AI is no longer a futuristic concept. It's here, transforming the insurance industry at an unprecedented pace. AI in traditional insurance jobs is reshaping everything, and if you're not ready, you risk falling behind. The question is clear: How will this shift affect your workforce, and how do you keep your top talent in place during this change?

The Emerging Talent Retention Challenge

Currently, 29% of insurance companies globally are using AI, with many more investing heavily in this technology. High-performing employees are interpreting this as a signal that they need to keep up with rapid changes. They recognize artificial intelligence as a tool to enhance their roles but feel the pressure to adapt quickly, fearing that failure to do so may put their positions at risk.

Premature Departures Among Experienced Professionals

In the U.S., 400,000 insurance professionals are expected to leave the industry soon. This will not only result in an insurance talent shortage but also drive up recruitment and training costs as companies scramble to fill the gap. The relationships and insights these professionals hold are irreplaceable, and their departure will affect operations and service quality long after they leave.

To attract top talent during this transformation, recruitment strategies need to evolve. Here's how:

• Highlight opportunities for growth and leadership in a rapidly changing industry, leveraging AI tools to enhance roles.
• Offer flexibility and autonomy to appeal to the next generation of professionals.
• Position your company as innovative and forward-thinking, embracing new technologies like AI to stay ahead.
• Emphasize the meaningful impact of the work, showing how employees contribute to real-world solutions.
• Tap into diverse industries, bringing in fresh talent with skills that align with the industry's transformation.

The Mid-Career Professional Challenge

For mid-career professionals, the shift to the use of AI isn't just about adapting to new technology; it's about rethinking how careers progress. Traditional advancement pathways are being thrown off track. AI handles the data-heavy tasks that used to define job growth, leaving professionals wondering where to go next. As roles evolve, compensation frameworks must adapt as well.

In the face of augmented roles, compensation must reflect the growing responsibilities of overseeing AI systems rather than sticking to outdated pay structures tied to traditional job functions. If you're not paying attention to this shift, you risk losing valuable talent who feel their growth opportunities are being stunted.

The Reality of AI in Insurance

The line between human oversight and AI-powered tasks is clear. AI in traditional insurance jobs is no longer just automating routine work; it's enhancing it. Roles are evolving: titles stay, but daily responsibilities shift as humans and AI technologies work together to make better decisions. However, the metrics you've relied on to measure success may no longer paint the full picture in this AI-driven environment. Implement performance metrics that assess both the efficiency gains from AI and the critical role of human judgment in complex decisions, ensuring compensation reflects both.

What's Happening to Core Insurance Roles?

• Insurers: AI enhances fraud detection by analyzing patterns and identifying anomalies in claims data, helping insurers detect fraudulent claims more accurately and quickly, reducing financial losses and improving overall risk management.
• Underwriting: Routine risk assessments in underwriting processes are now handled by AI, allowing underwriters to focus on more complex cases that require human judgment.
• Claims Processing: AI takes care of the bulk of routine claims, while human adjusters focus on more specialized cases.
• Actuarial Work: Actuaries are now focused on validating AI models, ensuring they align with market conditions, and providing strategic insights.
• Customer Service: AI automates basic queries, allowing customer service reps to focus on building deeper relationships and enhancing the customer experience through personalized advice.

Implementation Timeline Considerations

Managing the transition to AI doesn't happen overnight. The most successful transitions come from hybrid models where AI and humans collaborate. Phased approaches allow employees to adjust gradually, reducing disruption and ensuring smoother integration. To ensure a smooth transition, create a detailed timeline with clear milestones for each department, starting with back-office operations and gradually integrating client-facing roles while continuously monitoring progress.

New Positions Emerging in AI-Enabled Organizations

As AI continues to shape the insurance industry, it's also creating a new breed of roles:

• Algorithm Oversight Specialists: These professionals ensure that AI-driven decisions are accurate, compliant, and aligned with industry standards.
• AI-Insurance Hybrid Professionals: These roles bridge the gap between technology and domain expertise, overseeing AI systems while ensuring they're applied effectively in day-to-day insurance operations.
• Workflow Optimization Roles: These professionals focus on managing the points where AI and human workers intersect, ensuring smooth collaboration between both.

To keep pace with this transformation, balance retraining existing staff with hiring new talent in AI to ensure growth and performance.

Communication and Workforce Planning Strategies

To successfully manage the AI transition, be transparent about how AI will affect roles and address job security concerns within legal boundaries. Clearly outline reskilling opportunities and your commitment to supporting employees through the transformation. Effectively communicate the changes to maintain stability and performance, ensuring your team feels confident and engaged throughout the process.

Adapting Insurance Jobs for AI and Automation

AI and automation are reshaping the insurance sector, affecting everything from personal lines to business insurance jobs. To retain top talent, it's essential to realign roles and career paths as job functions change. Leveraging AI effectively can drive higher productivity and better decision-making. This shift offers your company a strategic advantage to stay competitive and lead in the evolving market.

For too long, client interaction has largely been confined to the critical junctures of new policies, renewals, and the unfortunate event of a claim. This infrequent contact leaves a vast, untapped potential for fostering deeper relationships and crucially, retaining valuable customers. The challenge for today's broker isn't just about selling policies; it's about becoming an indispensable advisor, a partner in risk management, and a consistent, reassuring presence in their clients' lives.

This article explores groundbreaking strategies and innovative touch points that empower insurance brokers to stay relevant, build lasting connections, and innovate in a fast-moving climate.

Why "Set It and Forget It" No Longer Works

The average policyholder's interaction with their insurance broker can often be summarized as a "set it and forget it" mentality. Once a policy is in place, communication often goes quiet until the next renewal cycle, a question arises, or a life event necessitates a policy change. This silence is not benign; it creates a vacuum that competitors are eager to fill. As Deloitte's 2023 Insurance Industry Outlook highlights, "customer expectations are soaring, driven by experiences with tech giants. Insurers and brokers must evolve from being product providers to trusted advisors offering proactive, personalized service." If brokers aren't actively engaging, clients may perceive their insurance as a commodity, making them susceptible to price shopping and the lure of direct-to-consumer models.

