While our coverage at ITL these days can feel like "all AI, all the time," there's still a massive open question: How quickly can we develop and adopt AI agents that can act on our behalf? 

Most of the articles submitted to me are from enthusiasts, but there are reasons to be cautious, too. We've all seen or read about the hallucinations AI can have, about how AIs can learn to be ugly, and so on. How do we know they won't do something stupid or offensive if we cut them loose? One nasty lawsuit or loss of a major customer can outweigh a lot of efficiency gains.

Insurance will get there with AI agents. The question is just how fast. If you could tell me today what adoption would look like at the end of the year, I could tell you a lot about the state of innovation in insurance. So I'll be watching closely.

Six other areas also seem to me to be key for this year. The two other huge ones are the spread of the IoT, which is letting us monitor so many more issues in real time, and the growing adoption of the Predict & Prevent model, which helps turn that new data into ways of protecting customers. Embedded insurance and parametric insurance are also playing increasingly important roles — and have lots of potential still. And autonomous vehicles have built a launching pad that could let them take off this year, with all sorts of implications for insurers. Finally, I'll focus on the general notion of speed. Sometimes, a quantitative change is important enough to make a qualitative difference, and I think some processes in insurance, such as underwriting, may start moving so much faster that they could change the competitive landscape.

Let's have a look at the seven keys I'll be scrutinizing this year — and think you should be watching, too. 

AI Agents

My caution stems from the sort of problem I've witnessed in years and decades past related to "decision rights." Remember when "Internet refrigerators" were supposed to track what you had in them and order, say, milk for you when you were running low? Well, I didn't want my refrigerator ordering for me. Maybe warn me if I'm running low on something or be able to tell me when I'm at the store whether the thyme is still usable, but that's it. I control what I eat. 

I'd love for AI agents to take repetitive work off my plate, but I give up control slowly. 

My optimism stems from the sort of vision that my old friend and colleague John Sviokla described in a webinar conversation we had recently on AI. He described AI agents as employees that we'll be able to supervise and monitor as we do our current staff and suggested that each of us might have dozens of highly trained AIs whose autonomy is carefully circumscribed. He said job interviews in the future will include the question, "What AI agents do you have? Show me your bots." If you don't have an impressive array, John said, it will be like interviewing for a chef position at a fancy restaurant without having your own set of knives.

AI agents will be a big one to watch.

IoT

The Internet of Things, especially if you include auto telematics, has already made a massive impact on insurance. Drivers are being coached to be safer. Devices are detecting fire hazards so well that carriers are giving them away to customers. Water leak detectors in homes are getting closer to that tipping point, too, where carriers will give them away because they'll prevent so much damage. 

A sort of operating system for homes now lets any sort of device communicate wirelessly with it and have a signal relayed, letting you know about that water leak or that your smoke detector has gone off while you aren't home. Amazon's Sidewalk creates what's known as a mesh network that allows wireless connections to all sorts of nodes, even in public spaces, that can relay a signal to wherever it needs to go. Meanwhile, sensors just keep getting smaller — I wrote in November about how researchers had even managed to outfit Monarch butterflies with trackers weighing .06 gram.

Progress will only accelerate.

Predict & Prevent

When I got involved with Insurance Thought Leadership a dozen years ago, following decades of writing on innovation and technology, the first talk I gave carried the title, "He Who Sells the Least Insurance Wins." My reasoning: Nobody wants to buy insurance, but everybody wants safety. So why focus on selling insurance when the industry can take its massive amounts of data and expertise and provide safety?

That's obviously easier said than done, but I've been delighted to see that there's been so much progress and that the industry is rallying around the Predict & Prevent idea (sometimes called by slightly different names). At ITL — and more broadly at The Institutes, of which ITL is an affiliate — we've tried to highlight some key examples, such as Whisker Labs' Ting, which detects electrical faults in homes and is preventing hundreds of fires a year, and Nauto, whose two-way cameras in truck fleets are drastically reducing accidents. 

In 2026, we'll highlight as many more as we can — while hoping for more breakthroughs.

Embedded Insurance

Embedded insurance had a big year in 2025, to the point that toward the end of the year authors published two major articles with us on the topic. One said embedded insurance was nearing a tipping point and marshaled an impressive amount of evidence about the companies leading the way. Another said embedded insurance wasn't just a way of reducing distribution costs but had become a key part of the customer experience, by simplifying the purchasing process.

There are some complications. For one, agents will resist being cut out of the purchasing process. For another, carriers that offer insurance as part of the purchase of something else risk ceding control of the experience to the seller of that product. The insurance could even be treated as a commodity, meaning one carrier could easily be swapped out for another. 

But the convenience is still so great and the drop in customer acquisition costs so substantial that I expect more and more insurance to become embedded.

Parametric Insurance

Parametric insurance is showing up, in particular, in agriculture and in natural catastrophes, where it's relatively straightforward to find an agreed-upon metric, such as wind speed or lack of rainfall, and where a speedy, partial payout on damages can be key to keeping a business running or to rebuilding quickly. 

We haven't covered it as much as we might have, but I suspect we'll see parametric insurance make inroads in lots of areas in 2026.

Autonomous Vehicles

AVs have had their ups and downs in the nearly 13 years since Chunka Mui and I wrote a book on the topic, but they seem to finally be on a glide path — and an exponential curve at that. While Uber, Cruise and others have fallen by the wayside, Google's Waymo keeps expanding relentlessly. It's up to 450,000 fully autonomous paid rides per week in the U.S. and expects to hit 1 million a week late this year. (Waymo tends to understate its goals and routinely exceeds them, unlike, say, Tesla, where Elon Musk has been promising full autonomy for a decade but only has perhaps 30 robotaxis on the road at the moment, almost always with safety drivers.) Waymo keeps expanding into more cities and will even move into London this year, where it will go head-to-head with China's Baidu. 

Amazon's Zoox has begun offering limited service, as have some startups, including May Mobility and Nuro. Nvidia just announced big plans to supply the technology and even much of the AI for car makers that want to develop AVs, debuting with a slick offering it developed with Mercedes. Tesla, of course, continues to talk big — and much of Musk's potentially $1 trillion pay package depends on meeting aggressive plans for AVs. 

