Although insurance is a data-first business, it has been traditionally tough to quantify the human side of operations: the quality of a claims adjuster's interaction with a policyholder in crisis, the patterns that predict when a top-performing call center agent is about to disengage, the signals that distinguish a renewal conversation that's going well from one that's creating retention risk.

AI is quickly closing this gap. A new generation of AI-powered tools is giving insurance organizations real-time visibility into behaviors that determine outcomes. The carriers moving fastest on this are redesigning how employee experience data flows through the organization and, in doing so, creating a direct line between workforce intelligence and business performance.

The Data Gap in Insurance Operations

A field adjuster handling catastrophe response may conduct 12 to 15 policyholder visits in a single day, and each one can determine whether a customer walks away feeling supported or abandoned. A call center agent in a high-volume property claims environment may handle 80 inbound contacts in a shift, each requiring rapid judgment calls about coverage, tone, and escalation.

Historically, the data generated by those interactions has been gathered by call recordings, satisfaction surveys, and observation/field rides. However, these are challenging to scale and to measure which behaviors drive impact across the workforce.

The tools available today — AI-powered conversation analysis, real-time behavioral signal detection, field mobility platforms, IoT-enabled workspace intelligence — connect not just data, but patterns, behaviors, and activities that can predict and redirect outcomes.

What the Tools Actually Do

The technology stack for frontline workforce intelligence in insurance has matured significantly. There are four primary capture mechanisms now deployed at scale across financial services and insurance operations.

1. Real-Time Conversation Analysis

   Ambient voice AI and natural language processing engines transcribe, classify, and analyze spoken interactions as they happen. These systems go beyond transcription by detecting sentiment in both the employee and the customer, flagging compliance-relevant language, identifying missed resolution opportunities, and surfacing coaching prompts — during the call or conversation.

   A system that detects elevated customer distress during a first notice of loss call can prompt the adjuster with an empathetic acknowledgment script, which can enhance the interaction in real time.

2. Behavioral Signal Detection Beyond Words

   The most advanced conversation AI systems capture language, analyze voice and behavioral signals (think pace, hesitation, tonal shifts, speech rate under stress), and build a real-time picture of both the employee's and customer's emotional trajectory.

   These signals, aggregated across thousands of interactions, also reveal patterns that pure text analyses miss. Which claims generate the most agent stress? Which coverage explanations correlate with downstream complaints? Which interaction profiles predict a renewal at risk? The answers sit in the behavioral data that exist in insurance operations but now can be systematically mined.

3. Field Intelligence for Road-Based Adjusters

   The data capture challenge for field adjusters is fundamentally different from the call center environment. Their day consists of unscripted property assessments, policyholder conversations, and documentation tasks conducted in varying conditions under time pressure.

   Mobile-first field platforms now give adjusters AI-assisted documentation tools. These include photo capture with damage classification, voice-to-text for on-site notes, and real-time coverage guidance based on policy type and loss description. These can reduce administrative burden and improve documentation quality simultaneously. Importantly, they also generate experience data: how long assessments take, where documentation quality varies, which loss types generate the most adjuster rework, and why.

4. Workspace and Interaction Pattern Intelligence

   In fixed-location operations like service centers, claims hubs, and regional offices, occupancy sensors, spatial analytics, and interaction pattern data provide a layer of intelligence that traditional workforce management tools cannot. They identify whether certain workspace configurations are creating service bottlenecks, whether team placement is affecting collaboration patterns, and whether high-performing agents cluster in specific environmental conditions that could be replicated broadly.

   For a carrier managing a large claims service center, this kind of environmental intelligence can surface insights like which team with the highest attrition sits in a zone with the highest ambient noise and the lowest natural light, and which agents who access shared knowledge bases most frequently produce the fewest coverage disputes.

What Better Looks Like For Employee and Customer Experiences

Claims Quality and Cycle Time

When adjusters receive real-time documentation guidance and coverage support in the field, documentation quality improves and rework decreases. With in-the-moment coaching on empathy and resolution framing, first-call resolution rates increase, and post-interaction complaint rates fall.

Agent Development and Retention

The traditional model for developing insurance frontline talent is episodic — via classroom training, annual reviews, and occasional supervisor observation. An agent receiving specific, behavioral, in-context feedback across hundreds of interactions develops faster and retains more than one who receives a quarterly performance review.

Customer Experience Outcomes

The EX-CX link in insurance is not theoretical. Adjusters who are well-supported, well-coached, and experience manageable cognitive load produce different customer interactions than those who are overwhelmed and under-resourced. Employee experience quality is a leading indicator of customer experience quality, not a lagging one.

Reducing Burnout and Retention

The employee experience dimension here is direct. Adjusters consistently report that administrative burden — and not the complexity of the work itself — is the primary driver of burnout. Tools that absorb that burden and do so in a way that improves, rather than complicates, the field workflow produce measurable improvements in adjuster retention and output quality simultaneously.

What Deployment Actually Requires

What determines whether a carrier captures this opportunity is how the implementation is designed.

Three elements separate the deployments that deliver from the ones that stall.

1. Tools must be introduced with clear communication about their purpose. Define specifically what the AI is optimizing for, how data will be used, and what employees can expect from the experience.
2. Managers must be equipped to use the data the tools generate in ways that support development. The most valuable output of an AI workforce intelligence platform is the conversation it enables between a team lead and an agent.
3. Metrics used to evaluate the deployment must include employee experience indicators alongside operational ones. If the only measures of success are call handle time and claims cycle time, the deployment will be optimized for those measures, and the experience improvements that make the gains sustainable will be invisible until attrition numbers force the conversation a year later.

The Window Is Now Open

The tools are available. Technology has been proven in adjacent industries. The workforce data that has been sitting uncaptured in every claims call, every field visit, and every agent interaction for decades is finally capturable at scale — and the infrastructure to turn it into real-time organizational intelligence is no longer experimental.

The question for insurance leaders is not whether this shift is coming. It is whether their organizations will be the ones that shape it.

Paul Carroll

To start us off, what is your overall outlook for the cyber insurance industry?

Liz Kim

If only we could predict where it's going to go, right? I've been in the cyber insurance industry for many years and I've worked across a lot of different roles. I've been in it as a lawyer, as head of claims for a major insurer, in underwriting, in product development, and as a broker. We’re in a soft market now, but, as with all insurance, the cyber market is cyclical.

I think cyber is more cyclical than other lines, for a couple of reasons. First, although there are plenty of disaster scenarios that people talk about in the industry — things like a worldwide AWS outage — we haven't yet really had a true disaster, which would tighten capacity and increase prices. Second, we have new entrants coming into cyber all the time. Because of that constant influx, a lot of their value proposition comes down to nothing more than having the lowest prices. That dynamic drives pricing down more than you'd typically see in other lines of business.

That said, companies that maintain underwriting discipline and pair their insurance with meaningful services or technology solutions to reduce digital risks are better positioned to hold pricing than those that are purely insurance plays.

My overall outlook? It's always positive — because if it wasn't, I wouldn't still be in cyber after all these years. With the kinds of innovations we're seeing across the industry, it's always going to be an area that drives the market forward.

