Around the world, political, economic, and social uncertainties are on the rise. They can affect every aspect of a company's operations, as well as lead to significant changes in financial, regulatory, and legal environments. Failure to anticipate and adapt can expose companies to operational failings, financial loss and reputational harm with consequences for the companies' directors and officers.

According to Allianz Commercial's latest Directors and Officers (D&O) Insurance Insights report, D&Os can be held accountable for misjudging the impact of geopolitical developments on their company's operations or for failing to adequately adapt to the legal or regulatory requirements in different countries. Liability for D&Os may arise from shareholder lawsuits or regulatory penalties directed both against the entity and individual decision-makers.

At the same time, cyber liability risks for directors and officers have risen sharply in recent years with higher expectations for board level oversight of cyber security and a trend toward more litigation and regulatory actions. Exposures for D&Os typically arise from their duty to oversee the organization's cyber security posture.

Claims against directors have been triggered by a wide range of events, including data breaches, ransomware attacks, and even technical failures. Ransomware accounted for around 60% of the value of large cyber insurance claims (>€1mn) seen by Allianz Commercial during the first six months of 2025, according to its annual Cyber Security Resilience Outlook. Should a cyber incident result in financial loss, directors could face legal claims from shareholders, customers or suppliers if the board is seen to have failed to implement adequate risk controls or business continuity planning.

Insolvencies drive D&O claims globally

Bankruptcy and regulatory enforcement actions are among the top sources of private D&O claims, although claims can also arise from allegations for breach of fiduciary duty, such as misleading or inadequate disclosure, or negligence. According to Allianz Trade, global business insolvencies are expected to rise by 6% in 2025 and 5% in 2026. Next year will mark five consecutive years of increases to reach a record high number of bankruptcies, 24% above the pre-pandemic average. Insolvency risks are particularly concentrated in the automotive, construction, retail, and consumer goods sectors.

There has also recently been a notable rise in "mega bankruptcies" in the U.S. – those filed by companies with over US$1bn in reported assets. The first half of 2025 saw 17 such bankruptcies, the highest number since the Covid-19 pandemic, with 32 in the past 12 months, well above the historical average. The current challenging business environment – marked by factors such as tariffs, weak demand, rising costs, technological transformation, growing competition, and regulatory changes – is heightening the risk of bankruptcy and also claims against directors.

Claims activity is increasing in the highly dynamic D&O market

Over the past three years, there has been a continual increase in the frequency of new claims against directors and officers, now approaching or exceeding pre-pandemic rates in most regions of the world. Claims severity continues to be an issue in North America. For D&O insurers, the U.S. especially is a highly complex market due to its high frequency of securities class action claims and surging average settlement costs, which rose by 27% in the first six months of 2025 to US$56mn. Meanwhile, shifting governmental policy in the U.S. and parts of Europe regarding DEI (diversity, equity, inclusion), ESG (environmental, social, governance), and artificial intelligence (AI) have introduced new complexities for boards to navigate.

To read the full Allianz Commercial D&O Insurance Insights report, please visit: Report | Directors and officers (D&O) insurance insights 2026

There's nothing like starting the year off with some good news. Conning's Year-End Life-Annuity forecast for 2025-2027 certainly has a lot of that. For life-annuity industry executives, statutory net operating results, after tax and dividends, are forecast to increase from $27 billion in 2025 to $30 billion in 2027.

Those strong results start with premiums, of course. Due to an increasing number of individuals saving for retirement and pension risk transfers, annuity premiums are projected to increase 16% from 2025 to 2027. Meanwhile, life insurance remains a key financial need for younger generations starting or building their families. As a result, life insurance premiums are forecast to increase 8% from 2025 to 2027.

While premium headlines grab attention, life-annuity insurance executives know profitability depends on successfully managing investment returns, reserves and capital. At the same time, both life and annuity insurers need to begin grappling with the potential impact of GLP-1 drugs on claims and pricing.

Investment performance drives sales and profitability

Life-annuity sales and profitability are sensitive to General Account investment performance. That performance depends on two broad factors: the external rate environment and asset allocation strategy. As we look out to 2027, we see the continuation of a favorable external interest rate environment. We also expect insurers to continue diversifying their asset strategies to achieve higher portfolio yields.

Portfolio yields forecast to increase through 2030

Even if the Federal Reserve cuts rates over the forecast period, we project life-annuity insurers will benefit from higher portfolio yield. Higher portfolio yields support fixed annuity and universal life interest-crediting rates, which are favorable for more sales over our forecast period.

Our portfolio projection uses the moving average ten-year Treasury rate and models three scenarios. The first is based on the third quarter of 2025 Philadelphia Federal Reserve's Survey of Professional Forecasters. The second assumes credit losses reduce the spread over Treasuries achieved in insurer portfolios. The third is an aggregate blend of one and two. By 2027, our aggregate projection is for the portfolio yield to reach 4.22%, up from 4.03% in 2024.

Continued asset diversification supports higher portfolio yields

During the longer-for-lower interest rate period of 2015 through 2021, life and annuity insurers began diversifying their assets to generate higher General Account portfolio yields. They decreased allocations to bonds and redistributed to mortgages and Schedule BA assets (alternative assets such as joint ventures, hedge funds, and private equity investments) to gain yield. In addition, there has been a marked shift within the bond portfolio towards private credit.

Even with the recovery of interest rates, we anticipate that diversification efforts will continue through our forecast period.

Reinsurance Continues to Support Growth

Whether onshore or offshore, reinsurance remains a key reserve and capital management tool for life annuity insurers. For example, in 2024, 21% of direct and assumed premiums were ceded. In 2025 and through 2027, we expect that key role will continue. What will be noticed, however, is the growing use of sidecars to support life-annuity reinsurance transactions.