The lack of consistent touch points also means missed opportunities to truly understand evolving client needs. A client's life doesn't stand still for a year; they buy new assets, start businesses, expand families, and face new risks. Without regular, meaningful interaction, brokers are flying blind, unable to offer tailored solutions that truly protect their clients.

Beyond the Renewal: Crafting a Continuous Engagement Strategy

The key to sustained relevance lies in transforming sporadic interactions into a continuous engagement strategy. This isn't about inundating clients with spam, but rather delivering timely, valuable, and personalized information that demonstrates genuine care and expertise.

1. Policy Reviews & Life Event Triggers

Instead of waiting for a renewal notice, brokers can initiate policy reviews based on anticipated life events or general best practices. For instance, a home insurance broker could send an annual reminder to review personal property coverage. This isn't just a transactional ask; it's an opportunity to educate clients on the importance of accurate valuations and the potential pitfalls of being underinsured.

Example Email Touch Point:

Subject: Is Your Home Inventory Up-to-Date? A Quick Check-In

"Hi, [Client Name],

As your home insurance partner, we want to ensure your coverage always aligns with your evolving needs. With the passage of time, it's easy to accumulate new valuables – from electronics to heirlooms – that might not be fully accounted for in your current policy.

We recommend taking a few moments each year to review your personal property coverage. Have you recently made any significant purchases, received gifts, or inherited items of value? Keeping an up-to-date home inventory is crucial for a smooth claims process should the unexpected happen.

For a hassle-free way to manage your inventory, consider using a dedicated home inventory app. It can help you document your belongings with photos and descriptions, making it easier to adjust your coverage as needed and providing vital information if you ever need to file a claim.

If you have any questions or would like to discuss updating your coverage, please don't hesitate to reach out. We're here to help you protect what matters most.

Best regards,

[Your Name/Agency Name]"

2. Hyper-Personalized Content & Educational Newsletters

Generic newsletters are easily ignored. The future of engagement lies in hyper-personalized content. Leveraging client data – policy types, demographics, geographic location – brokers can segment their audience and deliver highly relevant insights.

For auto insurance clients, a newsletter titled "Five Car Modifications That Could Affect Your Insurance Policy" offers practical advice. This not only positions the broker as knowledgeable but also helps clients avoid surprises down the road. For homeowners, content could range from seasonal maintenance tips to understanding flood zone changes.

Example Newsletter Idea: "Protecting Your Ride: Auto Insurance Insights"

● Segment: Auto Insurance Clients

● Content:

• "Performance Upgrades & Your Premium: What to Know"
• "The Rise of ADAS: How Advanced Driver-Assistance Systems Affect Your Coverage"
• "Preparing Your Car for Winter/Summer: Essential Maintenance & Road Trip Tips"
• "Understanding No-Fault vs. At-Fault Accidents: A Quick Guide"

3. Leveraging Weather Events & Local Data

Local weather events offer a potent, timely touch point. A major storm approaching? A property insurance broker can send out proactive tips on securing homes, preparing emergency kits, and understanding what to do if damage occurs. This demonstrates immediate value and care, positioning the broker as a trusted advisor in times of need.

"In the wake of Hurricane Ian, many policyholders realized the crucial role their agents played in guiding them through the claims process," notes Insurance Business America. "Communication before, during, and after a catastrophic event can significantly strengthen client relationships."

4. The AI Advantage: Data-Driven Engagement

Artificial intelligence (AI) is no longer a futuristic concept; it's a powerful tool for enhancing client engagement. Brokers can use AI to:

• Analyze Client Data: Identify patterns in client behavior, policy gaps, or potential needs. AI can flag clients who recently moved, purchased a new vehicle, or had a significant life event, prompting the broker to reach out with relevant policy adjustments.
• Predict Churn Risk: AI algorithms can analyze various data points to identify clients who might be at risk of not renewing. This allows brokers to intervene proactively with targeted retention strategies.
• Automate Personalized Communication: While human touch remains vital, AI can automate the delivery of personalized messages, ensuring timely and consistent communication without overwhelming the broker's workload. Imagine an AI identifying a client's specific interests (e.g., classic cars) and then flagging relevant insurance news or articles for the broker to share.

For example, AI could analyze a client's property records for recent renovations or permit applications, allowing a home insurance broker to proactively suggest a policy review for increased dwelling coverage.

5. Embracing Digital Tools: Beyond Email

While email is effective, brokers should explore a broader suite of digital tools:

• Client Portals: Secure online portals where clients can view policies, make payments, and update information offer convenience and transparency.
• SMS Messaging: For urgent alerts (e.g., weather warnings, policy reminders), SMS can be highly effective, provided clients have opted in.
• Educational Webinars/Videos: Short, informative webinars on topics like "Understanding Your Deductible" or "What to Do After an Accident" can position brokers as thought leaders.
• Home Inventory Apps: Encouraging clients to use home inventory apps is a game-changer. These tools help clients accurately document their belongings, simplifying the claims process and ensuring adequate coverage. A broker can suggest this and similar tools from trusted sources. Tips such as having a detailed home inventory readily available can significantly expedite claim processing and reduce client frustration. You get the idea.

The Human Touch Remains Paramount

While technology provides incredible tools for efficiency and personalization, the fundamental value of an insurance broker remains the human touch. AI can identify opportunities, but it's the broker's empathy, expertise, and ability to build trust that truly cements client relationships. Technology should augment, not replace, this human connection.