Paul Carroll

How has the cyber threat landscape evolved over the past year or so, particularly with the rise of AI capabilities being leveraged by bad actors?

Liz Kim

The biggest concern I'm hearing right now with respect to AI, in particular, is deepfakes. It's not necessarily a claims-oriented concern in the way ransomware or even extortion is — it's more of an existential threat, which is how most people seem to view it. But deepfakes do connect to insurance, in that some cyber insurers have AI-related exclusions that could potentially leave a deepfake-related claim uncovered. I don't think we've landed on a perfect solution there yet.

We're also seeing a rise in invoice fraud, especially through business email compromise and invoice manipulation. Deepfakes and other trickier social engineering techniques that are leveraging AI certainly make those types of scams even easier to pull off.

Paul Carroll

Tell me a bit more about invoice manipulation, if you would. It’s been around for a while, but I find it interesting that it’s picking up.

Liz Kim

What you see is threat actors creating a fake invoice from a vendor that the insured already does business with. They'll know somehow that you work with that vendor — maybe through social engineering, or maybe they've actually gained access to your systems. From there, they'll send you a fraudulent invoice using one of two main methods.

The first is domain spoofing, where the email domain looks very, very similar to the legitimate one — maybe just a misspelling, or .com versus .ca or .co. They're counting on the recipient not noticing.

The second is BEC, or business email compromise, where the hacker has actually compromised the email account of the other party and is sending invoices directly from it to legitimate contacts.

Either way, there's generally a payment redirection involved — like, "Oh, I've changed my banking information." That's a key red flag. There's no tech hack to prevent this; it's really a process issue. Accounting teams need to have protocols around anything involving a change to payment details. Verify it through a phone call to a known contact using confirmed contact information. And you need to be the one calling them, not the other way around.

You can even see cases where someone on the accounts payable team receives a fake email thread or a WhatsApp message from their CEO or CFO saying, "Pay this invoice."

What makes it convincing is that the thieves have done their homework: they know the CEO is connected to that person professionally on LinkedIn, or they've worked together, or they're tagged in a post. The thieves replicate real, believable scenarios to trick employees.

Junior employees often don't want to question something that looks like it's coming from the CEO. But that's exactly the point: You cannot bypass your internal validation protocols at any level, no matter how legitimate something looks. Because threat actors are trying to trick you.

Paul Carroll

I gather AI is also increasing the volume of cyber threats like phishing. What is the industry doing to counter that?

Liz Kim

Yes, the volume is going up. AI is an enhancement to all of the tactics that bad actors are already using.

A phishing email from three, four, or five years ago is not the same as a phishing email today. Before, there were very obvious markers — the spelling mistakes, the type of email. Nowadays, with advanced social engineering, they can make an email seem so much more legitimate. It's hyper-personalized.

At the same time, the prevention aspects are improving, too. The market is providing more education around building digital resilience and awareness of how phishing scams work: Don't click on things from someone you don't know, and don't click on something you weren't expecting — even from someone you do business with every day.

As an industry, we're not seeing the increase in claims volume that you would expect given the sophistication of AI, and that's because there's much more emphasis on education and prevention.

Paul Carroll

I've been tracking hackers since probably the late 1980s, back when friendly Nigerian princes used to offer me a lot of money. Now I'm at the point where I may report emails as phishing scams that turn out to be legitimate — I'm suspicious of everything these days.

Beyond education, what are you and others in the industry doing to prevent cyber threats from succeeding?

Liz Kim

We have our in-house technology experts — the BOXX Hackbusters team — who are on call 24/7. In addition, each commercial policy is bundled with Cyberboxx Assist, a suite of tools and services designed to help individuals and businesses predict, prevent, and respond to cyber threats. We also offer a virtual CISO [chief information security officer]. These services are focused on the SME space, because many of our insureds don't have any in-house technology expertise, and we can help them bridge that gap.

By offering services like our virtual CISO, it does two things. One, it raises awareness among the management team that cyber risk is a real issue that can impact their organization. Two, it allows our insureds to get expert-level cybersecurity advice. Our vCISO will work with them on a plan — and offer them advice and resources on how to execute it.

In terms of insurance offerings, BOXX introduced a tech E&O policy earlier this year. It has a really strong cyber focus and offers something very specific for technology companies: breach of contract coverage. To get a little lawyerly, the liability that tech companies face isn't a breach of industry standard, which is what you normally have for more traditional professionals like accountants, lawyers, doctors, and so on. Breach of industry standard is the coverage traditional professional errors and omissions insurance provides. But in the technology space, liability is driven by what companies put into their contracts. So the importance of having affirmative coverage for contracts really cannot be overstated when it comes to Tech E&O.

Paul Carroll

There seems to be growing emphasis not just on an organization's own cybersecurity, but on the security of all the vendors and business partners they interact with, because those relationships can serve as entry points for attackers. How is that third-party risk being addressed in the insurance market?

Liz Kim

We can't physically address the security of our insureds' vendors or business partners. So we have to essentially push our insureds to address the security of their own vendors and business partners through education and awareness.

That's critical, because as an industry, we're seeing more claims come in through those third-party relationships than through direct attacks on the insureds themselves.

Paul Carroll

Looking ahead two or three years, where do you think the cyber landscape is headed — and does it ever really change, or is it always going to be that back-and-forth battle between attackers and defenders?

Liz Kim

Even though cyber is an area that changes a lot, it also stays the same in a lot of ways. The role of cyber insurers — especially technology-focused ones like BOXX — is to stay ahead of what the bad guys are doing. That's why things like monitoring the dark web, which is still a relatively new practice for the industry, are so important.

The focus will shift, sure. We've seen it move from ransomware to extortion to business email compromise and invoice manipulation. But ultimately what we're doing remains the same: predicting, preventing, and insuring against negative cyber and technology-related events.

Paul Carroll

Are you seeing much change in the geographic origin of cyber threats? For a while, North Korea, China, and Eastern Europe were significant sources — has that landscape shifted?

Liz Kim

The industry is seeing what appears to be a decrease in volume from Russia and Ukraine, simply because their energies are focused on each other rather than on the rest of the world.

That said, I don't think we're seeing any decrease from the other traditional sources, such as China and North Korea.

Paul Carroll

This has been very helpful. I hope people get the message, especially about the vigilance needed to head off invoice manipulation.

Any final message?

Liz Kim

I’ll just note that I’m excited to have joined BOXX. Just in the few weeks I’ve been here, I’ve found the people to be amazing. The other thing that really drew me to BOXX — and that I've come to appreciate even more since joining — is that we have all the excitement and focus of a startup and we’re channeling that energy into growth after officially becoming a part of Zurich Insurance, a 150-year-old, well-established, and well-respected insurance company.

Paul Carroll

Thanks, Liz.

About Liz Kim

Elizabeth (“Liz”) Kim is the President, US at BOXX Insurance, where she leads the company’s U.S. strategy, operations and market expansion. With nearly 30 years of experience in the insurance industry, she brings deep expertise across underwriting, claims, product development, reinsurance and legal analysis. 