Since 2019, over 15 new sidecars have formed. Looking ahead, we believe sidecars will continue to bring more capital to support life and annuity reinsurance growth. This is a strong positive for the life and annuity industry's forecast capital strength and profitability through 2027.

GLP-1s Affect Claims and Pricing

When we think about claims through 2027, the good news is that excess mortality has receded from the COVID-19 pandemic peak. At the same time, an increasing number of retirees use annuities to generate retirement income and increase annuity benefits. However, the impact of GLP-1 drugs on mortality, morbidity, and longevity is a new factor we and insurers need to consider. These drugs hold the potential to affect life insurance underwriting as well as life insurance and annuity pricing.

There is a concern that applicants may be using the drugs when underwritten for new policies, but then later stop using the drugs, leading to a return of weight and/or other health conditions the drugs treat. On the annuity side, longevity improvements due to GLP-1 change longevity expectations and strain original annuity pricing assumptions. The current impact of GLP-1 on life-annuity profitability may not be large. That said, these drugs may have a long-term effect on claims and pricing beyond 2027.

A Forecast for Strategic Adaptation

How should life-annuity executives respond to the good news in this forecast? The next three years give insurers a rare alignment of strong earnings, improving yields, new sources of third-party capital, and a return to more normal mortality. The companies that use this period to adapt and realign strategy, instead of simply enjoying favorable conditions, will be the ones that lead the industry in the decade ahead.

To position for continued growth and success, life-annuity insurers should accelerate product innovation. Developing flexible products that can adapt to shifting longevity and morbidity trends will help address emerging customer needs and market dynamics.

At the same time, enhancing the investment strategy remains essential. Continued diversification of the General Account portfolio, with a focus on private credit, mortgages, and alternative assets, will help optimize yields. Partnering with key asset management partners will be crucial to executing successful diversification strategies.

Leveraging reinsurance and third-party capital is another strategic priority. Expanding the use of reinsurance, including innovative structures like sidecars, can help manage capital efficiently and support growth objectives.

Driving operational excellence is crucial for sustainable growth. Investing in technology and analytics can improve underwriting, claims management, and customer engagement, while streamlining operations will enhance efficiency and scalability.

Finally, strengthening regulatory and capital management practices will help companies stay ahead of evolving requirements, maintain robust capital buffers, and support business expansion in a volatile market environment.

By executing on these strategic priorities, life-annuity insurers can capitalize on favorable market conditions, manage emerging risks, and position themselves for sustainable growth through 2027 and beyond.

Elite athletes don't wait for an injury to start strengthening their bodies. They invest in preventative rehab or 'prehab'—the stretching, conditioning, mobility work, and small adjustments that keep them performing at their peak. It's a disciplined commitment to staying strong and ready for what's next.

Independent agencies can approach the year ahead the same way.

Too often, agency leaders slip into rehab mode, discovering a producer's lagging numbers months too late, noticing revenue leakage only after renewals drop, or realizing that their commercial lines pipeline is weak just as growth goals loom. These issues could have been spotted much earlier if the right visibility had been in place.

The agencies that consistently grow and retain clients are the ones that operate with a continuous prehab mindset. They use real-time reporting and analytics to keep a close watch on their business, ensuring everything stays on track and healthy.

As the new year approaches, this kind of clarity becomes one of the most valuable assets an independent agency can have. Here's how analytics can help keep your agency in peak shape for the year ahead:

Daily Performance Visibility Prevents Costly Surprises

Small imbalances like tightness, fatigue, or weakness tend to appear long before a real injury occurs. Athletes rely on these early warning signs to adjust their training to prevent setbacks before they affect performance.

Tracking your agency's key metrics works the same way. Minor shifts like a slipping close ratio or an underperforming line of business can signal larger issues if left unnoticed. By catching them early, you can take corrective action before they seriously affect your agency.

The key is having an agency management system that not only collects and tracks your performance data but also presents it in an intuitive way. Tracking your agency's metrics provides access to dashboards and reports that give a centralized view of its performance, making it easy to act on insights.

Agency analytics tools can help agents track:

• Policies per term, customer, and transaction type
• Revenue per client
• Retention and renewal performance
• Close ratios per producer and line of business
• Book mix, risk concentration, and line diversification

When these numbers become part of your daily routine, presented through dashboards that highlight trends, risks, and opportunities, you gain a truly proactive view of your business. You can easily identify top-performing areas, pinpoint where improvements are needed and ensure team members stay aligned with your agency's goals.

Leverage Your Book of Business to Uncover Growth Opportunities

Just as monitoring agency metrics helps you identify where your agency is excelling and where improvement is needed, it also helps you uncover new opportunities for growth. With consistent metric tracking, your agency management system can help identify cross-sell and upsell opportunities within your existing book of business, such as clients with monoline policies who could benefit from bundled coverage or accounts with underinsured risks that may need additional protection or policy enhancements.

Instead of relying on producers to manually hunt for upsell opportunities, agency management systems can surface prioritized lists of prospects ready for outreach. This empowers your team to act quickly and efficiently, maximizing the value already sitting in your book.

By using the data you already have, the right agency management technology can turn everyday servicing into meaningful growth that strengthens client relationships and boosts revenue and retention.

Shared Insights Align Your Team Around What Matters Most

Athletes perform best when they know the game plan and understand how their role affects the team's success. Similarly, agencies thrive when insights are shared across the entire team.

The key is having a system that lets you build reports once and schedule them to run automatically. You can use these reports in meetings, share summaries with producers, or provide leadership with KPIs.