Conclusion: The Future Is Personalized and Present

While some of the ideas floated here can be implemented right now, some may require approval or long adoption road-maps, but the take-away here is to start thinking about how and what you could be using to your advantage. To stay relevant and thrive, brokers must embrace a personalized, and consistently present approach to client engagement. 

By leveraging technology for data analysis and communication, while never losing sight of the essential human element, brokers can transform themselves from mere policy providers into indispensable advisors. The future of insurance brokering isn't just about selling policies; it's about building enduring relationships, providing continuous value, and being a constant source of assurance and expertise.

My Indiana Hoosiers (or is it Bison?) are 10-0 and ranked second in the nation. What Coach Curt Cignetti has accomplished in his year-plus in Bloomington is nothing short of remarkable. Coach Cignetti worked under the GOAT, Nick Saban, at Alabama for four seasons, and he cites Coach Saban as his main influence.

I've written about Saban in this column here. Studying both coaches, today I propose a framework we can all use for building teams and winning championships. It's a paradox, but in the age of AI, leadership style and people matter more than ever—so listen up. Here we go.

1. PROCESS OVER OUTCOMES

Don't think about winning championships. Think about what you need to do in this drill, on this play, in this moment. Stop obsessing about quarterly results and execute today's tasks with precision. Think about the eight hours in this day and the 65 business days in this quarter, not the quarter.

2. TRANSFORMATIONAL, NOT TRANSACTIONAL

Saban shifted from transactional to transformational leadership at Michigan State in 1998 against Ohio State when he realized he couldn't win the "transaction" against a superior team. Transformational leadership means you care about other people to help them for their benefit, not your benefit - if it's for your benefit, it's manipulation. Stop managing tasks. Start developing people.

3. CULTURE EATS EVERYTHING

The No. 1 thing is culture, and the culture comes from the individuals who make the team what it is. Mediocre people don't like high achievers; high achievers don't like mediocre people - you can't let those two things coexist. Fire the mediocre. Now.

4. PRODUCTION OVER POTENTIAL

Cignetti's "production over potential" principle means an underperforming five-star has to compete for playing time with a less-talented player who does his job on the field. Stop hiring based on résumés and pedigree. Hire based on what people have actually accomplished.

5. CHANGE THE WAY PEOPLE THINK

Becoming head coach after Indiana posted a dismal 3-9 record in 2023, Cignetti was asked about his biggest challenge and said simply: "Changing the way people think." Your first job isn't strategy - it's breaking the loser mentality.

6. ELIMINATE DECISION FATIGUE

Saban eats two Oatmeal Creme Pies for breakfast every morning and the same salad every day for lunch so he doesn't have to spend a single second debating what he wants. Automate the trivial. Save mental energy for what matters.

7. HIRE TOWARD YOUR WEAKNESS

Saban hired outspoken Lane Kiffin as offensive coordinator—he in many ways is everything Saban is not—because he respected Kiffin's offensive mind. Stop surrounding yourself with yes-men. Hire people who make you uncomfortable because they're better than you at something critical.

8. THE 24-HOUR RULE

Saban allows himself, his team and his coaching staff 24 hours to either enjoy a victory or contemplate a defeat, then they move on to the next goal. Stop celebrating or wallowing. Next play.

9. CONTROL THE NARRATIVE

Saban was a master in handling the media, going on a rant or two every season to divert attention away from one story line and redirect it back to what he believes is important. Cignetti has followed suit. If you're not influencing the story your people believe, you're failing to lead them.

10. AGGRESSIVE CONFIDENCE

When asked what fans should expect, Cignetti said simply: "I win. Google me." National coverage has characterized his public tone and on-field identity as unapologetically aggressive, noting his "attack" ethos and unwillingness to "play nice." Stop hedging. Own your track record.

11. BRING YOUR SYSTEM, NOT THEIRS

Cignetti took the majority of his staff from James Madison and immediately got to work, bringing in 22 transfers. Don't inherit broken culture. Import winning culture.

12. ACCOUNTABILITY IS NON-NEGOTIABLE

Cignetti cites a culture of accountability as critical - the best players don't need coaches barking at them to show up to conditioning on time or study the playbook. If you're micromanaging, you hired wrong.

13. ONE-PLAY-AT-A-TIME MENTALITY

Cignetti's emphasis: "We try to play every play like it's nothing-nothing, game on the line, regardless of the competitive circumstances." His philosophy of fighting human nature keeps his team focused — ignoring outside noise, staying level-headed, and locking in on the next play. Stop thinking about the quarter. Execute this hour, this day.

14. MENTAL TOUGHNESS THROUGH FUNDAMENTALS

One of Indiana's defining characteristics is the way it limits mistakes — Cignetti's emphasis on fundamentals and playing relentlessly but also disciplined has molded a team that doesn't give much away. Discipline isn't punishment. It's freedom through mastery of basics.

15. OBSESSIVE PREPARATION

Recently, Cignetti mentioned UCLA's fake punts in multiple media availabilities during the week, and Special Teams Coordinator Grant Cain made sure players were ready — they stopped a fake on fourth-and-7. Preparation isn't paranoia. It's professional obligation.

16. MODEL RELENTLESS WORK ETHIC

Cignetti: "I put in the hours because I expect my team to do the same. You can't out-talent hard work. Teams win because they outwork the competition." If you're not the hardest worker, you have no credibility if you demand it from others.

17. EVALUATE RUTHLESSLY, CONSTANTLY—AND SHOOT STRAIGHT WITH PLAYERS

Over time, "kind lies" lead to dysfunctional (read: losing) systems; "unkind truths" lead to functional (read: winning) systems. Give true feedback. Deal in truth over feelings. Tell your players it's not criticism, it's coaching — which is what they said they signed up for.