Before joining BOXX, Liz served as a Cyber Reinsurance Broker at Gallagher Re, structuring reinsurance solutions for cyber insurers, InsurTechs, and MGAs. She also held senior leadership roles at Hiscox in underwriting and product development after spending more than a decade as a litigator and claims leader managing complex technology, media, cyber, and professional liability matters. Her broad background gives her a practical, well rounded perspective on emerging risks and the operational needs of insurers and insureds. 

Liz holds a J.D. magna cum laude from Seattle University School of Law, an M.S.W. with honors from California State University Sacramento, and a B.A. in Sociology with a Minor in Women’s Studies from the University of California Davis. She is also committed to mentorship and community service and has volunteered with San Francisco’s Volunteer Legal Services Program, the Asian American Bar Association/Asian Pacific Islander Legal Outreach Pro Bono Clinic, and the ACLU of Washington. Liz also served on the Board of Directors of the Korean American Bar Association of Northern California and continues to serve on the Board of its affiliated Foundation, where she has chaired the Scholarship Committee and mentors law students.[

When people think about a healthy culture in most insurance organizations, they usually say the same things: People follow the process, leaders avoid trouble, and long-tenured employees are promoted. Leaders track metrics like compliance, regrettable attrition and engagement scores to determine success.

But this definition is incomplete because it hides what's beneath the surface: behavioral norms fragmenting across business units and new hires leaving within 18 months because the operating environment is significantly different from what was described during recruitment. The people who stay do so because of inertia, not because the work feels meaningful.

Behavior design matters now more than ever. Cultures built on adherence and compliance are based on a set of rules that are assumed to stay static. But when disruptions occur, the organization is not prepared, and confusion and bad decisions are made.

Culture Redefined as Adherence

In high-compliance industries, culture and process compliance tend to conflate. When regulatory requirements, audit cycles, and procedural accuracy define how work gets evaluated, organizations start measuring culture through proxies like tenure, compliance rates, and survey scores. These operational measures are important, but they describe stability rather than resiliency.

The result is a culture that performs well on paper and fragments in times of instability. This distinction is becoming costly in ways that are hard to ignore. Gallup's 2026 State of the Global Workplace report found that only 20% of employees worldwide are engaged at work (the lowest scores ever), with disengagement costing the global economy an estimated $8.9 trillion annually in lost productivity.

AI Is Making the Problem Visible

When AI shifts what the work actually requires, carriers that have spent years measuring culture through stability metrics cannot answer basic questions: what does good behavior look like to support and sustain change in the organization and the industry overall? How do we sustain and manage our teams through all the changes? How do we ensure confusion isn't jeopardizing team performance?

We need to start moving away from dependence on easy-to-measure metrics, most of which are lagging, and tell us how people worked in the past, during a moment in time. What companies need to start thinking about is how to ensure their teams can learn and adapt to new technologies, new processes, and new requirements. How will their employees learn, develop, and grow in the new AI world? Answering these questions requires the much harder work of defining culture at the behavioral level, specifically enough that people can act on it even when circumstances shift.

Five Steps to Building a Culture That Is Specific Enough to Work

Behaviors don't just change by mandate. They require deep thought into understanding what outcomes the company is looking to create, and then designing the behaviors required to achieve those outcomes. Getting clear and actionable provides transparency and, finally, building recognition and accountability systems around those specific behaviors guides future alignment. Here is how to do it:

Step 1: Get Clear on the Problem and the Desired Outcome

Before naming behaviors, leaders need to name the gap. Is the issue that collaboration is breaking down at the team level? Does accountability diffuse when decisions cross business units? Are new hires not connecting to the real operating and cultural norms fast enough? The behavior work only holds if it is designed to close a specific gap that is clearly articulated. This is where value statements can't hold up.

Step 2: Get Clear on the Dos and Don'ts

Get team members into a room and via digital whiteboard (like Miro or FigJam) or sticky notes, ask them to independently write down:

• Green Behaviors (Dos): Actions you want to see more of (e.g., "turn on cameras during internal video calls," "respond to messages within 24 hours").
• Red Behaviors (Don'ts): Actions to avoid (e.g., "canceling 1-on-1s without 24 hours notice," "speaking over colleagues in meetings").

Step 3: Write a One-Sentence Definition

Condense the list into clear, actionable statements and avoid buzzwords as much as possible. If the definition requires interpretation, it is not finished yet. Build a simple test: read it to someone two levels below you and ask them what they would do Monday morning. If the answer matches what you had in mind, the definition works.

Step 4: Apply the Street Test

The street test asks: Would someone off the street be able to easily recognize the stated behaviors in play? Behaviors are exhibited and reflected in the day-to-day actions of employees. It should be in the feedback of customers or vendors. Behaviors that fail the street test are aspirational language that do not change anything.

Step 5: Model It and Reward It

Defined behaviors only become cultural norms when leaders model them visibly and when the recognition system tells the stories of the people doing them. In insurance, where performance management tends to be tightly tied to technical output metrics, this requires a deliberate decision to build behavioral recognition into performance conversations, team meetings, and promotion criteria. What gets recognized gets repeated.

The Real Competitive Risk

Culture defined as adherence will hold together as long as the rules stay stable. The insurance industry is entering a period where the rules, the work, the tools, and the talent expectations are all shifting simultaneously. Carriers that have not done the behavioral definition work have a structural gap that a survey will not capture.

The organizations that will retain the best people and navigate transformation most effectively will be the ones where culture is specific enough to guide behavior when the process is no longer clear. That requires doing the unglamorous work of naming what good actually looks like, one behavior at a time.

Engagement scores will tell you how people feel today. Behavioral culture design determines how they act tomorrow.

In the past two years, I have sat in on more board-level reviews of AI deployment proposals than in the previous 10 combined. The dollar amounts have gone up, as have the strategic stakes. What has not gone up enough is the quality of the questions board members ask before approving these proposals.

Most board reviews follow a predictable script. Management presents a use case, a vendor, a timeline, and an ROI model. Board members ask about the vendor's track record, the integration risk, and the projected savings. The proposal gets approved or sent back for revisions on the basis of those answers.

Those questions are not wrong. They are insufficient.

Across 20 years of building insurance software and watching deployments succeed or fail, I've seen three other questions matter more for the long-term success of an AI decision-making deployment. Most board members are not asking them yet. The ones who do are the ones whose organizations end up with AI in production rather than stuck in pilot.

Question 1: What is the data foundation we are building this on?

Every AI deployment runs on data the organization already has. The proposal will say so. What the proposal usually does not say is whether that data is in the shape the model needs.

In my experience working with carriers, the data foundation question surfaces three different problems depending on the organization. Sometimes the data exists but is fragmented across systems of record that cannot be reconciled to a single customer or transaction. Sometimes the data is reconciled but tagged inconsistently across business units. Sometimes the data is consistent but does not include the variables the model actually needs to make a defensible decision.

Each of these is a deployment-stopping problem. None of them is visible from the vendor demo. All of them surface in the first 60 days of integration when the model starts producing outputs that the business cannot use.