Agency management systems often allow customization, letting you filter, group, and visualize the metrics that matter most—whether it's top producers, policy types, or conversion rates—without extra steps or manual reformatting. Having this clarity gives your team the insight to adjust tactics in real time, keeping your agency in top shape.

Turning Insights into Everyday Action

Setting your agency up for success next year goes beyond quarterly check-ins. It's about building daily habits that keep your business strong. By taking advantage of real-time insights and analytics technology, your agency can spot opportunities early, avoid surprises, and stay ahead all year long. Because when you know more, you can do more.

KEY TAKEAWAYS:

• The top-down leadership model is losing relevance as future insurance leaders seek collaboration and dynamic career growth
• Emphasizing the industry's purpose-driven mission and community impact helps attract professionals seeking meaningful work
• Affinity insurance, mentorship, and emerging tech roles offer diverse career paths that foster growth and customer engagement in insurance

With the U.S. Bureau of Labor Statistics projecting the loss of nearly 400,000 workers by 2026, the insurance industry is entering a period of significant change. This potential workforce decline underscores the urgent need for insurers to invest in people, culture, and modern career paths that appeal to today's professionals. To attract and retain future insurance leaders, insurers must rethink how they engage talent and structure career development.

Though often seen as traditional and slow to adapt, the industry is actually changing fast. Technology, evolving consumer expectations, and a workforce that values purpose and flexibility are driving this transformation. To bridge the gap between perception and reality, insurance leaders must embrace modern approaches to leadership, career development, and company culture.

To help our industry overcome today's talent challenges, I believe there are four key areas leaders in the industry should focus on.

1. Evolve Leadership Models

The traditional top-down leadership model, where decisions flow from the top, is losing its effectiveness in today's fast-paced environment that emphasizes collaboration and adaptability. Once common, this hierarchical approach no longer aligns with the expectations of younger professionals. According to PwC's 2024 Workforce Radar, this group is seeking environments where their voices are heard, their ideas influence outcomes, and their career paths feel dynamic rather than rigid. They want to be contributors, not just implementers.

Similar research shows that employees who see a bright future at their company are 1.7 times more likely to stay, 2.3 times more engaged, and 2.4 times more likely to recommend their employer. Yet, more than half of Gen Z and Millennial workers hold a negative or neutral view of our industry, often perceiving it as complex and rigid. This growing desire for dynamic workplaces, combined with the industry's negative perception, creates a major challenge in attracting and keeping new talent.

By shifting to collaborative, team-based leadership, we can bring a wider range of perspectives into decision-making, which is crucial for understanding the diversity of today's consumers. Diverse perspectives foster environments where fresh voices enhance market understanding, strengthen decisions, and build greater customer engagement in insurance. This shift also serves as a powerful signal to younger talent that their contributions are not only valued but also essential to our success and future. Collaborative cultures will help forward-thinking insurance leaders appeal to the next generation of talent.

2. Play Up Our Strengths: The Purpose-Driven Core

At its heart, insurance is an industry built on trust and human connection. Our fundamental mission is to help people navigate some of the worst moments of their lives by providing support and financial security. This core mission is a powerful differentiator for attracting talent who seek meaningful, purpose-driven careers.

For many younger professionals, a job is an opportunity to make a tangible, positive impact. Findings from Deloitte suggest that this generation is motivated by a desire to contribute to something bigger than themselves. By highlighting the security and peace of mind we provide for individuals, families, and communities, we show that a career in insurance is deeply meaningful. When corporate culture and leadership embody the industry's thoughtful, service-oriented values, they resonate with employees who want their work to matter and inspire them to bring their best every day.

Emphasizing this core purpose helps attract emerging talent, demonstrating to them that a career in insurance offers meaningful, lasting impact.

3. Highlight Diverse and Emerging Career Paths

While traditional insurance roles like underwriting, claims, and sales remain vital, they're only part of the story. The industry has untapped potential to showcase exciting paths that attract talent seeking innovation, impact, and growth.

Advanced technology, analytics, and digital platforms are redefining the insurance experience from the ground up. New opportunities in AI, cybersecurity, data science, and user experience design open the door to talent that may have once overlooked the industry as a viable career path. By showcasing how these modern disciplines are transforming our industry, we can attract professionals who may have otherwise gravitated toward the tech sector.

Beyond technology, we can highlight unique career paths like those in affinity insurance programs, where professionals work with organizations that reflect their personal interests, such as a university or a professional association. These positions allow individuals to combine their professional skills with their passions, creating highly engaging and fulfilling careers.

Mentorship programs also play a critical role in both recruitment and retention. Mentees gain exposure to cross-functional experiences and broaden their understanding of career possibilities, while mentors gain fresh perspectives on the priorities and aspirations of the next generation. This mutual learning builds stronger connections and encourages long-term engagement.

When insurance leaders effectively highlight diverse career paths and foster mentorship and engagement, emerging talent is more likely to see the industry as a place where they can grow, innovate, and build meaningful careers.

4. Create Genuine Connections

Building and maintaining strong ties with young professionals is essential for long-term success because when employees feel part of a community, they stay engaged and motivated. In addition to nurturing internal relationships, cultivating external networks and partnerships helps new professionals feel welcome, included, and connected to the broader industry community.

Leveraging professional membership organizations is a powerful way to facilitate meaningful connections between young professionals and experienced leaders. These groups provide a vital link between young professionals and experienced leaders, creating opportunities for collaboration and learning. By participating in these networks, new employees can attend special interest groups, join committees, and form relationships that will shape their careers for years to come.

A strong sense of community helps ease the feeling of being an outsider in a new and complex industry. Membership organizations also provide valuable resources and support, especially as we navigate new technologies and evolving market dynamics. In an era defined by change, having a trusted network for shared knowledge and support is more important than ever.

