Sustainability and ESG at the Core

Regulators, investors, and customers are increasingly demanding accountability when it comes to environmental, social, and governance (ESG) factors. Insurers are uniquely positioned to influence responsible behavior—through both their underwriting policies and investment strategies.

The winning strategy:

Develop green insurance products (e.g., lower premiums for eco-friendly homes or EVs), and integrate climate risk assessments into underwriting. Align the investment portfolio with ESG goals, such as supporting renewable energy projects.

Insurers that demonstrate purpose-led values and environmental stewardship are more likely to build customer loyalty, meet compliance requirements, and attract ESG-conscious investors.

________________________________________

5. Foster a Culture of Continuous Learning and Innovation

In an uncertain world, innovation is not a luxury—it's a survival skill. Insurers that cling to legacy thinking risk being left behind by insurtech disruptors and digital-native competitors.

The winning strategy:

Promote a culture of experimentation, invest in digital upskilling, and create innovation labs or partnerships with startups. Encourage teams to pilot new ideas, fail fast, and learn quickly.

Moreover, future-ready talent is critical. As underwriting, claims, and customer service become more tech-driven, reskilling the workforce and redefining roles will help insurers stay ahead of the curve.

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Looking Ahead: From Risk Manager to Risk Partner

2025 is not just a test of operational strength—it's a test of vision. Insurers that position themselves as risk partners—not just risk protectors—will win market share and customer loyalty.

By helping businesses and individuals prevent losses, recover faster, and plan ahead, insurers can transform from reactive providers to proactive enablers of resilience.

________________________________________

Conclusion

The insurance industry in 2025 is being shaped by forces that demand transformation—not tweaks. The winning formula is clear:

• Be dynamic in risk intelligence
• Be personal in customer engagement
• Be agile in operations
• Be ethical and future-focused in values
• Be bold in innovation

Those who embrace change will not only withstand the uncertainty—they'll define the future of insurance.