AVs have taken hold enough that an ER doctor — as in, not a techno-optimist — recently wrote an op-ed in the New York Times arguing that we have to move as fast as possible to AVs for public safety reasons. He argued that AVs are now so clearly safer than human drivers that we have no choice.

I think it'll be a big year for AVs, whose effects will eventually trickle down not just into auto insurance but health, life and workers' comp.

Speed

One of the impediments to innovation in insurance has always been that it takes so long to see if an idea will pan out. In Silicon Valley, when they talk about A-B testing, they're talking about testing thousands of different ideas — headlines, offers, etc. — every second. In insurance, if you want to test a new price or new product, regulatory approval alone can take months, no matter how fast you go internally. 

But generative AI has increased the metabolism in insurance, and I think we're just beginning to pick up speed. Because Gen AI can gather so much information so fast and at least pre-process it, claims agents and underwriters can make decisions faster than ever before. Carriers can also start experimenting with automating certain classes of submissions and claims so that a human never even has to touch them. Agents can respond to customers faster, too, and speed everything along.

Those who increase their speed the most will win a competitive advantage, according to all sorts of surveys showing how much customers value quick payments and how carriers and MGAs may lose business if they're slower than the other guy at responding to a submission. 

Increased speed could cause even more fundamental shifts. For instance, here is a piece we published recently on how underwriting could move so fast in some cases that no binder would be needed. Just think about how much work that could eliminate. Or, consider what happens if policies aren't just reviewed at renewal, and underwriting becomes continuous, updating as circumstances change. There are all sorts of implications, as Bobby Touran and I discussed in a recent webinar that carried the confident title, "Continuous Underwriting Changes Everything."

Speed is such a powerful but broad force that it's hard to see just where it takes us, but I'm sure it'll be somewhere interesting and important.

Here's to a fascinating 2026!

Cheers,

Paul

In an increasingly competitive marketplace, insurers are looking for every edge they can find to enhance operational efficiency and drive profitable growth. Digital payments have had a positive impact in these areas as the transition from traditional payment by check streamlines the disbursement process and reduces costs. Now, new research shows that digital payments are just as important when it comes to retaining customers in the face of rising premiums.

One Inc. commissioned industry analyst Celent to investigate key drivers of policyholder satisfaction in the claims process so insurers could better understand where to focus improvement efforts that would really move the needle. To do this, Celent polled more than 300 auto insurance claimants about their experience.

The good news is that 75% of respondents were "somewhat" or "extremely" happy with their claims experience. Moreover, a good claims experience can also create "loyalists," which Celent defined as policyholders who will stay with their insurer despite a rise in price. Nearly 40% of cat claimants and 25% of non-cat claimants in the study said they would stick with their current insurer, even if it costs them more. Impressive numbers, to be sure, but that leaves a significant majority of policyholders — both cat and non-cat — at risk with every claim.

Insurers must focus on strategies for retaining these price-sensitive customers, and this is where the power of digital payment capabilities can make a major difference in policyholder loyalty.

Speed of Payment is King

While policyholders appreciate quick claims cycles, how fast a claim closes matters less than how fast they receive their payment. For all claimants, speed was the most important aspect of payments. What is more striking is the response from dissatisfied claimants who were much more likely to say that speed was a top priority and were less likely to be satisfied with the speed of payment. These claimants really care about how quickly they're paid, and it's critical for insurers to meet that expectation.

Among dissatisfied non-cat claimants, 55% said payment speed was their top priority, and 62% of dissatisfied cat claimants ranked speed most important. It comes as no surprise that catastrophe claimants place even greater weight on how quickly insurers disburse claims since they are trying to rapidly rebuild their lives. Cat claimants were found more likely to be "extremely" dissatisfied with speed of payment (9% compared to 3% of all claimants) and less likely to be "extremely" satisfied (38% compared to 43%). Insurers must take advantage of this clear opportunity to deliver speedy payment and ensure an experience that creates lasting loyalty.

While slower payments don't necessarily doom the process, faster payments are clearly a driver of satisfaction.

Payment Choice Matters

It is not only the speed of payment that matters, but also policyholder control over how claims get paid.

The research found that paper check was the most common form of payment, at 34%, and most claimants (57%) don't have the ability to choose how they receive their payment. It was also found that when the insurer chose the form of payment, the claimant wished they would have been able to make their own choice in a majority of cases.

Indeed, allowing claimants to choose how they receive their payments leads to high levels of satisfaction. Of claimants who were allowed to choose, 85% indicated they had a positive experience overall, with 50% indicating their experience was "extremely" positive. Just providing choice of payment methods can be a game changer for insurers.

Moreover, the study revealed claimants' familiarity with digital wallet products. Nearly half said they have used Cash App, Apple Pay, or similar products in the past, and over two-thirds of the total survey group have previously used a virtual card. Clearly, the insurance policyholder market is becoming comfortable with digital payments and wants the ability to choose between traditional methods and the proliferating number of digital payment options.

Growing the Loyalists

While digital payments are not the only factor in claims satisfaction, based on this new data, partnering with providers who can facilitate faster payments and more flexible payment options for policyholders is critical for insurers to build more loyal customers.

Digital payment solutions such as our ClaimsPay are delivering on the promise of insurance, enabling insurers to disburse claims the way people are transacting more and more in their everyday lives. Leveraging modern technologies may have seemed esoteric just a few years ago, but today, virtual cards, electronic funds transfers, and digital wallets such as Venmo, PayPal, and Apple Pay can take a stressful and rare process and make it a familiar one.

Digital payments are a critical tool that gives insurers more control over the customer experience when premium increases are inevitable, over time. Taking advantage of this financial technology is critical to transforming claimants from being at risk with every claim to "loyalist" policyholders who will stick with their insurer even if their costs increase.

For generations, the fundamental promise of insurance brokers and insurance companies has been reactive: a financial safety net designed to catch clients after they fall. We repair, and we replace.