These connections strengthen the industry as a whole. While young professionals gain guidance and insight, established leaders gain access to fresh perspectives and promising talent. Together, these relationships strengthen the industry's future and foster a culture of shared growth and innovation that will help attract, develop, and retain the next generation of insurance leaders.

Shaping the Future of Insurance Careers

The talent gap in the insurance industry is both a challenge and an opportunity shaped by technology, talent trends, and culture. Companies that invest in meaningful connections, diverse career paths, and inclusive environments will not only retain top performers but also build a more engaged workforce. Supporting mentorship and embracing new technologies helps organizations innovate while staying grounded in core industry values. By doing so, they create environments that draw emerging professionals and strengthen the industry for years to come.

How quickly have enterprises across industries embraced AI? The answer depends on your view of its origins. Some people believe AI dates back to Alan Turing's early theories of machine intelligence. Others see the Dartmouth Summer Research Project on AI in 1956 as its birth.

What is unarguable, however, is that AI has moved at breakneck speed since the launch of ChatGPT three years ago. A recent McKinsey survey revealed that 88% of organizations now use AI regularly. Yet there is a downside. Only one-third of respondents have scaled AI enterprise-wide, and fewer than half can tie any significant earnings before interest and taxes (EBIT) to their efforts.

What will it take for insurers to see real ROI from their AI investments? And how can carriers prepare for an agentic AI future? A look at past tech trends can show us quite a bit about what is to come.

Why Every Tech Revolution Stalls Before It Scales

All significant technological breakthroughs of the past 20 to 30 years have followed a distinct progression. First comes the hype, where inflated expectations generate massive excitement and speculation. Next comes normalization, where practical use cases emerge. Lastly, there is substantive change, where technology becomes embedded in core operations, driving genuine business value.

Within each cycle, however, key barriers exist that block progress once the initial hype fades. In the late 1990s, high-speed connectivity was going to reshape business overnight, but ROI did not come until broadband access expanded. Apple's first iPhone launched in 2007 but did not achieve widespread use until its app store and developer ecosystem matured. Cloud computing brought huge promise in the mid-2000s but did not mature fully until operating models shifted toward DevOps, APIs and microservices.

Even insurtech itself went through a metamorphosis. Early disruptors that set out to overturn insurance incumbents about a decade ago have either been acquired or failed to prosper. Those that focused on partnering with incumbents to modernize core parts of the insurance value chain, however, have grown stronger and manifested an industry that drives innovation in insurance forward.

What's Holding AI Back?

There clearly is no shortage of excitement or action when it comes to implementing AI in insurance. Seventy-six percent of insurers already use generative AI in at least one core business function, making insurance the second-fastest industry to AI adoption, trailing only tech, according to BCG research.

Yet true transformation value remains rather elusive. Despite the breakneck speed of adoption, the results of AI pilots are uneven, and progress is patchy. Only 6% of respondents to McKinsey's survey are classified as high performers. That means they set targets beyond efficiency, embedding AI in existing operating models and new products to capture more revenue and expand cross-selling opportunities.

These high performers have already moved beyond generative AI and toward agentic AI, which involves using AI-powered agents to plan and execute multi-step work. Sixty-two percent of McKinsey respondents are already experimenting with agentic AI, and 23% are scaling agents somewhere in the enterprise. Here again, however, penetration is narrow, with agentic deployments living in one or two functions.

So, what's holding insurers back from ROI with generative and agentic AI? One common thread is deployments that are saddled by the limitations of legacy and mainframe systems. Put simply, insurers cannot reach an AI-enabled future if their workflows are dependent upon decades-old technology that is inflexible and impossible to integrate.

Breaking Through the Barrier

To deliver meaningful returns from their AI bets, carriers must rethink the foundations supporting their technology ecosystems. Many of today's challenges stem from years of product-centric digital transformation that delivered incremental wins but left insurers with a patchwork of disconnected systems. These solutions were never designed for the real-time data or observability that AI and agentic AI require.

A platform-centric approach offers a practical path forward. Unlike point solutions that focus on single steps in the value chain, modern platforms provide the connective tissue that allows data, workflows, models and controls to operate together. Platforms succeed because they allow insurers to redesign workflows holistically; something point solutions were never built to support.

The most effective platforms in the coming three to five years will share several attributes.

• Flexible, API-driven architectures that allow carriers to integrate new technologies into existing systems without a costly rip-and-replace.
• A broad ecosystem of partners and integrations, giving carriers access to specialized tools, such as distribution and fraud detection, without adding further fragmentation.
• AI-enablement at the foundation, meaning agents and models can operate safely and consistently across underwriting, claims, servicing, finance and product development.
• Built-in governance and human-in-the-loop patterns that build transparency and trust as insurers ask AI to take on more complex work.
• Outcome dashboards that provide clear metrics, including cycle time, loss adjustment expense, bind ratio, Net Promoter Score, and revenue uplift per use case.

With a platform-centric mindset, insurers can begin building momentum with their existing AI investments and gradually move toward an agentic future. A smart approach is to embed AI agents into crucial workflows where it can consolidate data, reason about actions, and hand off smoothly to humans, such as quote triage in commercial lines or claims final notice of loss (FNOL) to settlement recommendations. Start small, measure the impact, and then implement AI agents into other projects to make adoption stick.

Navigating the Road Ahead

From the dot-com boom to the rise of AI, history shows us reinvention in insurance happens over time, not overnight. AI is moving faster than any wave before it, but the core principles for insurtech companies and carriers alike remain the same: build and implement platforms that solve real business problems and engender trust with customers along the way. This type of measured approach will propel the next generation of AI-powered insurtech platforms and help accelerate the AI adoption cycle.

