In an evolving healthcare ecosystem, insurance companies are uniquely positioned to lead innovation and influence the adoption of technology-driven care models. Among the most transformative advancements in recent years are telemedicine and remote patient monitoring (RPM). These solutions are not just short-term responses to healthcare access challenges, they are enduring strategies that can enhance care quality, reduce costs, and improve patient engagement. For insurance companies, particularly those managing Medicare Advantage plans, the question is no longer if telemedicine and RPM should be prioritized, but instead how quickly and effectively they can be scaled.

Telemedicine: Expanding Access While Controlling Costs

Telemedicine refers to the use of electronic communications and software to provide clinical services to patients without an in-person visit. This includes video consultations, telephone appointments, and asynchronous (store-and-forward) communication.

For payers, the value proposition of telemedicine lies in cost avoidance, member satisfaction, and access to care. Studies consistently show that virtual visits are more cost-effective than emergency room or urgent care visits for non-emergency conditions. Moreover, they help insurers engage hard-to-reach populations, including rural residents and mobility-challenged seniors.

A Medicare Agent from Medicare Agents Hub outlines how strongly Medicare Advantage plays a role here, "if you're living in a rural area, a Medicare advantage plan may offer you more options for telehealth that you would otherwise not have access to if you were simply on original Medicare and Medigap."

Insurance executives should view telemedicine as a lever to support value-based care models. By enabling more frequent touchpoints with providers, plans can manage chronic conditions, reduce hospital readmissions, and identify gaps in care.

Remote Patient Monitoring: Continuous Care Beyond the Clinic

Remote patient monitoring (RPM) involves the use of connected devices—such as blood pressure cuffs, glucose monitors, and wearable sensors—that transmit health data from the patient's home to clinicians in real time. RPM is particularly valuable in the management of chronic diseases like diabetes, hypertension, heart failure, and COPD.

For insurers, RPM translates into real-time insight into member health, early intervention, and better utilization management. Instead of reactive care driven by acute events, plans can support predictive care models where risks are flagged before they escalate. This not only enhances patient outcomes but also reduces the need for high-cost interventions such as ER visits and hospitalizations.

Medicare Advantage: A Catalyst for Adoption

The Centers for Medicare & Medicaid Services (CMS) has played a pivotal role in legitimizing and providing incentives for telemedicine and RPM. Medicare Advantage (MA) plans, in particular, are at the forefront of this transformation due to their flexibility in offering supplemental benefits and their emphasis on care coordination.

Since 2020, CMS has allowed MA plans to offer telehealth services as part of their basic benefit structure. This includes virtual primary care, behavioral health services, and even specialty consultations. The CHRONIC Care Act and other CMS regulatory updates have further enabled the use of remote monitoring for chronic disease management, providing reimbursement pathways for services that were previously out-of-pocket expenses.

Moreover, under Medicare Advantage, plans can use telehealth to meet network adequacy requirements in underserved areas. This creates an opportunity to expand provider networks without significant investment in brick-and-mortar infrastructure.

Strategic Considerations for Insurance Executives

1. Align Telehealth With Risk Adjustment and Quality Metrics:

Telemedicine and RPM generate valuable data that can support HEDIS measures, Star Ratings, and risk adjustment coding. Executives should ensure interoperability with electronic health records and build data analytics strategies to capture and leverage this information effectively.

2. Invest in Member Education and Technology Access:

Even with broad reimbursement support, telehealth and RPM adoption hinges on member trust and usability. Executives should consider programs that provide devices, offer digital literacy training, or partner with community organizations to bridge the digital divide.

3. Strengthen Provider and Agent Partnerships:

Providing incentives to providers and agents to adopt telehealth and RPM requires more than reimbursement, it requires workflow integration and clinical alignment. Collaborative models that offer training, shared savings, and decision-support tools will accelerate participation.