However, as we navigate an increasingly volatile risk landscape marked by climate change, supply chain complexity, and inflationary pressures, this traditional "utility" model is under increasing strain, particularly in sectors where loss frequency and severity are on the rise.

The industry is approaching an inflection point where the frequency and severity of losses in certain sectors are threatening the viability of traditional indemnity coverage.

The most critical strategic insight for leadership today is that sustainable profitability and continued relevance will no longer come solely from sophisticated pricing of risk. It will come from reducing the risk itself.

We are witnessing a necessary paradigm shift from a reactive "repair and replace" model to a Predict & Prevent partnership.

The Burning Platform: Why the Shift Is Necessary

The traditional insurance model is under growing strain. Rising losses from weather-related catastrophes and so-called secondary perils have increased earnings volatility and placed pressure on the affordability and availability of coverage in certain regions.

Swiss Re's research highlights that global protection gaps — the difference between economic losses and insured losses — remain large, despite recent improvements in industry profitability and capital strength.

While favorable macroeconomic conditions may support insurers' ability to absorb risk, significant portions of global exposure remain uninsured, underscoring structural limitations of risk financing alone.

If insurers continue to operate primarily as financial utilities that engage only at the point of loss, two strategic risks emerge:

• Commoditization: Clients increasingly perceive transportation insurance premiums as a necessary cost rather than a source of real value.
• Adverse selection: As pricing hardens, lower-risk clients may retain more risk through captives or higher deductibles, leaving carriers with deteriorating risk pools.

These dynamics reinforce the need for insurers to move beyond indemnification toward models that improve client resilience.

The New Value Proposition: Active Risk Partnership

The future winners in commercial lines will be those that become active risk partners. The goal is to move from merely financing the loss to mitigating the circumstances that cause it.

McKinsey says the future of insurance lies in evolving from "detect and repair" to "predict and prevent," estimating that this shift could fundamentally reshape the industry's role in the global economy.

This shift requires converging three key capabilities to change the client relationship:

1. IoT: Moving From Observation to Intervention

For years, telematics has been used primarily for pricing segmentation. The strategic pivot involves moving from passive monitoring to active intervention.

In commercial property, the focus is shifting toward sensor technologies that can physically intercede to prevent losses. Water damage—a primary driver of non-catastrophe commercial property losses—can be significantly mitigated through IoT-enabled automatic shut-off valves.

Deloitte has highlighted how this technology is transforming commercial real estate risk management, allowing insurers to eradicate high-frequency attritional losses and preserve capital for true catastrophes.

2. AI and Data: Democratizing Risk Engineering

Historically, bespoke risk engineering advice was reserved for the largest corporate clients. Today, advanced analytics and AI allow carriers to scale this advisory capability across the mid-market portfolio.

Analysis by Accenture indicates that generative AI is moving beyond back-office efficiency and toward core business functions, including underwriting and risk advisory. By ingesting vast amounts of data regarding location and assets, insurers can create near-instant, personalized risk assessments, enhancing the underwriting process and improving portfolio quality.

3. Parametric Structures: Closing the Resilience Gap

Traditional indemnity remains vital, but its claims adjustment process is often too slow for modern business continuity needs.

We are seeing increased interest in parametric solutions used not as replacements for traditional covers, but as complements. These solutions, triggered by objective data parameters (such as wind speed or flood depth), provide rapid liquidity. Marsh McLennan notes that parametric structures are increasingly vital for covering non-damage business interruption (NDBI) and providing immediate cash flow while traditional claims are processed.

The Executive Takeaway

The transition to Predict & Prevent is not merely a technology upgrade; it is a fundamental business model evolution.

It changes the carrier's role from a distant payer of claims to an always-on partner in business resilience. For the C-suite, prioritizing this shift is essential not only for improving long-term underwriting ratios but for ensuring the continued relevance of the insurance industry in a riskier world.

These 2026 cybersecurity predictions offer insights into the trends that will be front and center in the coming year, particularly around AI and data protection.

There is a great deal at stake. The business world is on the verge of making significant AI breakthroughs, but the technology has some serious security gaps that must first be addressed. At the same time, regulatory environments around the globe are increasing pressure on companies and AI providers to establish provable, trustworthy practices. And while practical quantum attacks may be several years away, the "harvest-now, decrypt-later" threat is creating urgency for organizations to act today.

All of this is driving a critical need for organizations to ensure end-to-end protection of data at rest, in transit, and, most importantly, in use – without which, companies expose themselves and their customers to potentially irreparable harm.

The predictions below are intended to help guide organizations in embracing AI-powered innovation while maintaining persistent protection of sensitive data and ensuring regulatory compliance across regions worldwide.

1. Confidential AI: A Business Imperative

In 2026, enterprises will integrate AI more deeply into core operations, moving beyond experimentation toward scaled, business-critical deployments. This expansion will expose the limits of today's security measures and accelerate demand for "Confidential AI" — systems designed with built-in privacy, encryption, and trust guarantees.

Much like the early days of the Web, when open protocols gave way to HTTPS and SSL, organizations will shift from simply using AI to securing the full AI lifecycle – from data ingestion to model training and inference. As breaches targeting AI models and systems increase, companies will adopt proactive protection strategies by embedding privacy, encryption, and integrity controls directly into their AI architectures.

As enterprises advance their AI capabilities, Confidential AI will emerge as the new standard – embedding privacy and protection into every layer of the AI lifecycle. Through continuous, end-to-end encryption and confidential computing, organizations can train and run models securely, even on sensitive data. In the year ahead, growing demand for zero-trust AI ecosystems will redefine the landscape, making security the hallmark of enterprise AI rather than an afterthought.

Predictions 2026:

• Organizations will move beyond protecting perimeters and threat detection to securing models, data, and inference chains.
• Confidential AI, powered by continuous encryption and secure enclaves, will define the next phase of AI security.
• AI security will evolve toward "Confidential AI," where encryption and privacy-preserving computation become essential for trusted enterprise deployment.