18. ADAPTABILITY WITHIN DISCIPLINE

Cignetti: "You can't win today's game with yesterday's plan. Adjustments are the name of the game. Leadership is about seeing the big picture but knowing when to pivot in the moment." Saban benched starting QB Jalen Hurts at halftime of the national championship game and replaced him with Tua Tagovailoa when the game plan needed it — Hurts' response: "Tua was purpose-built for tonight." Process doesn't mean rigidity. It means disciplined flexibility.

19. RECRUIT FOR FIT, NOT FLASH

Cignetti didn't just sift through the transfer portal — he interviewed players with a purpose, bringing in transfers who were the best players on their previous teams and had played a lot of football. Stop hiring for credentials. Hire for proven performance in your system.

20. CLARITY ELIMINATES CONFUSION

A key element of Saban's process is clearly defined expectations for players not only on the field but also academically and personally, including a dress code, and monitors players year-round. Ambiguity is the enemy of execution.

THE HARD TRUTH

The "process" is easier to define than execute: Execution requires obsessive attention to process, zero tolerance for mediocrity, relentless preparation, and absolute accountability. Winning isn't complicated, but it requires high daily energy, absolute discipline, and zero tolerance for BS.

As automation, APIs, and smart contracts redefine how policies are issued, one of the industry's most enduring artifacts — the binder — may quietly fade into history.

As an underwriter, I've long moved through the familiar insurance life cycle: submission, rating, booking, quote, binder, issuance, renewal, and endorsement.

It's a rhythm every underwriter knows well. But a simple question recently crossed my mind:

What if automation doesn't just reimagine this cycle — but erases one of its oldest steps, the binder?

Why the Binder Might Fade Away

For more than a century, the binder has played a vital role in confirming temporary coverage while the final policy is prepared. It served as a bridge between intent and issuance — a necessary pause in a largely manual, paper-driven process.

But as the industry embraces artificial intelligence, automation, blockchain, and smart contracts, that bridge may no longer be needed.

Today, the binder stage often adds delays, introduces manual errors, and requires repetitive back-and-forth between carriers, brokers, and clients. In a future where risks are assessed, priced, and bound in real time, does this interim step still make sense?

From Temporary Coverage to Instant Issuance

Imagine a world where:

• AI-powered underwriting engines evaluate submissions and generate quotes instantly.
• Blockchain-backed systems securely record client data and policy terms.
• Smart contracts automatically trigger issuance once a quote is accepted.
• Dynamic endorsements adjust coverage midterm when specific parameters are met.

In this model, the policy itself becomes immediate, removing the need for a traditional binder.

Some insurtechs, such as Lemonade and Cover Whale, are already experimenting with real-time issuance and policy management models that compress binding and issuance into one seamless transaction.

Unified Client and Coverage IDs

One innovation that could make this reality possible is a unified client identity system — a blockchain-secured digital ID for every insured individual or entity.

Every coverage, transaction, and claim could be linked to that identity, simplifying servicing, audits, and compliance while dramatically improving fraud detection.

However, for such a framework to work, the industry would need common data standards and regulatory alignment — significant hurdles that will take time and collaboration to overcome.

Still, the payoff could be transformative: a frictionless, verifiable insurance experience from application to claim.

Brokers and Agents: From Issuing Authority to API Authority

This evolution doesn't replace brokers and agents — it redefines their value.

Instead of operating with issuing authority tied to individual carriers, brokers could gain what I call "API authority."

Through standardized application programming interfaces (APIs), they could quote, bind, issue, and manage policies across multiple insurers in a single environment.

Imagine a brokerage platform connected to 10 carriers simultaneously, comparing quotes, binding coverage, and issuing policies in minutes — all through secure APIs.

This shift would make distribution faster, more transparent, and far more client-centric, turning brokers into technology-enabled advisors rather than transactional intermediaries.

Personal AI Agents Managing Coverage

Looking ahead, we may even see AI-powered personal insurance assistants managing coverage on behalf of clients:

• Monitoring lifestyle or business changes
• Suggesting coverage adjustments
• Comparing premiums and initiating claims
• Negotiating renewals through secure APIs

In such a world, these AI agents wouldn't just handle renewals — they could also bind coverage instantly based on verified data streams, removing human latency from the process altogether.

Is the Binder Really Going Away?

Maybe. Or maybe it will evolve into a new digital verification layer embedded within automated issuance systems.

Either way, the binder's traditional purpose — to bridge time and uncertainty — is being challenged by technology that eliminates both.

Whether the binder disappears or evolves into a digital handshake, its transformation will signal something bigger — an industry finally unburdening itself from paper-era pauses to embrace true, data-driven immediacy.

As automation deepens its roots, we should all be asking: What other legacy steps might quietly evolve or fade next?

Between April 1 and April 6, 2025, a storm crossed the south and eastern Midwest of the United States, bringing strong winds, tornadoes and heavy rainfall to a large area ranging from North Dakota to Texas. The most significant damage occurred in Iowa, Missouri, Arkansas, Kentucky, Oklahoma, Tennessee, Indiana and Mississippi. The National Weather Service warned a week beforehand that the storm had the highest possible risk, allowing emergency managers to prepare.

April 2025 storm outbreak

The storm produced over 156 tornadoes, including at least six rated EF3 (i.e. with estimated wind speeds between 136 and 165 mph). It received a score of 96 (classified as "devastating") on the Outbreak Intensity Score, with recorded hail seven centimeters in diameter and straight-line wind speeds of up to 110 mph. Fed by an atmospheric river drawing moisture up from the Gulf of Mexico, over 200mm of rain fell over a wide area, with western Kentucky experiencing nearly 400mm in four days. Widespread surface water flooding and numerous rivers reaching moderate or severe flood stages, with several setting records, caused devastation and power cuts. Kentucky faced the most severe impact, with scores of bridges destroyed and hundreds of roads closed. Mountaintop removal mining in Kentucky is known to have changed the hydrological response of the area during previous floods and likely exacerbated the flooding in this latest event.