The latest government shutdown was the longest in U.S. history. For the insurance industry, it was also a stark reminder of the many difficulties homeowners face when getting policies via the National Flood Insurance Program (NFIP).

During shutdowns, funding for this program can face delays that may prove devastating for those who need it most. That sense of unreliability — along with coverage caps, technological limitations and recent cost increases — helps explain why government-funded flood insurance declined by roughly 2% each year between 2020 and 2024, according to one report.

Meanwhile, private flood insurance has boomed, with the total number of policies expanding at a rate of 20% during that same period. By some estimates, private companies now hold as much as 12% of all flood insurance policies.

It's a trend that shows no signs of slowing, especially with the risk of dangerous floods increasing, bringing greater — or in some cases, newly realized — threats to homeowners across the country.

Below, we'll explore what this change means for insurers, including why it's happening, what makes the situation unique and how providers can prepare for the consequences.

Why is private flood insurance on the rise?

Many of the reasons for the private flood insurance boom can be found in the shortcomings of the NFIP, which has provided federally funded coverage for Americans since 1968.

Today, the program is in trouble, with over $22 billion in debt and an inextricable dependence on a Congress that is regularly in strife. While it's too soon to know the full consequences of the most recent government shutdown, it's estimated that over 120,000 home sale transactions were affected due to policy delays (flood insurance is sometimes required by mortgage lenders when properties are in flood-prone areas).

And, frankly, that's far from the worst-case scenario because it only involves delays for those seeking a new policy. What about those who need to file a claim during a shutdown? Those claims are often delayed and can go totally unpaid until the government reopens, if all previously allocated funds run out.

Meanwhile, accepting these risks and the unreliability of NFIP coverage offers policyholders no protection from skyrocketing costs. Thanks to changes in how rates are calculated, NFIP premiums have surged in some parts of the country. NPR highlighted one flood-prone area of Louisiana where costs increased by an average of over 500%.

This particularly hurts new customers, who may move to an area with a high flood risk — or realize their current home is now at an increased risk — and face much higher rates than expected. Plus, longstanding policyholders may have benefited from subsidies that lowered rates in the past, while newcomers get no such relief.

The good news is that the private flood insurance market has grown because it recognizes these issues and is able to bring reliability, flexibility, competitive rates and new features to the landscape. With an estimated 95% of new policyholders now eligible for coverage via a private provider, there are plenty of ways for homeowners to shop around for an option that suits them best.

What are the biggest benefits?

One of the biggest innovations private insurers have made is to create higher coverage limits, provided policyholders are willing to pay for it. Under NFIP, coverage is capped at $250,000 for residential buildings and $100,000 for their contents. These limits were last increased over a decade ago, and don't provide the level of coverage that some homeowners — especially those in high-risk areas — want.

And, perhaps most importantly, private coverage can still offer competitive rates. Research from Neptune Flood Insurance indicates that around 60% of policyholders would pay less in the private market than they would with NFIP.

While those may be the marquee benefits, they're not the only ones. Private insurers are also able to offer better, more efficient and — in the event of another government shutdown — more reliable claims processing than NFIP, bringing all the technology and know-how of the modern digital marketplace.

For many homeowners, this means not just a better customer service experience, but also improved coverage, with providers using advanced analytics and mapping to create bespoke, fairly priced policy plans.

Parametric insurance, which has become quite popular in disaster coverage, is perhaps the best example of this. By designing claims payouts around set trigger points, like water level or rainfall amount, insurers can guarantee that customers will be paid what they deserve quickly, conveniently and transparently.

What hurdles do providers face?

Still, this fledgling industry is not without threats. Price is one, as providers will need to ensure rates that consistently beat out NFIP in order to secure a true market share.

It's true that most people will save money by going the private route but, currently, not everyone will. Of course, as more people purchase private policies, providers will be able to offer lower rates — but this is where a bigger potential problem reveals itself.

Flood insurance, in general, has a visibility issue. Despite the fact that 98% of U.S. counties have been affected by flooding at some point, only 4% of homes are covered.

This has led to billions in uninsured destruction — for example, only 35% of all flood damage from 2010 to 2023 was covered by insurance — with homeowners often realizing too late that their area was at risk.

Here, private insurers will need to do the work of informing a population that is vastly underinsured and increasingly at risk. This will not be an easy process, but it should involve working with mortgage lenders, state governments and other bodies that help determine who needs flood insurance in the first place.

It will also involve educating the public about the risks. In many areas, the risk of flood damage is substantially higher than fire damage, and yet many homeowners are not prepared.

How can the industry adapt?

Flood insurance is a new frontier for private insurers, and as a result, there's a lot to learn from it.

And even in this short time, there are already takeaways for providers of all kinds. One of the most critical lessons is the way private insurers have dissected a preexisting product — in this case, NFIP — and determined what they can improve on. This philosophy will prove essential as the insurance industry faces worsening severe weather, changing customer expectations and rapid technological change.

If providers fail to keep up, they'll be left behind. And this is especially true when it comes to innovations like parametrics, which have a direct relationship to the customer's bottom line. It will become critical to apply these technologies in the right ways, especially as artificial intelligence quickly transforms the business.

So often, the AI conversation in insurance circles centers on cyber risk - how generative AI tools are helping bad actors automate and scale attacks. While this is certainly a concern, there are also a number of less-discussed areas where AI is quietly creating exposures for businesses.

It's a shift that's seeing opportunities to innovate in the insurance market and requiring brokers to adapt quickly.

Where is AI creating exposures for businesses?