2. Compliance and the Rise of Sovereign AI

In 2026, as AI compliance takes center stage in the enterprise, we'll also see the rise of Sovereign AI – nationally governed AI ecosystems that affect global data flows. As nations tighten restrictions on how models are trained, hosted, and shared, companies will face growing pressure to demonstrate compliance across multiple jurisdictions simultaneously. This will require organizations not only to meet their country's privacy and data security standards but also to comply with foreign laws governing AI transparency, data residency, and model integrity.

The next wave of regulation will focus on "trustworthy" models – AI systems that can prove, through cryptographic means, that data remains secure and private throughout the entire lifecycle. Governments, telecom companies, and cloud providers will need to go beyond contractual promises to offer verifiable assurances that they cannot see or misuse a customer's data or model. Model theft, data exfiltration, and misuse of AI-as-a-Service will rise sharply, forcing providers to deliver cryptographic evidence of confidentiality to satisfy regulators and clients alike. In 2026, enterprises operating in multiple regions will recognize that compliance and security are inseparable, and that continuous encryption will become the cornerstone of regulatory trust in AI.

Predictions 2026:

• Sovereign AI will push multinational compliance beyond borders, demanding alignment with overlapping global standards.
• Model-as-a-service providers will face rising risks of theft, exfiltration, and regulatory scrutiny.
• "Trusted models" will require cryptographic proof of data confidentiality and model integrity.
• Technologies such as FHE and secure inferencing will underpin compliance verification frameworks.
• Cryptographic assurance will become the foundation of AI trust, compliance, and cross-border collaboration.

3. Quantum Resiliency and Latency-Optimized FHE

In 2026, quantum computing – both a looming technological breakthrough and cybersecurity threat – will remain a key concern among enterprise CISOs. The "harvest-now, decrypt-later" tactic, where adversaries stockpile encrypted data to decrypt once quantum hardware matures, will accelerate demand for latency-optimized, quantum-safe encryption. When the day comes, traditional standards like RSA and elliptic-curve cryptography will be rendered obsolete by quantum algorithms, leaving unprotected financial data, health records, and AI models vulnerable.

The next wave of security innovation will focus on quantum-resilient encryption at scale, capable of protecting data without slowing real-time AI workloads. Latency-optimized, production-grade fully homomorphic encryption (FHE) enables computations on encrypted data, safeguarding information throughout the AI lifecycle.

Predictions 2026:

• The "harvest-now, decrypt-later" threat makes post-quantum migration urgent today.
• Latency-optimized FHE enables quantum-resilient AI inference without compromising performance.
• Quantum-safe, latency-optimized FHE will be recognized as essential infrastructure for securing AI systems worldwide.

In the coming year, the benefits of AI will only be accessible when the technology is built upon a tapestry of privacy and security. The collective, urgent need for proactive protection, data sovereignty, and quantum resilience is driving Confidential AI to become a prerequisite for enterprise competition and trustworthiness. By building security into the very fabric of their AI, organizations can confidently protect their most valuable assets, innovate across borders, and gain the competitive trust necessary to thrive in the global digital economy.

Insurance fraud in property and casualty insurance is no longer dominated by isolated bad actors slipping through the cracks. Increasingly, the most damaging fraud comes from coordinated networks of claimants, service providers, and intermediaries who understand carrier processes and exploit their fragmentation. These schemes rarely trigger obvious red flags at the individual claim level, which is precisely why they are so costly and so difficult to stop.

The Scope and Impact of Fraud in P&C Insurance

The cost of fraud in insurance is staggering. According to the Coalition Against Insurance Fraud (CAIF), total insurance fraud (across all lines) is estimated at $308.6 billion per year in the U.S. Within the P&C sector, fraud represents a significant portion of losses. Industry analyses consistently estimate that 10% of P&C claims are fraudulent or involve fraud-related padding.

A recent report on fraud detection solutions estimates that roughly $50 billion in P&C paid claims may be fraudulent each year. Meanwhile, the FBI (via NAIC-supported research) has historically pegged total non-health insurance fraud — including P&C — at $40 billion annually. Another survey found that many insurers believe fraud costs represent 5-10% of their claims volume; some even reported that up to 20% of their claims were subject to suspicious activity.

These losses hit insurers' bottom lines directly through inflated payouts, but the effects ripple outward:

•  Premium increases: Fraud raises loss costs, which then contribute to higher premiums for honest policyholders.
• Operational drag: Investigating suspected fraud takes time, manpower and specialized expertise.
• Reputational risk: Organized fraud rings damage trust in the industry and can create regulatory scrutiny.

Why Network Fraud Evades Traditional Detection

Network fraud (also called collusive or organized fraud) refers to schemes where multiple actors cooperate to submit fraudulent claims or inflate losses. Rather than isolated "opportunistic" fraud, these are coordinated efforts that may involve:

• Claimants staging accidents or exaggerating damage.
• Repair shops or body shops submitting inflated or fake invoices.
• Brokers or agents steering business toward fraud-friendly networks.
• Collusion between claimants and medical providers, attorneys or investigators.

Because these networks are interconnected, detection is especially challenging. Traditional rule-based fraud detection — checking individual red flags on a claim — may not catch the systemic patterns. That's why more insurers are turning to network analytics, which analyzes relationships across participants to spot suspicious clusters.

In academic research, for instance, social network models have been applied to fraud detection. One study built networks linking claims, brokers, garages, policyholders and other participants, then applied specialized graph analytics to identify highly suspicious claims. These network-based approaches outperform traditional models, because they reveal hidden collusive structures that might evade conventional detection.

How Fraud Strategy Has to Change

Fraud Can't Be Evaluated One Claim at a Time Anymore: Most fraud controls were built to spot problems inside a single claim file. That approach works for opportunistic fraud, but it breaks down when activity is coordinated across people, vendors and claims over time. In network fraud, no individual claim looks especially suspicious. The risk only becomes clear when patterns emerge across claims, repair shops, providers or intermediaries. That reality is forcing insurers to connect signals across systems and teams rather than relying on isolated reviews.

Better Detection Still Requires Human Judgment: Advanced analytics and AI have made it possible to surface patterns that would never be visible through manual review alone. Network and relationship analysis can highlight repeated interactions and unusual clustering across participants, while machine learning can flag claims that deviate from expected norms. But technology does not replace investigation. These tools are most effective when they help experienced SIU teams focus their time on the cases that truly warrant deeper scrutiny.