Leading up to this storm, Gulf of Mexico sea surface temperatures were 1.2C above average, which helped the atmosphere to hold more moisture and fuel the atmospheric river. Post-event analysis suggests that climate change made the event 40% more likely and 9% more intense.

In Arkansas, the Burlington Northern and Santa Fe Railway restored service just two days after a derailment and bridge washout, demonstrating the benefits of early warnings and good emergency planning. Overall, the storm affected nine million people, resulted in 24 fatalities and inundated more than 15,000 homes and businesses. Insured losses are estimated at $2 billion or more, with economic losses already exceeding $3.5 billion.

The limited scope of flood insurance in America

The Federal Emergency Management Agency (FEMA) established the National Flood Insurance Program (NFIP) in 1968 to provide flood insurance and sponsor flood risk reduction projects. However, since then, climate change, exposure growth and inflation have significantly increased the costs of rebuilding after natural catastrophes. An additional challenge for the NFIP is the low take-up rates outside high-risk coastal counties. In recent years, claims from tropical-cyclone flooding have resulted in NFIP accumulating $20 billion in debt to the U.S. Treasury.

These debts have required several congressional bailouts. While NFIP participation is mandatory for federally backed mortgage holders, it is capped at levels often considered inadequate for flood restoration. As illustrated by 2024's Hurricane Debby, much of the flooding occurs outside FEMA mapped flood areas, where flood insurance uptake remains stubbornly low. In 2021, Risk Rating 2.0 was introduced by FEMA to move the NFIP toward actuarially-sound pricing, with staged increases that will double prices for many policyholders, especially those at high risk.

It is possible to source private insurance, but flood cover is an add-on in most cases. Between 2021 and 2024, private insurance costs rose by 24% on average, with some states experiencing 40%-60% increases.

NFIP penetration rates in the area affected by these floods are among the lowest in the country. Impoverished communities in the U.S. have a disproportionately high flood risk exposure, and insurance affordability is contributing to a widening insurance protection gap.

A common challenge to insurers worldwide

Globally, disaster financing responses are under many of the same pressures. Approaches vary from country to country, with each insurance market using a range of levers to reduce flood exposure. One approach is restricting access to credit or rebuilding aid for those without insurance, thereby providing incentives for or even mandating coverage uptake. Another strategy is balancing public and private involvement, with models ranging from fully government-backed systems to entirely private markets. Some countries require disaster insurance, while others leave it voluntary or have the state cover disaster recovery costs. Additionally, the choice between offering comprehensive (all-risks) versus hazard-specific policies depends on the structure and capacity of national insurance systems. Finally, applying risk-based versus subsidized pricing is a critical consideration, where premiums may reflect actual risk or be offset by cross-subsidies or government support.

For example, in France, carriers are supported by the Compagnie Centrale de Reassurance, a public-sector reinsurer that provides a low-cost reinsurance plan for natural catastrophes and uninsurable risks. Though this service does undermine the private reinsurance market, it has allowed France to achieve penetration rates for natural catastrophe coverage close to 100%.

Under an unusual model in Switzerland, cantonal (provincial) insurers offer all-perils cover; however, they also participate in land use planning and donate significant amounts to measures that reduce risk. Insurers should expect that nation states will commit to effective flood management and land use planning in new and existing developments, while property owners must make their homes more resilient. How this is achieved will vary by country and market. But as losses continue to rise, long-term policies should be reviewed to ensure the most vulnerable are not left behind as climate change increases risk.

It's a common misconception that the "supply chain" only applies to the movement of physical goods. However, the insurance supply chain (which connects reinsurers, carriers, agencies, and customers) is a key example of a non-tangible connection. Through this chain, brokerages, agencies, and carriers all provide customers with competitive products, dependent on each other's expertise and financial capacities.

With this connectivity comes a wealth of opportunities and risks. Insurance firms within the chain that rely on third-party vendors, and those that are increasingly digitizing their operations, put themselves at an increasing threat of cyberattacks.

Risks may vary from firm to firm. However, supply chain attacks in general increased by 431% across two years, indicating now is not the time to assume your firm isn't affected.

How Cyber Risks Emerge in the Global Insurance Supply Chain

Global insurance businesses that digitize their services, including documents and other operations for efficiency and accessibility, are doing so while increasing their cyberattack surfaces. The more third-party software and network devices are rolled out, the more opportunities there are for hackers to target.

Third parties pose an increasing level of risk to operations within global insurance supply chain. Regrettably, as secure as your own networks and processes might be, any lapses in your software or hardware vendors' securities may still put you and your customers at risk. In fact, operational risk from third parties is now a leading concern for companies on most chains.

With modern insurance firms reliant on content management systems, cloud storage and servers, and customer relationship management software solutions, they cannot simply avoid working with third parties.

What's more, cyber risks emerge in the global insurance supply chain when there is variation in security policies and standards between linked firms, and when parties simply neglect to update software versions, hardware, and security processes.

This is all compounded by the fact that hackers see insurance companies as prime targets for ransomware and data theft. The data you possess on customers is not only sensitive but also financially lucrative in the wrong hands. It also provides cybercriminals with a target list of organizations, as well as an understanding of the limits their insurance will cover, any exclusions that may apply, and the terms and timelines of payments. This enables them to focus and customize their efforts on both attack vectors of the victim organization and the amount of funds they can look to extort from the victim organization, maximizing their ability to achieve an ROI on their time and resources.

Common Cybersecurity Vulnerabilities in the Supply Chain

Although cyberattacks are evolving in scope and sophistication (for example, through the proliferation of artificial intelligence), there are still many common vulnerabilities that supply chain insurers can easily monitor and patch, and implementing strategies to address these gaps can further strengthen your defenses.