When my team published research from 20 US insurance leaders earlier this month, data quality and fragmented systems came in as the single biggest blocker to AI deployment. ROI uncertainty came second. Internal IT capacity came third. The order surprised some readers. It did not surprise me.

Board members who ask "what is our data foundation" are not slowing the project. They are giving it a chance to succeed.

Question 2: How do we document an adverse decision?

Most AI deployments at the decision-making layer touch outcomes that affect customers. In insurance, that means claim denials, payout reductions, and coverage decisions. In banking, that means lending denials and credit limit reductions.

For each of those, the regulatory environment in 2026 expects you to be able to document why the AI system reached the decision it did, what input features it considered, what model version was active at the time, and what human review was involved. The expectation is not theoretical. The NAIC Model Bulletin on AI in insurance, adopted in 24 U.S. states as of early 2026, makes this explicit. The EU AI Act makes this explicit. Federal regulators in banking and healthcare are moving the same direction.

In recent research, only three of 14 carriers with AI in production were confident they could produce a complete decision audit trail within five business days if a state regulator asked. The other 11 were less confident. Some far less.

The board question is not whether the AI deployment will be regulated. It will be. The board question is whether the deployment as proposed has the documentation discipline built in, or whether it will require an expensive retrofit when a regulator first asks.

Question 3: Does the AI touch the actual decision?

This is the question most likely to change the structure of the deployment itself.

In my experience, AI deployments succeed faster and create more measurable value when they sit on the edges of a decision-making pipeline rather than at the decision itself. The reasons are operational and regulatory. Capabilities that handle structured but tedious work, such as document interpretation, intake triage, and fraud signal generation, scale faster because the data they consume is more structured, the output they produce is easier to measure, and the regulatory scrutiny they attract is lower.

Capabilities that touch the decision itself, such as reserve recommendation in claims, credit decisioning in lending, and care recommendation in healthcare, scale more slowly. The data is messier. The measurement is harder. The regulatory exposure is higher.

This does not mean decision-making AI is wrong. It means decision-making AI should generally not be the first deployment. The board approving a first AI deployment that sits at the decision itself, before the organization has built the data foundation and the documentation discipline on lower-stakes capabilities, is approving the most complex deployment under the worst conditions.

In that same research, of the 20 U.S. insurance leaders surveyed, just three described their organizations as running AI-assisted decision making. Seventeen still relied on humans for every meaningful decision. The 13 with any AI in production had deployed it on the edges of the pipeline, not at the decision.

A different conversation

When boards ask these three questions, the conversation about an AI deployment changes. The vendor selection becomes secondary. The integration timeline becomes secondary. The ROI model becomes secondary, because all three depend on getting the data foundation, the documentation discipline, and the pipeline position right first.

The boards that ask these questions get more AI deployments into production. The boards that do not ,get more pilots that never move beyond pilot.

For years, insurance agents and brokerages have pursued growth using a familiar model: Add producers, expand carrier relationships, and absorb the operational load through incremental hiring or outsourced support. When pressure builds, they introduce technology to accelerate individual tasks.

That model is now breaking under the burden of the way agencies actually operate.

Across the industry, agencies are losing significant capacity to operational drag. Anywhere from 30%-40% of their time per week is lost to manual, repetitive work such as rekeying data or manually executing analyses – time that should be allocated to revenue-generating activity.

At the same time, such core processes as policy checking, endorsements and data entry can consume more than 20 hours per week per employee, much of it non-differentiated work. The result: Growth is constrained not by demand, but by how the agency runs.

Industry has moved to AI — but not far enough

Insurance is no longer lagging in AI adoption, it is leading. AI adoption in insurance is outpacing most industries and accelerating rapidly. According to market research firm Zipdo, more than 61% of insurers have embedded AI into workflows or are actively piloting it. Additional research from global consulting firm Deloitte notes that 76% are using AI in some form across their operations.

The impact on the insurance industry of using AI is clear. When AI is applied correctly, insurance organizations have found the following results:

• 30%+ productivity gains for operations teams using AI-enabled tools
• 40%-50% reduction in manual workload across key agency tasks
• 30% cost savings through automation in brokerage operations 

For fast-moving insurance organizations, quoting is where service quality and operational efficiency either scale together or break apart. By implement AI technology, agencies have attained up to 55% faster quoting and 50% faster renewals, improving client satisfaction.

Despite widespread adoption, only a small minority of insurers have scaled AI across their full operating model with most deployments remaining siloed or tactical.

Structural problem: Fragmentation

The majority of agencies have not redesigned workflows. Instead, they have layered AI onto disconnected agency management systems. They continue to use siloed workflows across new business, renewals and servicing. In addition, agencies maintain inconsistent data structures and use manual handoffs from department to department. 

The outcome is predictable: Automation improves isolated tasks, but not end-to-end throughput. Agencies find that they have key data somewhere in their system, but the data is missing context across a policy’s lifecycle. Producers find they continue to be constrained by service dependencies, and the agency’s leadership finds it lacks any visibility into real-time operations.

This is why many agencies experience a paradox: more technology, more automation, and yet limited improvement in growth capacity.

What leading agencies do differently

The agencies capturing disproportionate value are not only adopting AI. They are restructuring the way their agency operates. They are building operating models where:

• Data flows seamlessly across the policy lifecycle,
• Work moves across functions with shared context, and
• AI is embedded into workflows, not added on top. 

This shift is where performance begins to compound. By using AI-driven information, producers can find cross-sell and renewal insights that can increase revenue by 20%-30%. Agencies have found that error rates in operations can drop by up to 90% with integrated validation and data workflows. Most importantly, customer engagement and service response times improve materially, driving retention and growth.  

At an industry level, the upside is significant. According to the well-known consulting firm Bain & Company, AI-enabled transformation represents about $100 billion in value for the insurance industry, driven by productivity, growth, and improvements in operational efficiency. 

The Cogneesol perspective: Extending the agency system

This is the shift Cogneesol is focused on enabling.

The agency management system remains the system of record, but it was never designed to coordinate the full intricacy of modern agency operations.

Cogneesol provides an intelligent operational layer that:

• Connects data across systems, workflows, and stakeholders,
• Standardizes and coordinates how work moves across new business, renewals, and servicing,
• Embeds AI at the points of highest operational leverage, and
• Creates a unified, real-time view of agency performance.

This is not incremental optimization. It is structural alignment. When agencies move from fragmented operations to a coordinated system many benefits accrue:

• Producers gain capacity without adding headcount.
• Service teams operate with greater consistency and scale.
• Renewal cycles become more predictable and analytics based.
• Leadership gains actionable visibility across the book. 

Most importantly, the agency transitions from absorbing growth to enabling it.

The bottom line?

The industry has already proven that AI works by reducing costs, accelerating workflows and improving productivity. But those gains plateau quickly when applied to a fragmented operating model.

The next phase of competitive advantage in insurance distribution will not come from deploying more AI tools. It will come from changing the way the agency operates so that intelligence can move across the entire business. That is the difference between simply automating tasks and building an agency that continually improves the way it performs. 