Organized Fraud Rarely Stops at One Carrier: Fraud rings are adaptive and mobile. They move across insurers, jurisdictions and lines of business, learning quickly which controls are enforced and which are not. That makes fraud difficult to contain when each carrier operates in isolation. Industry collaboration, shared intelligence, and participation in fraud bureaus play an increasingly important role in disrupting organized activity. When carriers connect what they are seeing, repeat actors and emerging schemes become much easier to identify.

Prevention Starts Earlier Than Most Carriers Expect: As fraud becomes more organized, prevention matters as much as detection. Strong identity verification, consistent documentation requirements early in the claim, and training for frontline claims staff all reduce opportunities for coordinated fraud to gain traction. Clear communication around fraud consequences also acts as a deterrent. Over time, these measures lower investigative workload and help ensure that legitimate claims move through the system without unnecessary friction.

Network fraud is not a future concern for property and casualty insurers. It is already reshaping loss costs, investigative workloads, and customer trust. As fraud becomes more coordinated and less visible at the individual claim level, carriers that rely on traditional controls will continue to react after losses are locked in. Those that treat fraud as a networked risk can disrupt organized schemes earlier, protect margins more effectively, and reduce the burden on honest policyholders. The difference is not whether fraud exists. It is whether insurers can see it clearly enough and early enough to act.

A cyber incident hits a small business in a way that feels personal. The owner watches familiar tools fail, customers get locked out and schedules fall apart. They turn to their insurer looking for clarity, yet their expectations rarely match the process ahead. That disconnect shapes the entire claim and exposes where small businesses still misread cyber risk.

Many small operators still think that cybercriminals are carefully selecting their next target, but the reality is that automation has made it easier than ever for attackers to run broad scans across the Internet and strike wherever a shared account or outdated plugin gives them an opening.

It really doesn't take much. A rushed login, a forgotten update or a credential reused for convenience gives attackers the foothold they need. Those details rarely seem dangerous until the incident interrupts revenue, and the business owner realizes the breach reached everyday tools they rely on to run their business.

Misunderstandings around what triggers coverage

Confusion around coverage starts before a claim reaches the adjuster. Many small companies expect a cyber policy to function like a technical repair plan and anticipate quick fixes while assuming the carrier will take over the issue. Business owners also underestimate how fast costs build when dealing with investigations, data restoration and income loss that pop up in just the first hours of an incident.

The same pattern appears when incidents look minor from the outside. I've seen something as simple as a corrupted device wiping payment records for a food truck, and a damaged workstation forcing a photographer to cancel paid work. These events lacked the drama of national ransomware stories, but they still created lengthy downtime.

Tight staffing makes the fallout worse, because a single compromised login or failed device slows customer communication and sales. With no spare hands to absorb the disruption, small issues turn into long setbacks that strain the entire operation.

Where expectations diverge from what coverage provides

Cyber liability policies support recovery on two fronts.

• First-party coverage helps with investigation teams, data recovery, income loss and negotiation support during ransom talks.
• Third-party coverage addresses the fallout customers experience when their information becomes exposed.

Many small operators focus only on the technical failure and overlook how much involvement they will have once the claim starts. They may need to grant investigators access to certain devices or review which customer touchpoints were affected, and those responsibilities hit while they are already trying to steady the business.

On the flip side, executives hear from owners all the time who assume the carrier will fix the technical problem outright and feel blindsided when they learn how many steps sit between the first alert and a stable recovery. They do not anticipate the coordination needed to rebuild systems or manage customer notifications. That misunderstanding adds pressure to an already tense situation.

Security habits that stall during underwriting

Underwriting often uncovers a different kind of confusion. Many owners treat basic safeguards as add-ons rather than the foundation that keeps incidents contained, and controls like MFA or scheduled backups usually receive attention only when the application requires them, not when the business starts taking on digital risk. Once owners finally put those safeguards in place, they tend to keep them because the checks and alerts make daily operations steadier.

An office can cut risk by using a password manager and running brief phishing reminders with staff. A restaurant benefits when its reservation system restores from a recent backup instead of staying offline after a plugin failure. These steps rely on consistency more than technical skill, yet many owners delay them until an attack forces the lesson.

A clearer path forward

Cyber incidents reveal more about a business than the breach itself. They expose how prepared the team feels, how they handle uncertainty and how they respond when everyday tools fail. Insurance leaders watch this play out across industries, and those moments show the real gap between perception and reality for small companies.

Carriers cannot remove the stress that comes with a breach, but they can steady the path forward. Helping owners understand their role and their responsibilities changes how they navigate the experience. Cyber liability coverage gives them a path to continue operating during their hardest moments. Helping small companies understand that earlier reduces friction and sharpens the support they receive when an incident tests their systems.

The 2026 P&C insurance environment may be much easier to forecast compared with the last several years. Many experts have already said 2026 will be a year of profitable growth. Fitch suggests a combined ratio of 96% to 97%, and even the volatile homeowner market is anticipated to "stabilize." Similarly, it is obvious the new year will be filled with AI in insurance, building off widespread hype and numerous announcements of huge, multi-year investments by the likes of Travelers, Nationwide, GEICO, and Chubb. Just how much and deeply AI will affect insurance remains far less visible, with some areas of attention coming into focus, e.g., pre-binding, underwriting data, claims/FNOL analysis.

Looking back to "see" forward

We also know that each year can bring some unexpected and unwelcome surprises, such as the record-setting $40 billion-plus Palisades wildfires burning some 23,000 acres and everything in its path a year ago. On the flip side, not a single hurricane hit the U.S. Atlantic coastline in 2025. Global CAT losses still amounted to $107 billion in 2025, per SwissRe, but to put things in perspective, Hurricane Katrina in 2005 was around $105 billion alone. Severe CAT exposure has become more visible and thus accepted. In turn, risk models have presumably adjusted over the recent years, and, optimistically, the industry is better prepared.