In general, the answer to this question falls into two categories: the companies developing AI tools, and the organizations using them, sometimes without even realizing it.

Let's look first at the businesses behind AI innovation and any exposures linked to how their systems are built and trained. Here, intellectual property (IP) infringement remains one of the biggest areas of concern (particularly where training data may include copyrighted or otherwise protected content obtained without explicit permission). Even when sourced from the open web, the ownership and licensing status of data can be ambiguous.

Developers may also face issues with algorithmic bias or discrimination if the training data they use reflects narrow or unrepresentative demographics, as well as reputational and financial damage if their models generate hallucinations, prediction errors, or flawed logic from poor training or model design.

On the other side of this, we have businesses that use AI - whether through generative platforms or via off-the-shelf tools and services that integrate AI functions. Here, we're seeing new professional indemnity (PI) exposures emerging. Using tools such as ChatGPT or image generators to produce media, whether blogs, visuals, or marketing content, could lead to copyright or trademark infringement if outputs reproduce protected material. There's also the risk of generated content containing false or misleading claims, which is a concern across industries, but is particularly sensitive in regulated sectors like finance or healthcare.

Real-life examples

Right now, we're seeing several high-profile disputes and public allegations that highlight how quickly some of these new forms of AI-related IP and consent issues are surfacing.

Their outcomes - whether through courts, settlements, or new regulation - are expected to set important precedents that could reshape how insurers, brokers, and businesses assess and manage technology-related risks, and may ultimately prompt a recalibration of how exposure is understood and priced across the market.

One example is the Lothian Buses voice-clone controversy, where voiceover artist Diane Brooks has publicly alleged her voice was used (via an AI-generated version) without consent. Cases such as this one underline a growing legal uncertainty surrounding AI-generated content, and have fueled calls for stronger legislative protections.

Other disputes, however, such as the U.S./U.K. Getty Images vs Stability AI case - which centers on the use of Getty's photographs (many bearing watermarks) to train Stability's generative AI model, Stable Diffusion, without the required licenses - have already reached the courts.

In November, the U.K. High Court largely ruled in favor of Stability, finding no copyright infringement in the training or outputs of Stable Diffusion (because the AI model did not store or reproduce the works), though it did uphold limited trademark breaches involving Getty's watermarked images.

Although this provides some light on the issue, the litigation as a whole is not fully resolved globally - with the U.S. case still open. It also leaves the broader question unanswered: whether training generative AI models on copyrighted material (without permission) constitutes infringement under U.K. law. This is something the court didn't make a definitive ruling on because the jurisdiction/territorial acts were lacking.

Whatever happens with these cases, it's clear there's work to do in terms of clarifying rules around things like dataset licensing for AI training and transparency of sources. But, from a tech PI perspective, it also highlights several early lessons for businesses, insurers and brokers to take note of going forwards.

What we can learn from continuing legal disputes so far

• For AI tool developers: Put simply, IP due diligence matters more than ever. The Getty vs Stability AI case shows the importance of understanding exactly what data goes into training AI models and the risks of assuming "open web" content is free to use. With this in mind, clear data provenance will likely become an increasingly important part of demonstrating responsible AI practices and mitigating technology PI risk. In addition, considering any cross border exposure - where the AI tool is developed, where it's trained, where the data comes from, who their customers are - will become just as important, as differing legal frameworks could compound liability.
• For organizations adopting or integrating AI: It's not just training data, the AI-generated outputs themselves can create liability, especially if they reproduce copyrighted or trademarked material. So for any firms using AI, strong verification and oversight processes are essential. Companies should have controls in place to confirm that AI-generated content doesn't infringe copyright or trademarks, and that outputs are factually accurate and appropriate for their intended use.
• For insurers: The entire insurance industry is monitoring cases as they unfold. Right now, many are helping businesses safeguard against risks at every stage of the AI lifecycle, with new PI and cyber coverage products emerging for tech companies. But what constitutes infringement in the AI-training context is still not clear, so underwriters and risk managers must assume this is a fast-developing area of exposure and watch it very closely. That being said, this uncertainty also presents an opportunity for the industry: as technology and regulation advance, there is significant scope to innovate through new coverage models or refined underwriting approaches, which is a real positive.
• Brokers: While insurers will always communicate a new or refined product in light of any market changes, I'd advise brokers to talk to insurers to understand their stance on AI-related exposures and stay ahead of emerging developments. And as always, the other lesson is to continue understanding clients' operations - particularly how and where they use AI, even indirectly. If brokers can help their clients recognize the less obvious risks, from content liability to algorithmic bias or model failure, it'll be easier to guide them towards suitable protection as the AI world matures.

Whether you're a business, AI developer, insurer or broker, the bottom line here is that we must all broaden our understanding of AI-related liabilities beyond cybercrime - because AI isn't going away. Its use is accelerating across every industry, and as that happens more and more this year and next, a new layer of risk is emerging that won't be solved by traditional cyber protections alone.

Today, a typical enterprise security team comprises over a dozen specialized functions, such as alert investigation, incident response, threat hunting, vulnerability management, and penetration testing. Even within the application security team, the people doing threat modeling and security assurance are very different from the people doing static application security testing (SAST) and dynamic application security testing (DAST), for example.

As AI agents and assistants increasingly take on the nuts and bolts of many security functions, the role of the security professional transforms into guiding the AI, feeding it the right data and business context, and making more strategic decisions for the business.

In this new world, the most important skill is understanding the shared business context and priorities across the organization, not knowledge of a specific tool or specific alert details. The enterprising employees who do this effectively are the ones who will excel in 2026. They will be positioned to take on any role in the security team, and perhaps all roles at the same time—part-time SOC analyst, part-time AppSec engineer, part-time threat hunter and more. This is because they can simply delegate the domain-specific details to specialized AI agents and assistants.