AI is a multiplier, but only if the operating model it sits on is designed to scale it.

About the author

Soumojit Ghosh is Head of Technology Services at Cogneesol.

For more thought leadership from the Cogneesol team, please visit our blog at Cogneesol Blog – For an Ecosystem of Digital Transformation

Sponsored by Cogneesol

While oil prices crested at a bit over $110 a barrel In April, some 65% higher than when President Trump began his second term in January 2025, they came nowhere close to economists' forecasts when it became clear that Iran would close the Strait of Hormuz. They expected prices of $150 to $200 a barrel. Some economists feared we might hit $250. 

That oil prices didn't cause a global economic crisis shows that the world has become more resilient in the face of oil shocks. I remember, as a kid, seeing lines around the corner at gas stations after OPEC imposed an oil embargo in 1973, but we came nowhere close to that this time.

The world will now move to become even more resilient, especially to possible events in the Middle East, given that we've seen that supplies can be curtailed just with some mines, speedboats and drones in the world's major oil thoroughfare. The shift toward a global economy no longer dominated by oil considerations will take many years to play out and won't be complete for decades, if ever, but the change will put the world on a new trajectory with profound changes for every industry, including insurance. 

So it's a good idea to start shifting to a new mindset as soon as possible.

My thinking about a post-oil world traces back to 2010, when I was part of a sort of SWAT team at the Department of Energy distributing tens of billions of dollars to drive innovation and help stimulate the economy as part of the Recovery Act following the Great Recession of 2008-9. The leader of the project, Matt Rogers, was the leader of the oil and gas practice at McKinsey, and he had developed a thesis that was radical, especially for the time. While the conversation among economists was about "peak oil" (when global oil supplies would max out and start to diminish), he calculated that the issue was peak demand (when demand, not supply, would crest).

Matt and Stefan Heck, also a senior partner at McKinsey, developed the peak demand idea much more broadly in their 2013 book "Resource Revolution," which I helped them write. So I was intrigued when a columnist in the Washington Post declared yesterday that: "The 53-year-long oil crisis is now over, leaving the world in a better place.... The black, sticky stuff just doesn’t matter as much as it used to."

The soaring output from fracking in the U.S. over the past two decades did a lot to cushion the oil shock this time around. So did impressive flexibility by China, which reduced its imports by some 4 million barrels a day, to less than 8 million, while barely tapping its oil reserves. In coming years, Venezuela may become a major oil exporter again, and the growth of power from renewable sources will keep surging. The Post column notes: "Renewables account for 47 percent of electricity generation across the European Union and 26 percent in the U.S. The share in America is rising fast, with solar last month overtaking coal in power generation."

The columnist says the end of the oil crisis will have three major consequences, and I think he's mostly right:

"First, the Middle East won’t matter so much anymore.... Next, inflation will be subdued. Oil was a crucial enough input in a wide range of products that it helped determine their prices. The U.S. should now expect a decade or more of the cost of living barely changing from one year to the next. Finally, and most significantly, the global economy will be far more stable. Over the last half-century, soaring oil prices accompanied five major recessions or stock market slumps (1973, 1979, 1990, 2008 and 2022).... Chaos was always just around the corner."

I'm not quite as sanguine as the Washington Post writer is, mostly because I've seen too many long-term assurances get derailed. Remember Francis Fukuyama's 1992 book, "The End of History and the Last Man," which assured us that liberal democracy and free market capitalism represented the final stage of human evolution? Look around today and tell me how that worked out.

I can also see plenty of short-term hurdles. The Trump administration is actually paying companies NOT to develop renewable energy, compensating companies for canceling off-shore wind projects. This administration has also recently announced some $700 million to support coal-burning plants, even though coal is on the way out as a source of electricity. In addition, the Trump White House is trying to halt or even reverse the transition to electric vehicles, even though the shift in strategy has caused U.S. car companies to take tens of billions of dollars in write-offs and will help Chinese companies widen their already considerable global lead on the cars of the future.

But I'm still convinced that the half-century-long oil crisis is, in fact, dissipating. 

The geopolitical implications will extend well beyond the Middle East. Other major oil producers, including Russia, Norway, Mexico and, perhaps, Venezuela. will lose huge amounts of revenue and, thus, influence. The world's largest producer, the U.S., won't be immune. Industries, such as chemicals, that rely on cheap energy prices in the U.S. will also lose out. 

Meanwhile, China should gain influence because of its dominance in the rare earth metals that are needed for batteries, in solar panels and in electric vehicles.

The changes should, in fact, reduce global tensions in some areas, though that doesn't mean that peace is at hand. China's increasing influence could, for instance, embolden it to try to retake Taiwan, which could touch off a geopolitical crisis. 

Insurers will have to tack continually as the geopolitical winds shift, and will have to guide clients wisely as they assess their risks. Insurers will likewise have to adapt as industries evolve — probably including shorter, more local supply lines at least for now, in reaction to the Iran war, and to the rise of isolationist politics, including America First. 

Again, there will be lots of twists and turns. Look at how fast Trump reversed U.S. policy in support of electric vehicles. But I think the move toward a post-oil world — at least one far less vulnerable to oil shocks — is accelerating because of the Iran war, and it's never too early to start reshaping our brains to prepare for such a profound change.

Cheers,

Paul

The World Cup always produces breakout stars. Think of 2018, when the teenaged Kylian Mbappe announced himself to the world by scoring four goals as his French team won the title. So far this year, you might lean toward Folarin Balogun as the possible breakout; he scored twice for the U.S. and looked brilliant as it dominated Paraguay in the opening round. For a team? Perhaps you're partial to Cabo Verde, a country of 500,000 that I confess I did not know existed but that tied mighty Spain, 0-0, on Monday.

For me, the clear breakout star is Freddy. 

The young German has taken social media by storm, growing his follower count on Twitter to 635,000 from the 11,000 he had when he arrived in the U.S. with some friends in early June for a six-week road trip to experience the World Cup. His earnest observations about the U.S. have made him so popular that when he posted that the group was headed to Houston, he arrived to find that former Houston Texas J.J. Watt had paid for a huge room for the group at a posh hotel, and that local businesses had stocked the room with gifts. When Freddy expressed admiration for the music of country music star Ella Langley, she invited the group to meet her backstage after a concert in Oklahoma City. A resort offered to send its plane to pick the group up in Oklahoma City and fly them to Las Vegas for a watch party for a game involving the U.S. men's team. 

There's a reason Freddy has become a sensation, and it suggests something that all businesses, including those in insurance, should do periodically.

An adage attributed to Marshall McLuhan (though with earlier roots) says, "We don't know who discovered water, but it wasn't a fish" — the notion being that anyone immersed in an environment can't understand it the way someone outside that environment can. And Freddy (@FreddyLA7 on Twitter/X) is an outsider providing an unvarnished, unbiased view of America to those of us immersed in it.  