Throughout 2025, M&A remained vibrant, with insurtech funding just over $1 billion per quarter and an increase in early-stage funding toward the end of year, per Gallagher. A closer look at some specific trends:

• Commercial rate softening, with much variation, e.g., property lines down, commercial auto up and workers' compensation flat
• New car sales slumping by 7.5% at year-end
• Car loan terms elongating beyond 60 months and car loan payments reaching a record of $760 monthly average, per JD Power
• Total loss auto rates rising, to 23%
• Overall auto claim repair volumes declining roughly 8%
• Deductibles for both auto and home climbing, shifting the financial burden from insurer to consumer. According to a study by MATIC, home deductibles are up 22%

As we look to 2026, the following trends help bring rationale for how we see things shaping P&C insurance into a year of progress and collaboration, including:

• Accelerating digitization
• Climate change
• Pressure on globalization
• Rising economic and social inequities
• Major demographic shifts
• Layoffs

AI in Insurance

Investments and practical insurance industry applications of AI will continue to expand even as a large number of AI startups fail and regulators try unsuccessfully to catch up to developments.

• AI will eliminate even higher numbers of less skilled employee positions, including transactional, customer service and document management. At the end of 2025, Chubb announced "radical" cuts of 20% over the next three years due to AI deployment. It is highly likely that other carriers will follow suit.
• A new breed of AI entrepreneurs will emerge to invent highly specialized consumer services delivering instant hyper-personalized gratification for information, retail therapy, mental wellness and unique "experiences."
• AI-enabled photo inspection will gain greater adoption across the insurance, automotive and transportation segments using computer vision and machine learning to automatically analyze images for defects, anomalies, damage, or authenticity, replacing or assisting manual visual operations. This technology will be applied across various industries including insurance to enhance efficiency, consistency, and fraud prevention.

Other Key Factors

Affordability will reverberate beyond a broad consumer/political cost-of-living issue, circling back to P&C insurance where unaffordability chants arguably began. Cost of coverage, availability, pricing and rating methodology will draw even greater attention from consumer groups and regulators. Protection gaps and total cost of home or vehicle ownership will become primary concerns replacing 2024/25 inflation and supply chain worries.

Sustainability will gain adoption across the insurance value chain, especially the North American ecosystem, influenced by global re/insurers. Areas of early focus will include risk and claims management such as auto physical damage and property. Sustainable insurance will reduce risk, develop innovative solutions, improve business performance, and contribute to environmental, social and economic sustainability. Lessons learned from consecutive catastrophic events may serve as a tipping point, taking holistic approaches to predict, harden and prevent.

Climate risk modeling will gain energy. Demand is high and growing for accurate, usable climate information, particularly data that can help assess risk more accurately and contextually. This will drive carriers and others to probe every level of risk, from neighborhoods exposed to more frequent flooding, and to test if proposed atmospheric cooling approaches can work safely, if at all. Interest and investments in climatetech that can benefit insurance will grow significantly.

Cyber threats and fraud losses will continue to expand as digitalization spreads around the world. Recent cyber claims frequency trends remained low while severity increased, presenting the insurance industry with a huge—yet hugely challenging—opportunity.

Insurtech consolidation will accelerate as partnerships and acquisitions become de rigueur and single-point, stand-alone solutions continue to lose favor. The future of insurtech is shifting from rapid disruption to sustainable, AI-driven integration, with the market projected to reach up to $254 billion by 2030. Key trends include AI-powered automation for claims and underwriting, hyper-personalization, embedded insurance, and a focus on profitability over pure growth. Agentic AI platforms will automate routine tasks, potentially cutting outsourced insurance roles in half by 2028. AI will also enhance risk assessment and, in some cases, replace traditional underwriting.

Embedded insurance will continue to emerge as a significant distribution channel as discreet insurance offerings are packaged with the related product/service purchase at the point-of-sale in a singular transaction. Auto insurance packaged with new and used cars will grow as OEMs and dealers seek new profitable revenues.

Open platforms and marketplaces will continue to proliferate, and closed systems will face greater headwinds. Core insurance system platforms (e.g., Guidewire, Duck Creek, Majesco) now host hundreds of popular third-party product and service providers supporting claims, policy administration, billing and payments. Even the leading auto claims and repair information providers (e.g., CCC Intelligent Solutions, Enlyte/Mitchell and Solera/Audatex) have begun to pivot from proprietary closed systems to partnerships with emerging physical damage solution providers.

Consulting firms will restructure for agility, such as moving toward "one firm" models to blend technology and consulting, exemplified by PwC's 2024 internal leadership changes. Major firms like McKinsey, Accenture, and the Big Four have implemented layoffs amid shifting demand for services. AI is cited as a major driver, with a growing percentage of McKinsey's work involving AI-related projects and ultimately affecting the need for traditional roles.

Tech talent will be at a premium. All companies will scramble to retrain, upskill and upgrade staff to fully leverage new and emerging technologies. Change management principles will be dusted off and applied to the numerous influences AI will bring to enterprises seeking to excel. A recognition of the importance of people leveraging AI as much as replacing work functions will continue.

Regulatory risk management will require agility in a fragmented landscape. Navigating a changing regulatory patchwork will require investments in legal expertise and compliance infrastructure, which can drive up operating costs. Some insurers will likely cut their losses and focus on less risky markets. That could increase return on investment for organizations that try to take a broader approach with a longer strategic horizon.

Caveats/The Future

If we have learned anything from recent history it is that the future is inherently uncertain. Not all of our predictions will materialize. Black swan events may occur, reshaping markets, nations and the insurance industry in dramatic, unpredictable ways. But we are confident that most of what we have forecast will become reality. Either way, our projection of optimism for a healthy and vibrant P&C insurance industry in 2026 tops the list.

We look forward to seeing the industry move forward, making progress through technology and collaboration. 2026 will be another exciting year for the industry in both expected and unexpected ways.

Moments after the Baltimore Ravens kicker missed a near-gimme field goal attempt with no time left and let my Pittsburgh Steelers escape with a two-point victory that won them the AFC North and got them into the NFL playoffs, ESPN sent out a notification. The headline read, "The North Belongs to Ravens."