What's more, in cases where weaknesses may not be so obvious, firms use penetration testing techniques to map out security flaws beneath the surface.

Here are some common vulnerabilities in the supply chain that insurers must keep vigilant for:

• Poor security standards adopted by third-party vendors and partners
• Gaps in security knowledge among internal personnel
• Outdated software, hardware, and firmware
• Shadow IT devices (systems or programs added to networks without approval)
• Misconfigurations and coding errors
• Poor access controls and user permission standards

Of course, the risks facing any specific insurer or agency will vary. However, companies can best prepare themselves (alongside working with a cybersecurity expert) by consulting OWASP's software supply chain security cheat sheet, which breaks down the threat landscape affecting software artifacts and explores potential risk mitigations.

Why Cyber Risks in the Supply Chain Are Business Risks

Cyberattacks are no longer "just problems for IT to worry about." They pose a genuine risk to business operations and customer livelihoods, particularly given the scope and depth they can reach in the current landscape.

Cyber risks in the insurance supply chain could result in innocent firms losing customer data, revenue, and reputation. Even with a robust internal security process, companies may also risk falling foul of compliance violations, leading to heavy fines and further reputational damage.

Any data leaked through European Union vendors, for example, may fall under the scope of the GDPR, where businesses can face fines stretching into the millions.

The "domino effect" of a cyberattack on the insurance supply chain could see multiple vendors (and therefore thousands of customers) at risk of data loss and operational slowdown.

For example, a reinsurer attacked by ransomware, which holds systems to ransom until payment is made to hackers, may freeze operations for other firms dependent on their expertise further down the chain.

Effectively, the right (or indeed wrong) attack could halt the movement of the supply chain for indeterminate amounts of time, causing loss of revenue, loss of business, and customer trust.

Practical Steps to Identify and Reduce Supply Chain Risk

Although there is no way to entirely remove cyberattack risk from the insurance supply chain, there are stringent measures individual business owners can take to protect their interests (and others). For example, they might:

• Draw up an airtight vendor security agreement and carefully vet new partners to mitigate the passing on of risks
• Embed certain cybersecurity controls within supply chain vendor contracts (i.e., to bind new parties to agreeing to security measures)
• Carefully train and refresh employees on cybersecurity standards and appreciation for security hygiene (and insist upon such measures for vendor employees)
• Adopt zero trust principles (i.e., assume no connections, requests, or network additions are safe, and require multi-factor confirmation before releasing access)
• Follow security frameworks such as ISO/IEC 27001 to ensure all bases are covered (without the need for intensive cybersecurity knowledge)
• Create software and hardware updating schedules, and only take on new tools and partnerships if deemed vital by major stakeholders and directors

Of course, it is still prudent to consult cybersecurity professionals for a customized analysis and action plan (as these steps offer a high-level overview of potential actions).

The Role of Governance, Compliance, and Risk Culture

Ultimately, every level of an insurance supply chain firm must take cybersecurity seriously. That means there needs to be oversight and buy-in from the top downwards, with a company culture built around data compliance and on the principles of zero trust.

The best step an insurance firm can take immediately is to start embedding a culture of risk preparation and proactive remediation. This is easily started by taking greater care in vetting new partners, training internal staff, and adopting more stringent access controls.

What's more, there needs to be open communication and collaboration. Regardless of where attacks may stem from in the supply chain, pointing the blame only wastes time and resources even further. Take care of your own cybersecurity, but at the same time, plan to support your partners and others in the chain with accountability, awareness, and proactive measures.

In today's insurance enterprises, data underwrites every decision - from pricing precision and reserving adequacy to regulatory compliance and capital efficiency. Yet even the most data-rich insurers stumble on a deceptively simple question – "which data truly matters most"?

The answer isn't found in a massive catalog or a one-size-fits-all governance policy. It lies in identifying the Critical Data Elements (or CDEs, as we call them) that have a direct measurable impact on the business and managing them with the right level of accountability.

Rethinking Data Criticality

Traditional governance programs treat criticality as an inherent property of the data. Teams document everything, classify exhaustively, and build controls across the board, assuming completeness equals control.

In insurance, however, data criticality is not a technical attribute. It's a business condition. A policy effective date that drives billing cycles or a loss development factor in a statutory filing is far more "critical" than a seldom-used rating variable, even if both sit in the same table. What matters is the business consequence of error, not the data's complexity.

Consider these business impacts when evaluating whether a data element qualifies as critical:

• Does this data feed a regulatory report that could trigger compliance exposure if inaccurate? (E.g.: statutory reserves, regulatory capital ratios)
• Is this data used in investor or board reporting? (e.g.: combined ratio, return on equity, written premium growth)
• Would errors in this data disrupt day-to-day business? (e.g.: claim severity, policy effective dates, producer commissions)
• Is this data used by executives to make key business decisions? (e.g.: pricing optimization inputs, portfolio mix metrics)

Remember, the goal is not to govern everything. It is to govern what drives the business.

Governance Model

Once identified, CDEs need governance proportional to their business scope and risk. A two-tier approach balances enterprise oversight with domain execution:

• Enterprise tier: Cross-domain, regulatory, and board-level CDEs such as statutory reserves, regulatory ratios, and consolidated financials require centralized standards and coordination across the company.
• Domain tier: Business-specific, operational, and analytical CDEs including underwriting metrics, claims KPIs, and pricing model inputs should be managed where business expertise lives.

This tiered structure prevents both under-governance and over-governance. Enterprise CDEs get the control they require, while domain CDEs stay agile and business aligned.

Pragmatic Implementation

This four-phase framework aligns with how leading insurers already deliver data products and analytics.