He has shared video of his drive through Alabama and Mississippi and marveled at how beautiful the landscape is — something I certainly missed when I drove through the states on my way from Georgia to Louisiana. Freddy posted a picture of a pile of food at a Taco Bell and called it "the holy land." He wrote: "We were about to walk an hour to the stadium in the rain to save on an Uber, and the receptionist at the hotel we were parked in front of decided to drive us there." Freddy discovered that a Bass Pro Shop had a shooting range inside.

My favorite is a post with two pictures. On the left is a building so big and lit it up it looks like it could be the entrance to an amusement park. On the right is a line of gas pumps stretching way out into the distance. Freddy wrote: "DUDE LMAO THIS IS A GAS STATION." (Someone else said there are 120 pumps and wondered if the travel stop was designed to refuel the U.S. Air Force.)

.           

Freddy then added a photo of the mountain of barbeque he bought inside the Buc-ee's in Texas.

He has surely resonated partly because he's so positive about what he's experiencing in the U.S. Everybody likes to be told they're great. But he still demonstrates the power of outside, objective observation, which is something every company and every individual should solicit as a regular exercise. 

A BCG study I've cited before and will surely cite again found in the early 2000s that 80% of senior executives thought their product was superior to competitors' — and that 8% of customers agreed. Businesses unintentionally erect filters that distort what insiders see, so they have to try extra hard to either remove those filters for themselves or solicit feedback from Freddies who never faced those filters to begin with.

I once interviewed Colin Powell, between his time as the chairman of the Joint Chiefs of Staff and his term as Secretary of State, and he described what I thought was an insightful way to get around the filters. He set up half a dozen phones in his office and gave the number of each phone to a single person whom he trusted to provide a smart, non-DC perspective and reliable, unfiltered information. He told his assistant to never answer any of those phones, to hide the identity of the callers. (I note that the interview was before his time as Secretary of State under President George W. Bush because, after initially resisting the plan to attack Iraq, Powell let himself be sold a bill of goods and made a speech at the United Nations that relied on distorted intelligence to sell the world on the disastrous invasion.)

As I've written before, I think the best way to get unfiltered insight is to experience your company without identifying yourself or to sit with randomly chosen customers as they interact with your company. Make up a persona and call your call center or text it, so you can see what your chatbot actually does. Sit with a relative as they try to decipher the language in the policy you've issued them, without helping. Call people after they've had a claim processed to see just how smoothly your theoretically seamless handoffs from call center and app to adjuster to collision repair shops and rental car companies actually went. And so on.

You surely won't get the sort of joyful feedback Freddy is giving to the U.S., but you'll be able to improve faster than the companies you're up against — and business, like soccer, is a harsh competition.

Cheers, 

Paul

P.S. For those of you who, like me, have been immersed in America so long that the environment feels completely natural, here are a few other observations from visitors for the World Cup:

To start with the negatives, Americans are loud, the U.S. is expensive, and the distances are inconvenient. Traffic is awful. The culture of tipping is baffling. And why are so many items, such as toiletries, locked up in stores?

That said, Ranch dressing seems to be quite a hit. One woman marveled at being able to order a chicken waffle with Ranch dressing and ice cream in an iHOP. Another wrote: "Ranch dressing should be a human right." He added: "The portion sizes are hilarious."

Our grocery store culture has struck a chord, too — the enormity of Walmarts and Costcos, the extraordinary variety of foods offered, and the quality in some of the upscale stores. A Frenchman posted a hilarious screed about how he arrived in the U.S. intending to be a snob but has to admit that the bathrooms in Buc-ee's are nicer than in his apartment. He says, "You could eat the brisket off the floor. It's cleaner than a hospital."

One woman wrote: "I can’t lie… the food in America is ridiculous. Everyone talks about portion sizes, but nobody talks enough about how GOOD everything tastes. Even the ‘quick’ food feels elite compared to what I’m used to in the U.K."

Portion size does come up a lot. One man wrote: "Nobody warned me that American portion sizes are actually a threat to your health. I ordered a medium coffee and received what my country would classify as a bucket."

My favorite, non-Freddy post is a lengthy, almost poetic, one from a Japanese tourist about the biscuits and gravy that a waitress recommended to him at a breakfast counter:

"When the plate arrived, I thought something had gone wrong in the kitchen. I say this with shame. The dish looked like a construction site after rain. Pale mounds. Gray ladle-fall. Speckles I could not identify. In my land, the eye eats first. A meal is arranged like a garden. This meal was arranged like weather.

"I must now formally apologize to the biscuits, the gravy, the waitress, the kitchen and the entire breakfast tradition of the American South. 

"It was magnificent. Warm. Peppered. The biscuit drank the gravy the way a field drinks rain — THAT is why it is shaped like that, you fool — and every mound I had insulted was a soft fold of comfort that my homeland, in 800 years, never once thought to invent."

I'll never look at biscuits and gravy the same way again.

Surging demand for artificial intelligence is reshaping the data center landscape at a remarkable pace. McKinsey projects that companies will invest nearly $7 trillion in data center infrastructure globally by 2030, with more than 40% of that spending concentrated in the U.S.

Much of the near-term opportunity is on the development side, with new construction ranging from ground-up hyperscale builds to core-and-shell projects that will eventually be converted into data centers. Beyond new construction, market activity is also being driven by owners and operators of existing facilities, ranging from colocation providers to large enterprises managing their own infrastructure.

As a class, data centers present property insurance exposures that differ significantly from other commercial risks. Understanding the full scope of exposures and the coverage required to address them is critical to building an insurance program that responds as expected when a loss occurs.

TOP EXPOSURES AND RISKS

While data centers are designed for resiliency, meaningful exposure still exists across every stage — from construction and commissioning to continuing operations — and extends beyond the physical asset itself.

Business interruption and downtime are the primary concerns. These facilities are built for continuous uptime that developers and owners depend on, meaning even a brief outage can generate a significant claim. Location compounds that exposure. Data centers are increasingly being built in areas where severe weather is common, considerably raising the risk for catastrophic losses. Even if a major weather event takes a facility offline temporarily, it can produce revenue losses that far exceed the physical damage. As such, carriers are focusing attention on loss control, engineering standards, business continuity and disaster recovery planning. They want confidence that construction can resume at a development site or that a facility can return to operations quickly after a disruption.

Secondary exposures also complicate the risk picture. These include:

• Power and grid reliability. Power disruptions stemming from grid instability, utility constraints, or insufficient local infrastructure are increasingly common. When operational disruptions occur that don't involve physical damage to the facility, a standard property policy may not respond to losses.
• Community opposition and project approval risk. Public pushback has become a defining obstacle to data center development. Last year saw 25 project cancellations — more than quadruple from 2024 — largely driven by intensifying community opposition across the country. Access to the power grid and water supply are among the most common sticking points, with the potential for municipal resistance to derail projects persisting well into the development process.
• Equipment procurement delays. Waitlists are already common for critical, high-value components that are in short supply. If equipment is damaged, stolen or lost in transit, sourcing replacements can further extend a project.

SPECIALIZED COVERAGE TYPES TO CONSIDER

A standard property policy covering physical damage and business interruption is foundational, but data centers frequently require additional layers to address the range of exposures that fall outside traditional coverage triggers.