Oops. 

I'm sorry I was too busy whooping and hollering at my TV to quickly click on the notification, and ESPN had fixed the story by the time I got to it, but I can imagine the tone it took about my Steelers. After all, I've read all the vitriol aimed at the Ravens. 

Ravens head coach John Harbaugh would have been a hero in Baltimore if he'd won the game against his archrivals and snuck into the playoffs, but now there is even speculation he will lose his job. He had his team in a position where it was so obviously going to win that I had my finger on the remote, ready to turn the TV off the moment the ball went through the uprights, so I could go out into the yard and scream. But his kicker missed the field goal, so, boom, let's get rid of the bum.  

The coverage is not only wrong-headed — as much as I'm happy to see people beat up on the Ravens and Harbaugh — but demonstrates the sort of mistake that makes executives, including in insurance, evaluate innovation efforts poorly.

The problem is that we don't think in percentages, or at least not well. We may know that the Baltimore kicker had a nearly 90% chance to make his 44-yard field goal try, but we don't quite get that the percentage means he'll miss one time in 10. We know it, but we don't really believe it. So when the kicker misses, we just see failure and look for someone to blame. 

The Yahoo Sports writer acted as though the Ravens failure to make the playoffs was foreordained, even though they began the season as one of the top-ranked teams in the league. His article began: 

"From the beginning of the Baltimore Ravens’ season, when they had an epic collapse and lost to the Buffalo Bills, right to the end when their season ended with a loss to the Pittsburgh Steelers, nothing was good enough." He added that the Ravens "will be searching for answers after a season that went horribly wrong. There will be immediate questions about John Harbaugh’s future as the team’s coach."

The Steelers and head coach Mike Tomlin would have come in for exactly this sort of treatment if the field goal had been good, even though the Steelers had even a stronger gripe about the kicking gods being against them. The Steelers were only two points ahead, and thus in danger of losing to a field goal, because their kicker had missed an extra point with 55 seconds to go in the game, after not missing one all season. The pressure on Tomlin isn't entirely gone, given that he hasn't won a playoff game in eight years, but there will be a lot less of it in the off-season, especially if we beat the Texans in Pittsburgh on Monday night. 

The Steelers even came in for misconceived criticism despite winning the game. I always liked Trey Wingo when he was an analyst on ESPN, but he posted a Tweet that was downright silly. He said Tomlin made a terrible decision by going for a field goal at the end of the first half rather than trying for a touchdown from the Ravens one-yard line. He tried to back up his claim, but he was clearly just Monday morning quarterbacking — because the Steelers failed to score a touchdown, they shouldn't have tried.

The truly goofy part of his argument was his statement that, had the Steelers converted a chip-shot field goal, they would have been five points ahead of the Ravens at the end of the game, not two, and wouldn't have had to worry about a field goal. But come on. If the Steelers had scored a field goal, the dynamics of the game would have changed. The coaches would have made different decisions, and the players would have done different things in the different circumstance. You can't just take the three points and add them to their score for the rest of the night. 

The other part was nearly as bad. He offered an adage: "You always take the points." But the NFL has moved beyond a lot of adages and started to apply real, live math to questions such as when to go for it on fourth down, as I wrote a year ago. And here's the math:

A field goal would have been almost a 100% chance, so the Steelers could have counted on almost three points. The attempt at a touchdown had a slightly better than 70% chance, based on league averages, and an extra point is almost a lock. 70%-plus of seven points is roughly five points. Yes, the Steelers' attempt was embarrassingly incompetent, but I'm still going to take a likely outcome of five points over one of three points in almost every circumstance. 

This is the Ravens we're talking about. I need every edge I can get.

What does this mean for insurers?

Insurers need to think more like venture capitalists and less like Yahoo Sports or Trey Wingo. Venture capitalists not only know that 90% of the startups they invest in will fail but act on that knowledge. If they think an area is promising, they make a number of bets rather than assuming they're going to pick the one winner. They don't label their entrepreneurs as losers just because they lose — if you had a 90% chance to win but lost, they count that as a win and blame the circumstance, not you. As a result, VCs often invest in serial entrepreneurs, who have either previously failed or only had modest successes. 

A line from the mother of a girl who ski raced with my younger daughter has stuck with me. Stephanie, who build a financial software business she sold for $2.5 billion, told me: "I like people with scars."

Insurers also need to think of early innovation efforts as opportunities to learn, rather than trying to immediately shape them into pilot projects designed to scale and go to market. As I've been saying for almost 30 years now, the key is to Think Big, Start Small and Learn Fast — the latter two points meaning that you need to do lots of inexpensive projects, even though they're in the service of a grand vision, and move on quickly to the next set of tests once you've learned what you can. The vast majority of these projects won't get anywhere near the market, but they aren't failures if you've learned something important.

I'm hardly arguing for no accountability. There are still bad ideas, and they may be executed poorly by people who should no longer be part of your organization. I'm just arguing that we all take a more sophisticated view of success and don't decide that failing to convert a 90% chance merits firing — even though I'd love to see Harbaugh out of Baltimore.

Go, Steelers! Beat those Texans!

Cheers,

Paul

Paul Carroll

You’ve written for us about the need for hyper-personalization in life insurance. Would you start us off by describing what that looks like in practice, as well as how it differs from how life insurance has historically been handled?

Brooke Vemuri

I've been in the life insurance business for 23 years, working in both technology and operations, so I've seen firsthand the evolution from moving physical forms around the building—we had folders, and we put them in carts, and we drove them around to our underwriters—to where we are today. We've crossed a lot of hurdles over the last 20 years.

Now we're in a place where we have intelligent automation and a digital application process. Over the past few years, this has meant having an event-driven, rules-based system that allows us to capture the right application questions, then run rule sets underneath, call third-party data, and do all the things we need to amalgamate and come together on a decision. That change was hard to get across the line, but we've arrived and are doing very well as a result.

The next evolution is moving away from considering the application as one static process or one way to get to an outcome. Instead, we're moving toward tailoring the experience by distribution, by agent, by customer. Personalization means accommodating the way our agents and agencies like to do business.