This is great for CISOs, as they get a highly fungible team of security generalists who can take care of whatever is the top security issue of the day in any domain. Having a single person take care of issues across all domains creates fewer gaps. And it's also great for security team members as it gives them mobility in their careers. It's a win for security across the board. If you're a security generalist, 2026 is your year.

Deepfakes have been a common problem on the Internet pre-2025. In 2025, they entered the workplace, with many incidents of fraud involving adversaries posing as interview candidates or a business partner in a video call.

An orthogonal problem in workplaces has been rogue insiders, employees who hurt their organizations from inside. Sometimes they do this on behalf of an external adversary in return for money, whereas others are lone wolves.

In 2026, these two will converge, with rogue insiders leveraging AI and deepfakes. Employees who have the proclivity to cheat but were previously afraid will be encouraged to cheat, with AI making it easy and deepfakes providing plausible deniability. Any insider has all the business context to customize deepfake attacks to seem much more real than anything we've seen in 2025.

The research on how to detect and defend against deepfakes, as well as techniques to detect and defend against rogue insiders, needs to catch up and tackle this threat effectively. Until it does, there will be a period in 2026 when trust within organizations will be broken. You no longer trust that the email, or the voice call, or even the video call from your teammate is truly from your colleague. During this phase, regular employee training combined with fast adoption of better deployment tools will become critical.

Additionally, the offensive security landscape will change more in the next 24 months than it has in the last 10 years. Traditional pen-testing has remained largely manual and very expensive, while DAST tooling is great at surface-level scanning, weak at context and logic.

In 2026, we'll see new automated approaches to offensive security that understand context, state, and business logic, not just endpoints. Think tools that behave like a creative attacker—chaining vulnerabilities, exploiting misconfigurations, and validating impact the way a human red-teamer would.

That evolution will turn what used to be a quarterly or annual pentest into something continuous and integrated into engineering workflows. Security shifts left to match attacks that are doing the same, into CI/CD, pre-prod validation, and runtime guardrails. Once offensive testing becomes autonomous and contextual, organizations will stop treating pentests as compliance artifacts and start treating them as live safety nets for every software change. 2026 will be the year offensive security becomes just another part of the delivery pipeline.

As AI transforms both security attacks and security tools, this fragmentation hurts agility, restricts scalability, and most importantly creates silos where adversaries hide. We predict this will change in 2026.

AI in insurance has long been discussed in terms of speed and precision; enabling faster underwriting and quicker claims processing, or better risk scoring and fraud detection.

But a new conversation is emerging - one that sees AI not just as a tool for efficiency, speed, or simply automation, but also as a means of creating agility.

It's a shift that couldn't be more timely. The industry is being reshaped by a perfect storm of disruptive forces, all unfolding at once and all demanding faster, more flexible ways of working. Natural disasters have rewritten risk profiles across regions, persistent inflation pressures have pushed carriers to shift focus from premium volume to profitability, and high interest rates have driven withdrawals and non-renewals. Meanwhile, huge advancements in technology and abrupt customer shifts have seen baseline expectations rise even further, especially among the more digitally savvy.

The result is that many agents and carriers struggle to keep up, with traditional legacy systems, compliance processes and slow decision-making cycles slowing them down.

Agility - which, in these terms, is classified as the ability to rapidly scale capacity, instantly apply improvements across an organization, or adapt decision-making in real time to new data - is fast becoming the industry's most valuable currency.

How AI is already bringing agility into insurance

As it stands now, the industry is already seeing early indicators of AI's ability to boost agility where traditional processes are constrained by human resource limitations, training timelines, or system dependencies. Examples include:

• Real-time market adaptation: When carriers shift their risk appetite or market conditions change rapidly, traditional systems rely on API updates or core system changes that can be painfully slow, inconsistent, or lacking in nuance. AI provides remarkable flexibility here - new information from documents, marketing brochures, or support tickets can be ingested directly into the AI engine, enabling immediate updates to underwriting logic and business processes. This means insurers can respond in real time to changing market conditions instead of being constrained by legacy system limitations.
• Strengthening agent-carrier connections: Not only can advanced analytics help agents identify the right carrier fit for their specific needs and risk profiles, but the same technology can work bidirectionally - enabling carriers to identify and connect with agents who align with their business strategies and distribution goals. This approach complements traditional relationship-building with a more strategic, data-driven method.
• Making data analysis easy - and accessible: For agents, AI can make decades of industry data available for easy analysis, helping even new professionals deliver seasoned-level insights to customers. When consulting firm-quality research and analysis is available to decision-makers at every level, complex questions that traditionally took hours or days to resolve can be figured out in minutes.
• Improved speed and operational consistency: AI is known for its speed and consistency, but being able to respond to change in real time enables true agility. For carriers, this extends to claims processing, underwriting, and employee workflow optimization, where AI has demonstrated completion rates that actually exceed human performance while delivering more consistent service across networks.
• Ability to scale capacity overnight: AI eliminates the bottleneck that traditional scaling causes. In phone call management, for example, if a carrier wanted to scale up outreach or avoid missing an influx of incoming queries, they'd need to post job listings, interview, negotiate, hire, onboard, and train - a lengthy process that for entry- to mid-level roles can take anywhere from one to six months before anyone is truly productive. With AI, that capacity can be dialed up overnight.
• Experimentation is far simpler and faster: Easing the process of experimentation allows organizations to respond very quickly to business conditions, needs, and insights. Following on with the phone call management example, traditionally, testing different scripts for handling in- and outbound calls means splitting agents into groups, measuring results, deciding which approach works best, and then retraining people. However, if a new script or approach works better with AI, it can be applied instantly across every interaction, without the slow grind of retraining or overcoming resistance to change.