Builder's risk coverage addresses the construction phase — a critical window of exposure for data center projects. With contractors, lenders, and third-party operators all at the table, each with their own coverage requirements, structuring a program that satisfies every stakeholder is critical.

Parametric and alternative risk transfer products are increasingly relevant for data centers, particularly when the cause of a financial loss doesn't stem from physical damage. Parametric coverage, captive structures, and self-insurance components can be structured to fill gaps where a standard policy doesn't respond. They can also serve as deductible buy-downs on programs with large retentions as well as supplemental capacity where needed.

Transit, cargo, or stock throughput policies are essential given the value of equipment moving through the supply chain. Millions of dollars in power equipment, servers and GPUs may be in transit, held in interim storage, or staged on-site before a facility is operational. If something goes wrong at any point in that chain, both replacement costs and project delays can escalate quickly.

Environmental insurance is worth considering for new construction, given the scope of ground-up development activity and its potential effect on the surrounding site and community. Contamination, pollution, and construction-related environmental liability are exposures that a standard property policy won't address.

Political risk insurance is particularly relevant for international projects. Geopolitical instability, strikes, riots, and government actions can affect data center operations in ways that generate both physical and financial loss.

WHAT THE CURRENT INSURANCE MARKET MEANS FOR OWNERS AND OPERATORS

The property insurance market is in a soft cycle, with data centers largely seen as a desirable class of business. Some insurers are deploying staggering single-line limits on data center risks, which translates to more options and more competitive terms for owners and operators. This is a welcome stance as many lenders and other sources of capital currently require full value limits of insurance vs. limits set by modeled losses based on probabilities and site attributes.

But questions remain as to whether that dynamic will last. Data centers remain a relatively untested class, and how the market responds when significant losses arrive is still an open question. Owners and operators who use the current environment to structure comprehensive, well-designed programs will be better positioned as conditions evolve.

Paul Carroll

We not only had strong job numbers in the U.S. for May, which would reduce the need for the Fed to cut interest rates, but also had 4.2% annual inflation in the latest report, which would tend to encourage the Fed to keep rates flat or even to raise them. Has your outlook on inflation and economic risks evolved since we last spoke, particularly given what's happening in Iran?

Michel Léonard

You're entirely right. Since we last spoke, I've grown more cautious. 

When the conflict started, nobody expected it to go into a third or fourth month. As a result, we didn't expect the conflict would last long enough for increases in oil and gas disruption to be  transmitted into the price of gas and petrochemicals and as sunk costs throughout the economy. We made the same assessment about the conflict being unlikely to last long enough to significantly alter our P/C replacement forecasts. 

But that transmission is taking place and driving up the price of products key to our replacement costs: construction plastics, PVC, rubber; construction materials; not to mention increases in the cost of transporting all these goods and more. 

That said, I would to share some caution. The price increases we’re already seeing are not solely due to actual price transmission; they're also about the anticipation of transmission. Some companies are pricing up before the higher costs hit them. We saw that during and since COVID. We can’t deny that there is price gouging: Why wait until your margins get compressed? Especially when the wider price narrative in the press and elsewhere is increasing consumer willingness to accept price increases. 

Paul Carroll

What does this mean for P&C insurers next year in terms of replacement costs relative to inflation in the broader economy?

Michel Léonard

Because of the anticipation, I think the trajectory—the pace of increase in inflation, including P/C replacement costs—is above what the underlying supply disruption would warrant. That’s partly because some people have been expecting a bigger disruption than has happened and partly because of gouging by some, who say, "Okay, we can charge a bit more." Right now, the regular CPI and the CPI-core (without energy and food) are increasing in lockstep. What it means is that we should expect P/C replacement costs to increase at the same pace as CPI-core (without energy), at a faster pace than they should given transmission alone, before gouging. 

Paul Carroll

Given the strong jobs report and high inflation, what is your outlook for Fed policy?

Michel Léonard

The Fed has put rates on hold but, in my opinion, still within the wider framework of an easing cycle. The unemployment rate is improving, and though one quarter is not a trend, it’s likely telegraphing to the markets that it the Fed is going from holding rates within an easing cycle, to holding rates between easing and tightening. I would be very surprised if the Fed went directly to telegraphing tightening.

There are a few things to consider here, especially for P/C insurance. Let's put this in context:

The Fed continuing to delay on interest rate cuts, or telegraphing a shift to tightening interest rates, would likely once again reduce homeowners and commercial property insurance’s underlying growth. 

Concerns about inflation, especially if the Fed gets fully on board with shifting to tightening rates, will further accelerate increases in P/C replacement costs – by signaling to producers that they can raise costs ahead of actual price increases. This is before we see more actual transmission from oil prices in to the wider economy.

This is bad news for P/C’s combined ratios – and it could not come at a less opportune time. 

We had COVID inflation and post-COVID inflation that led to carriers working with regulators to implement, in some cases, double-digit or high-single-digit year-over-year increases in premium rates. That's where we came from.

We had finally reached an equilibrium that would justify premium rate increases returning closer to historical averages—low single digits, around 2% to 4% year over year. Now that equilibrium is being challenged.

Now we’re faced with renewed inflation – but instead of doing so in a hard market, we’re doing it as we’re heading into a soft market. Depending on how fast we get there, the impact on combined ratios may be significant.  

Paul Carroll 

What's your assessment of the state of the U.S. economy, given all the stresses?

Michel Léonard

I’m still an optimist and think the U.S. economy remains resilient. Looking at the core drivers of monetary policy and how economists assess the economy —employment, inflation, and growth—let's start with employment. There have been a few months of improvement. If we look at nominal growth, it's healthy. But if we take out inflation from nominal growth, we see the problem. Real GDP is struggling. And inflation is getting worse.

Two out of the three, growth and inflation, are facing headwinds, which I read as the “balance of risks” is still tilting toward the downside. At best, we’re at an equilibrium. I would be wary if the Fed started to talk about raising rates – that would likely worsen the unemployment rate again, accelerate inflation, and bring growth to a halt. In my assessment, such talk would be a significant miscalculation. 

Paul Carroll

Given the enormous amount of geopolitical risk—from the situation in Iran to the Ukraine-Russia conflict to concerns about China and Taiwan—would you point to that risk as a major source of uncertainty that maybe hasn’t been priced into expectations about the economy?

Michel Léonard

Geopolitical risks keep piling up, and, at least for the time being, I would suggest that they aren’t being fully priced across unemployment, growth, and inflation. I did geopolitical risk stress tests 20 years ago about Iran, Taiwan, and war in the Middle East – they all resulted in equity and interest rate corrections much more significant than we are seeing now. Consequently, the tests showed economic performance deteriorating much further than it has now – not to argue that we’re in a good place at this time.  

You asked about what kind of other geopolitical risks are out there that may not have been priced in economic forecasts? A few truly raise alarms for me and not just as an economist: Putin attacking Finland or the Baltic states; China deploying cyber warfare against the U.S. and shutting down transportation, electric cars, or power grids; a new pandemic such as Ebola ,with few of the institutional capabilities we had during COVID; the looming threat of Jan. 6 on the coming midterms in the U.S. 