1. Identify: Begin with your most critical business information deliverables - the reports, dashboards, and metrics essential for operations. Work backward to identify underlying data elements, then apply criticality criteria to determine which qualify as CDEs.
2. Prioritize: Sequence implementation based on risk and organizational priorities. Growth-focused insurers might prioritize decision-making CDEs around pricing and profitability, while member-based mutuals may emphasize operational CDEs supporting policyholder service.
3. Execute: Integrate CDE management into data product sprints, not separate governance projects. CDE implementation, quality check and stewardship activities become backlog items, prioritized alongside other product features.
4. Monitor and Govern: Operationalize the two-tier model with clear ownership and accountability. Enterprise data offices should define standards, quality thresholds, and monitoring frameworks while coordinating cross-domain CDEs. Domain teams manage day-to-day CDE lifecycle, implement quality controls, and provide enterprise reporting on health and performance.

Moving Forward

A well-implemented CDE framework turns governance from a compliance exercise into a business enabler. When governance aligns with value creation, it no longer slows innovation… it amplifies it. For insurers ready to move beyond traditional data governance, focusing on what truly matters - the critical few rather than the comprehensive many -offers a path to both better control and greater agility.

Each winter, the same hazard returns: a sudden freeze that could lead to burst pipes and costly water damage inside homes. And when families are away for winter break or holidays, the damage can be even more disastrous. For insurance professionals, the pattern is predictable, yet preventable. This is the season when agents and brokers can play one of their most valuable roles: guiding homeowners toward practical steps that reduce risk, protect coverage and reinforce the value of good advice.

The Winter Water Problem

Every year, insurers see a surge in water-related claims as temperatures drop. Water damage accounts for over 40% of all winter insurance claims, with frozen pipes being the leading culprit. When water freezes, it expands, creating enough pressure to rupture pipes and release hundreds of gallons in minutes.

The damage extends far beyond what's visible. Burst pipes can ruin drywall, flooring and electrical systems, while residual moisture fosters mold growth that adds weeks to restoration timelines. According to the Insurance Information Institute, water damage — including freezing events — is the second most common cause of home insurance claims annually, representing roughly 22–29% of all reported losses. The average cost per claim exceeds $15,000. Across high-net-worth carriers, that number jumps to $55,000. And those figures spike even more when leaks go undetected.

Why These Losses Persist

Despite widespread awareness, these losses remain stubbornly common. Frozen pipes often occur in overlooked areas — basements, crawl spaces, attics or exterior walls where insulation or heating is limited. Homeowners often underestimate the risk, assuming that newer homes or mild climates offer protection. However, extreme cold events in traditionally temperate regions, such as the Texas freeze of 2021 ("Snowmageddon"), have proven that every property can be vulnerable.

Climate variability is also expanding the risk map. States that rarely faced hard freezes are now experiencing them more often, catching both homeowners and insurers off guard. As the boundaries of winter risk expand, preparedness and the agents who promote it have become essential to preserving insurability.

A Role Redefined: From Policy Seller to Risk Advisor

In today's ever-changing property market, the agent's role is no longer limited to securing coverage; it's about helping clients prevent losses that threaten their eligibility altogether. Homeowners now expect their insurance partners to act as risk advisors, not just intermediaries.

Independent agents and brokers must step up to fill this role. They can help clients understand how simple preventive measures — such as insulating exposed pipes, maintaining indoor heat and shutting off outdoor spigots — reduce the likelihood of catastrophic loss. But beyond basic maintenance, agents can guide homeowners toward the next generation of home protection: automated risk mitigation technologies that stop losses before they start.

Technology as a Line of Defense

Automatic water shutoff valves and smart leak detection systems have become critical tools for modern risk management. These devices continuously monitor water flow and pressure, shutting off the main supply when irregularities suggest a leak or burst pipe.

According to data from LexisNexis, homes equipped with smart shutoff valves experience up to 90% fewer water loss claims. Many insurers now recognize this impact, offering premium credits or underwriting incentives for verified installations. In some regions, particularly California, these devices are even becoming part of recommended mitigation programs or programs that provide incentives, alongside wildfire prevention measures.

However, while technology can dramatically reduce losses, proper installation and verification are key.

When "Protection" Isn't Protected

A growing concern for both homeowners and insurers is improper installation. A smart valve installed incorrectly — too far from the main line without full system integration or missing essential sensors — can fail when it matters most. Worse, it may void any insurance discount or invalidate mitigation credits.

That's where guidance from a knowledgeable agent becomes invaluable. Agents can help clients ensure these systems are installed by licensed, reputable professionals who understand manufacturer specifications and insurer expectations. A properly installed device reduces loss potential and ensures that mitigation efforts are recognized and validated in underwriting.

Agents can further support their clients by recommending that they:

• Keep records of the make, model and installation date for insurer files.
• Confirm that leak sensors are connected to the main supply line.
• Test and service the system annually, just as they would with HVAC or security systems.

When these steps are part of conversations, agents demonstrate their value as proactive partners who connect and ensure their clients are protected against losses year-round, not just at renewal time.

Prevention as a Path to Sustainability

The difficulty many homeowners now face in securing coverage, particularly in high-risk states like California, underscores why prevention must become a priority. The 2025 PRMA Private Client Insurance Insights Survey found that one in five high-net-worth homeowners nationwide have struggled to obtain insurance, rising to nearly one in three in higher-risk states.

Sustainability in the personal lines market will depend on pricing, capacity and prevention. Agents and brokers can help homeowners take that step by:

• Educating them about seasonal risks and new technologies.
• Connecting them with licensed contractors or certified installers for quality assurance.
• Advocating with insurers for recognition of verified mitigation steps in underwriting.
• Integrating risk mitigation discussions into every renewal and coverage review.

Each of these actions strengthens client trust while aligning with the industry's growing emphasis on resilience.