Just to give you a small example: We have some agents who say, "Don't waste my time collecting beneficiary information. I'm going to get you everything I need to get a decision on the case. Then once I have a decision and the customer accepts, I'll gather that beneficiary information—it's more of an administrative piece of work because it's not influencing the decision." I have another distribution partner that says, "We start with beneficiaries. We connect the sale to the reason why you're making the purchase."

That's a high-level example on the easier side of personalization—how do we tailor or reorder the journey? 

Next comes determining how many questions we ask based on the product, and how we tailor that experience based on the product, the partner, and the customer. You start to get all these different variations of how you would flow a digital application process to collect the right information at the right time, make the right decision, and end up with a case you can place in force—in a way that works with every agent and partner you have.

You can start to see that there are going to be lots of permutations and combinations of how all of that evolves and comes together. From a technology perspective, that's all about creating the right, flexible architecture to make that happen, to allow that configuration, and to support our agents in the way they want to sell the business.

Paul Carroll 

Is this personalization extending beyond the sales process to policy offerings and features, as well?

Brooke Vemuri

Yes, that's a good question. Over the last 20 years or so, you typically entered the journey when you already knew what product you wanted. For example, "I know I want a term 20 policy. It's for a 50-year-old male with two children.” Now we're heading toward a different approach—someone starts the journey as that same person, but they really don't know what product or combination of features they want until they move through the journey.

Whether that means recommendations based on how many beneficiaries you have, what stage of life you're in, what your income levels are, or what job you have—as the system starts to understand who the customer is in the journey, we can start to make the right recommendations for a product.

I think you're going to see both tailoring of products and features. One of the things we're working on is how to come out with an offer for every applicant. Because in a lot of cases, there are still declines in our environment, even on term business. So how do you enter the process saying, "I have a desire to have life insurance" and be sure to end up with something—whether that's an accidental death product or a final expense product?

So yes, you're going to start to see tailoring of offers, cross-sell, counter-offers—that's what we're calling it. How do we come up with another product that might be viable for both the customer and the life insurance company so that, at the end of the journey, you still get some product that is available to you.

Paul Carroll

How is AI being incorporated into this process, particularly in terms of gathering customer information and providing real-time recommendations to agents during customer interactions?

Brooke Vemuri

Intelligence is coming into play primarily in our agent-facing capabilities. Our journey encompasses both customer-agent interactions and internal, employee-facing systems. As people interface with the system, it makes certain recommendations to the agent based on how the journey is progressing. 

You might not do that directly with a customer, though. If a customer is going through the process unassisted, it's a little bit more complex for them to navigate some of those things. So our thought process is a lot like TurboTax—in the upper right-hand corner as you progress, it shows what you're accruing, what we know now, and where we might go in this journey, and starts to forecast and give options for next best steps.

For now, we’ll just focus on agent-facing capabilities, because that feels more like advisory-type activities. That's at least our early thinking.

Paul Carroll

What innovation can we expect to see over the next few years?

Brooke Vemuri

I think we'll be very much focused on what we're talking about now, which is tailoring our apply processes—for both customer and agent. We're looking at getting some cues or indicators into the journey about how a case is tracking and how agents might handle what's going to happen in terms of that sale, whether it's going to be a decline or whether we can pivot to another product.

I think you're going to see all of that in the next two to three years—tailoring the counter offers or the alternate offers, tailoring the journey to align with how that agent wants to sell their business.

Beyond that, we're imagining a lot more variation on the product. We're going to see more things in terms of what we call table ratings today: How do we get more price variability in the product so we can accommodate more and more applicants? I think that's probably on the three- to five-year horizon.

Paul Carroll

What trends are you seeing around younger generations being more interested in living benefits rather than death benefits?

Brooke Vemuri

That's a good point. Things are being added on and tailored into the product that allow more utility out of the product. It's not a policy that you print and put on the shelf and wait till you die, and then someone gets the benefits of it. It's about how the policy can give you benefits while you're living—tapping into that face amount for critical illness or accidents and things like that.

I agree that living benefits are giving more value to the term product. I mean, there's still a need for your basic term product out there that has no bells and whistles. But to reach some of the younger generations, we're finding that living benefits have been valuable for them.

Paul Carroll

Life insurance policies represent long-term commitments—20 years for term policies, often longer for permanent ones—making it challenging to validate underwriting assumptions quickly. How is the recent industry shift toward fluidless evaluation and fewer application questions working in practice?

Brooke Vemuri

It does take years to know if your assumptions are right. I think the biggest value of the data right now is being able to look at historical data and model it in a way that makes us more comfortable with innovations—whether that's leveraging other third-party evidence sources or forgoing exams altogether, like with fluidless underwriting.

We're using a combination of historical data—looking at how it would perform based on our back book of hundreds of thousands of cases at this point—and other third-party evidence that we can leverage, like medical claims data and labs data. We're leaning heavily into claims data specifically.

It's really about putting those pieces of the puzzle together alongside the self-declarations from the application so that you have a complete picture to underwrite from and make a decision. We're going after alternative evidence sources to eliminate some exams while also looking retrospectively at the data to see what it's telling us. Through our modeling, we can apply new assumptions to that data, see what it might look like, and price accordingly.

Paul Carroll

What other trends should our readers be aware of in life insurance?

Brooke Vemuri

I think you've probably captured a lot of them. There's going to be a lot of tailoring—tailoring on the journey and tailoring on the products, tailoring on the prices, tailoring on the variation of features and capabilities that exist in the term product space.

How do we alternate out of term if we need to? How do we counter out of that if we need to? I think that's the real progress on the horizon.

Paul Carroll

Thanks, Brooke.
 

About Brooke Vemuri

Brooke Vemuri is vice president, IT and innovation at Banner Life and William Penn. She leads people and cross-functional teams to reimagine the future of life insurance from lead generation, through apply and underwriting, to offer, pay, and in-force. Her team drives transformation and change to the business and distribution through the development and execution of business propositions focused on growth and cost reduction through a digital business strategy.