Paul Carroll

Where do tariffs figure in all this? I certainly have no idea what the tariff regime will look like in six months.

Michel Léonard

Thanks for bringing that back up. The tariff issue hasn’t gone away. There's an economics principle about risk tolerance. For example, folks winning at a casino become more risk-averse and prudent. Folks losing become more risk tolerant and bid more aggressively. With all that's going on in our world right now, folks are actually getting more risk-tolerant, and that's always the problem. 

Paul Carroll

What final words of wisdom would you leave us with?

Michel Léonard

I don't know if it's wisdom. But I would say that, regardless of everything, I remain optimistic. The U.S. consumer is resilient, U.S. companies are resilient. There's a lot of strength there.

For the P/C industry, we’re coming from a good place, even if we’re heading into a soft market. We’ve seen a lot of improvement in the last two years on replacement costs, and more recently we’re seeing better trends for combined ratios. Both provide some protection against the risks ahead of us.

Paul Carroll

Thanks, Michel. I always feel smarter after we talk.

The FBI’s Internet Crime Complaint Center (IC3) just gave the world a $21 billion wake-up call. According to its 2025 report, cybercrime costs reached a record $20.8 billion in losses last year, sounding the alarm bells on the critical need for personal cyber insurance policies that offer proactive risk management.

The FBI IC3’s annual report states that business email compromise (BEC) and financial fraud are the two leading methods of cybercrime. Long considered a corporate network issue, BEC is now the primary way cybercriminals infiltrate enterprises by targeting the personal vulnerabilities of key leaders. At the same time, high-net-worth individuals (HNWIs) are increasingly victims of cyber-enabled fraud, with AI playing a central role in enabling cybercriminals to create deepfake impersonations and realistic phishing emails and texts, thereby lowering the barrier to entry for malicious hackers.

As the adage goes, “an ounce of prevention is worth a pound of cure.” For cyber insurance underwriters and brokers, offering a policy that only covers remuneration for damages after an event is no longer enough. To manage risk effectively for HNWIs and business leaders, insurance must pivot toward a preventive cybersecurity model that stops incidents – and the long-lasting financial and reputational consequences that follow – before they can happen.

Modern Executives and the Expanding Attack Surface

The FBI IC3’s 2025 report findings highlight growing dangers and underscore the rapid expansion of the personal attack surface, fueled in large part by the rise of AI:

• Business email compromise: Scams that compromise business and individual email accounts to conduct unauthorized transfer of funds accounted for 15% of all 2025 losses, totaling slightly more than $3 billion.
• Cyber-enabled fraud: 85% of all losses reported in 2025 were due to cyber-enabled fraudulent activities, including theft of money, data, or identity, or the creation of counterfeit goods or services, totaling $17.7 billion in losses.
• Tech/customer support fraud: In 2025, nearly 48,000 complaints were filed by individuals about cybercriminals posing as technical or customer support/service representatives, resulting in losses totaling $2.1 billion.
• AI-fueled threats: For the first time, the report includes a section on AI-enabled cybercrime and scams, reporting that IC3 received 22,364 complaints in this category, which accounted for over $893 million in losses.

High-profile enterprise executives and high-net-worth individuals are caught in the crosshairs of these attacks. Because they have broad digital footprints, typically own multiple homes with numerous smart devices, and maintain significant public profiles, they are now prime targets of cybercrime. Additionally, it’s a tremendous challenge to maintain privacy in the digital era, with social media and the instant, broad dissemination of information. Events we prefer to keep private can instantly become public knowledge, creating a risk profile that corporate cybersecurity policies typically fail to address.

Personal cyber insurance brokers are ideally suited to help their clients consider how a single personal indiscretion or data leak can have long-term career and reputational impacts. Beyond that, however, they have a professional and ethical responsibility to protect their clients – not just provide reactive cyber coverage.

Making the Case for a Digital Bodyguard

In the modern cyber landscape, fraught with potential exposures and points of vulnerability at every turn, highly vulnerable individuals can benefit from personal cybersecurity protection that fills the gaps left unaddressed by enterprise cybersecurity. By shifting from a reactive cyber policy to a proactive, preventive risk-management offering, insurance brokers and underwriters can provide clients with a “digital bodyguard” to protect them while safeguarding their bottom line. I’m not talking about security software; I’m talking about a preventive capability that protects people and stops incidents from ever causing harm.

The core elements of comprehensive, proactive protection include:

• Minimizing digital footprints: Actively reducing an individual’s "attackable" surface area by minimizing how much information they share online.
• Data broker removal: Scrubbing personal info from the sites that feed cybercriminals.
• Hardening accounts and devices: Moving beyond basic passwords to elite-level security to ensure personal accounts and devices are not vulnerable to malicious access.
• Home network scanning: Continuous monitoring of home networks – the "soft underbelly" of executive security – to detect suspicious activity before it causes harm.
• Training & hygiene: Empowering individuals and their families on appropriate online behaviors, how to spot scams and threats, and continuing ways to minimize their attack surface.
• Incident response: Around-the-clock expert support to respond rapidly when a significant threat is detected.

The reasons for offering this type of personal cybersecurity protection and risk mitigation to corporate and individual clients are a no-brainer: insurance brokers can foster greater trust, improve client retention, and safeguard their clients’ financial posture. Preventing a $1 million breach and the resulting reputational and financial repercussions is far more advantageous than paying out on a claim.

Demand for this type of specialized protection is rapidly growing, as organizations and individuals gain a better understanding of what’s at stake. Insurance underwriters and brokers have a window of opportunity to capitalize on this growth before other trusted advisors step in and bolster their own service offerings.

Don Poster, vice president and senior director - national family office leader of Aon Private Risk Management, states: "Our clients rely on us to preserve both their legacy and their lifestyle. In 2026, you simply cannot protect a client’s wealth, assets, family, and privacy without also protecting their digital identity. We view digital executive protection not as a tech add on, but as a fundamental component of holistic risk protection.”

Diane Delaney, executive director of the Private Risk Management Association (PRMA), agrees. “The PRMA recognizes that the most successful brokers are those who offer more than just an insurance policy safety net. By taking proactive risk management approaches such as integrating digital executive protection, brokers can provide a holistic layer of protection that helps mitigate the reputational and financial fallout that traditional cyber insurance policies are meant to cover,” she said.

Locking Down the Future

Traditional insurance reacts to and repairs damage – in simple terms, it’s like getting a broken arm treated at the hospital. Proactive personal protection prevents the break from happening in the first place. In the modern digital realm, AI-powered threats targeting high-profile, high-net-worth individuals are rampant, and the personal attack surface continues to expand. The unfortunate reality is that corporate defenses often fall short of protecting individuals.

The solution is a proactive "digital bodyguard" approach – the best and most sustainable way to manage and mitigate executive risk, and protect people and corporations from significant, costly attacks and breaches. It’s time for insurance brokers and underwriters to stop viewing personal cyber as a standalone policy and begin offering a comprehensive service to lock down an individual’s digital footprint and safeguard their future.