A Season for Leadership

Winter may bring claim volume, but it also brings opportunity for agents and brokers to demonstrate their role as trusted advisors. By helping homeowners take practical steps to prevent frozen pipe failures and leveraging modern technology for continuous protection, they can significantly reduce water losses and improve client outcomes.

This is what the next era of property protection looks like: data-informed prevention, technology-enabled risk management and human expertise guiding both.

The agents who embrace this shift will help shape a more sustainable, resilient insurance market for years to come, ultimately benefiting their clients.

Over the past year, the potential of AI agents has captured the imagination of many enterprises. Projects like AutoGPT and frameworks such as LangChain and CrewAI have enabled AI systems to take autonomous actions: reading and analyzing documents, calling application programming interfaces (APIs), and making decisions on their own. The promise of these models is enticing AI that doesn't just chat but acts.

Insurance and financial services leaders are envisioning the automation of complex tasks, such as handling claims or investigating possible fraud cases using these intelligent agents.

Yet, amid the hype, a new MIT Media Lab report found that, despite $30–40 billion in enterprise AI spending, 95% of organizations have not seen a measurable return on these investments. Only a handful (about 5%) of AI pilots are delivering tangible value, while the rest stall out with no effect on the bottom line. This creates a noticeable gap that separates the few companies gaining value from these agents from those stagnating in experimentation.

Therefore, we must inquire as to the cause of this divide. It's not model quality or lack of enthusiasm, as evidenced by the executives who are eager to adopt AI, resulting in 90% of these executives having seriously explored solutions with these models. The core of the issue is in the approach.

Early enterprise AI efforts struggled with their integration of AI into real value creation workflows, as these efforts were lacking in mechanisms for the AI machine to learn and adapt. According to a recent report published by MIT called the "State of AI in Business 2025," in large organizations, only 5% of custom AI tools ever make it from their early pilot version to production-ready models. The rest never move beyond proofs of concept, often because they remain unable to handle the complexities of real-world cases.

To make real progress in AI, organizations need to rethink their approach: Rather than jumping straight to autonomous agents, they should first master the fundamentals by developing robust AI-powered tools. Simply put, walk before you run.

Cases exist of individual employees already figuring this out. In their "State of AI in Business 2025" survey, MIT researchers found that while only 40% of companies officially bought an LLM subscription, employees at over 90% of firms were using personal AI tools (like ChatGPT or Claude) to speed up their work. These "shadow AI" users succeeded by leveraging focused tools (e.g. drafting emails, summarizing texts) that deliver quick wins.

Enterprises can learn from this pattern. By deploying a portfolio of narrow and reliable AI tools that augment specific tasks, organizations set the foundation for bigger agent-driven transformations. It's a phased approach to AI maturity, one that is proving far more effective than leaping straight into "autonomous everything" without significant groundwork.

Agents or Tools First?

To understand why developing specialized tools comes first, it helps to demystify and better understand how AI agent frameworks work. An agent works as a decision-making engine (often a large language model) that can perform a series of reasoning steps toward a goal. Crucially, these agents aren't all-powerful on their own, they rely on tools to take actions in the world outside the AI's own mind. A tool, on the other hand, is an external function or API that the agent can invoke. For example, an insurance-focused agent might have tools for retrieving a customer's policy data, running a fraud check, or sending an email. The agent's job is to figure out which tools to use, in what sequence, to accomplish a complex task.

In practical terms, agent frameworks implement a loop often described as "think, act, observe". The AI agent "thinks" (meaning that it generates a reasoning step in natural language), decides to invoke a tool with some inputs, then "observes" the tool's output and incorporates it into the next reasoning cycle. This continues until the agent arrives at a final answer or action.

An agent is like a sophisticated orchestrator or problem-solver, and tools are the discrete capabilities it can leverage (query a database, call an API, run a calculation, etc.). The agent chooses and sequences tools to achieve an objective. This means that the agent is only as powerful as the tools given allow it to be. If the tools are weak, unreliable, or non-existent for a needed function, the agent will inevitably stumble. This is why building a robust toolset is a necessary and important step in the foundation of an agent.

For instance, imagine asking an AI agent to "Process this new claim and flag any anomalies." The agent might first use a document parsing tool to extract key fields, then call a knowledge base search tool to compare details with past claims, then use a calculation tool to compute risk scores, and so on – reasoning at each step about what to do next. The framework (LangChain, CrewAI, etc.) provides the orchestration that ties these steps together and manages intermediate states (so that, say, the result of step 1 can be fed into step 2). It also manages the agent's memory, which in this context means the information the agent retains as it moves through the sequence. Memory could include the conversation history or results from prior tool calls, allowing the agent to maintain context over multiple turns.

Not every task calls for an agent. Some are better handled by sharp, single-purpose tools. An AI tool might be something as simple as a document summarizer, a language translation function, or an email classification model – narrow in scope but high in accuracy.

Tools can be deployed directly into workflows (for example, auto summarizing each incoming claim report). In contrast, an AI agent tackles open-ended tasks that involve multiple decisions or tool uses (for example, handling an entire claims adjustment process). Trying to skip straight to agents without a base of proven tools is a recipe for frustration.

For enterprise leaders, the takeaway should be clear: Tools are the building blocks of any agentic system. If you want an AI agent to reliably execute a multi-step process, you must first invest in those individual steps as standalone competencies. Think of it like training an employee – you wouldn't expect a new hire to handle an entire claims process on day one without first ensuring they know how to do each component task (review documents, check databases, draft responses). Equipping an AI agent is similar; you need to furnish it with dependable mini-skills and data access (the tools) and then give it the autonomy to string them together.

Just as you wouldn't deploy a piece of software to production without testing each module, you shouldn't deploy an autonomous AI agent without first proving out the individual tool actions, data connections, and guardrails. Tools are an important foundation in the building of AI agents, and any individual or company that wishes to use AI agents in their workflow or systems should prioritize developing strong tools.