What AI-driven agility means for the future of insurance

While all of the above is already starting to improve agility across the industry, if we look a bit further down the line, AI's capabilities could have an even bigger impact. It could, for example, act like a virtual sub-agent, capable of finalizing or even binding straightforward policies. A bit like self-service, but with the reassurance that a human agent is still there, making customers feel comfortable while speeding up the process.

It could also affect the traditional quoting experience, such as comparative quoting. In this sense, AI wouldn't just pull APIs and return quotes, deductibles, premiums, and limits - it could also provide deeper insights into the nuances of each coverage. For example, it could draw on customer reviews, past issues, and other relevant data to give a more complete picture. In this way, it could act as a force multiplier, enabling agents to deliver richer, more informed advice to customers. Even a new agent could have decades of experience at their fingertips, helping them provide the same depth of insight as a seasoned professional.

Regardless of which possibility we explore in the future, the main point here is that AI can, and very much should, provide a much quicker, more agile way to respond to change - an ability that's becoming increasingly essential as change itself continues to accelerate across insurance.

The esteemed science-fiction author Arthur C. Clarke believed that "any sufficiently advanced technology is indistinguishable from magic." When it comes to artificial intelligence and its widening effect on the insurance sector, 2026 promises to be a magical year.

In recent years, AI has been tested, examined, admired, and even feared, but not often deployed at scale in the P&C market. That paradigm, I am convinced, will change in the coming months. Look to 2026 as the year when AI progresses from pilot to production across insurance sectors. That's when I expect to see more real-time underwriting, conversational experiences, and dynamic pricing, with many players shifting from the "dipping your toe in the water" phase to the "taking the plunge and swimming confidently" stage. Already, we're seeing underwriting models that can continuously learn, customer interactions that feel like natural conversation, and pricing that adapts to different behavior, context, and risk signals. When I observe how swiftly we've gotten here – I can't help but be bullish on the near future.

The latest numbers buoy my confidence. S&S Insider reports that the worldwide market for artificial intelligence in insurance is set to jump from about $8.6 billion in 2025 to nearly $59.5 billion by 2033. Annual growth rates of approximately 27% suggest an industry quickly implementing AI for claim streamlining, fraud detection, customer service enhancement, and stronger risk management. What's more, early AI adopters are benefiting from cost reductions of 20% to 40% across claims, onboarding, and back office operations, as well as premium growth of up to 15% thanks to improved customer segmentation and more personalized offerings, according to McKinsey data.

AI moves from experimentation to everyday operations

I foresee several transformative trends in 2026 based on advancing technologies and data innovations. One particular breakthrough will come from unifying fragmented data. One of insurance's oldest and stickiest problems has been that policies reside in one system, claims in another, and interactions in a dozen more. But the accelerating push to combine every piece of data into a single intelligent layer that connects all policies, claims, and consumer interactions will pay off this year. Innovations in entity resolution, retrieval-augmented generation, and privacy-safe synthetic data will unlock personalization at scale while safeguarding customers. (It's encouraging that, according to SAS, 79% of carriers are open to using – or are already employing – synthetic data to resolve privacy and data-quality challenges.) Those insurers who check these boxes will win both efficiency and trust from consumers.

I'm also excited about the increasing acceptance of generative AI. Consider that 82% of insurance companies adopting AI are also incorporating GenAI, which demonstrates a rapid progression toward more naturally conversational and content-driven experiences. Additionally, 2026 is poised to be another year of innovation and progress in advanced driver assistance systems (ADAS), which won't necessarily make fully autonomous driving mainstream but could lead to greater clarity involving liability assignments and claims patterns. S&P Global expects that, by 2035, around 40% of new vehicles sold around the world will include advanced driver-assistance features from Level 2-plus to Level 4.

The future belongs to trust builders

What's more, AI is positioned to remove friction from interactions in the coming year, converting what used to be a transaction into a relationship. By analyzing intent, preferences, and behavior in real time, AI-equipped carriers will truly understand – not just price quote – their clients. The companies that stand to benefit most are those that deepen trustworthiness via personalizations that feel effortless and provide real value to the consumer, leading to partnerships that foster long-term loyalty.

Looking ahead, we can also expect insurance technology teams to further evolve. I envision a shift from teams that build isolated services to those that orchestrate intelligent ecosystems. AI systems engineers, data governance leads, and machine learning operations specialists will be among the most indispensable roles. And the best teams won't just be deep technically: they'll blend domain fluency with adaptability, curiosity, and cross-functional collaboration as AI becomes further embedded into every layer of the business.

Obstacles and opportunities

Of course, significant challenges remain. One of the biggest is balancing AI-driven automation with the need for transparency, fairness, responsible governance, and human oversight. After all, automation without transparency erodes trust, and in insurance, trust is the whole ballgame. Although only around 5% of insurers have a fully mature AI governance framework in place right now, Market.US reports that nearly 70% of large enterprises are currently investing in fairness controls, audit trails, and model monitoring. I anticipate that 2026 will be the year when carriers embed explainability into every decision-making model, making "why" as visible as "what." That doesn't mean human oversight will disappear; instead, it will evolve into governance frameworks that ensure fairness, auditability, and consumer confidence.

The new year gives us a lot to look forward to. But it also reminds us that the AI timeline in insurance is unfolding at record speed and is sure to present fresh obstacles and unforeseen X factors that could upset even the most reliable predictions. Still, I've never been as excited about what's beginning to emerge just beyond the horizon.