4. Embrace Hybrid Care Models:

Rather than replacing in-person care, telehealth and RPM should be integrated into a hybrid model that blends virtual and physical interactions. This ensures continuity of care and supports patient preference.

Looking Ahead: A Competitive Differentiator

As CMS continues to encourage digital innovation and as consumer expectations evolve, telemedicine and remote monitoring will become table stakes for insurance companies, not differentiators. The window of competitive advantage is narrowing. Insurance executives who invest now in infrastructure, partnerships, and member engagement strategies will not only improve outcomes and control costs, they will position their organizations as leaders in the next generation of care delivery.

For Medicare Advantage plans, in particular, this represents a unique opportunity to leverage regulatory flexibility to pilot, scale, and refine technology-enabled care solutions. The imperative is clear: Telemedicine and remote monitoring are not optional, they are foundational pillars of a modern, resilient, and member-centered insurance model.

Today's unconventional solopreneur may be tomorrow's regional success story — that's why we need more inclusive underwriting.

Insurance is a safety net many take for granted—until they realize they've been excluded from it.

For countless small businesses across the U.S., securing coverage isn't just a bureaucratic hurdle. Instead, it's a barrier to entry. Without insurance, a budding business can't bid on contracts, rent space, or even get off the ground. Yet, many are shut out because their business models don't fit neatly into a traditional underwriting box.

As an industry, we have a duty and an opportunity to do better.

Having spent much of my career in insurance product development and underwriting, I've seen the mechanics of risk evaluation up close. I've also seen how legacy approaches can leave unconventional businesses out in the cold. From part-time side hustles to gig-driven enterprises, the insurance industry often struggles to keep pace with the changing nature of entrepreneurship. This is where innovation and inclusivity must intersect.

We're often likely to insure individuals' passions that happen to develop into businesses. For instance, we insured a young man's lawn mowing business that evolved into a thriving business. He started the business before even entering high school, and most insurance carriers would have rejected him for not having enough years of experience. If we had relied on conventional underwriting rules that required three-plus years of experience to get a policy, we would have extinguished his passion before it even began.

At Simply Business, we encounter entrepreneurs every day who have been turned away by traditional channels—not because they're high risk, but because they're misunderstood.

Microbusinesses, particularly those owned by first-time founders or individuals in non-traditional trades, often face either excessive premiums or complete exclusion, with 20-30% of small businesses struggling to obtain insurance. In fact, nearly one-third of uninsured business owners in one of our recent surveys reported relying on Google or peers for insurance recommendations because they've been unable to access professional guidance or fair pricing.

That's not a sustainable future for our industry—or our economy. Small businesses generate 44% of U.S. economic activity. If we're not willing to protect them, we're failing to protect the very foundation of American enterprise.

Meeting Customers Where They Are

Expanding access starts with rethinking how we define risk. A thoughtful underwriter doesn't immediately reject a policy because it's unfamiliar. They look deeper. Our insurance carriers have stepped up to cover everything from pet waste removal professionals to holiday light installers—trades most carriers wouldn't bother pricing. But by leveraging digital platforms and informed risk frameworks, we've been able to meet these customers where they are—and help them get to where they're going.

Technology plays a key role here. Digital buying experiences can offer clarity, transparency, and ease to entrepreneurs navigating insurance for the first time. Much like the shift from paper tax forms to TurboTax, online insurance tools demystify an opaque system. But digital tools alone aren't enough—we must also rewire our risk models to accommodate the range of business owners knocking on our doors.

I remember speaking with a sweet tea vendor—formerly an airline mechanic—who traveled from fair to fair trying to grow her new business. She couldn't find anyone willing to insure her, and this prevented her from selling at the local food festival. She wasn't asking for a handout. She just wanted a chance to build the business that was her passion. And that's what insurance is really about: giving people the opportunity to achieve their dreams.

If we want to remain relevant and responsible stewards of risk, insurers must reevaluate how we define insurability. We must develop products that flex to fit emerging business models, not the other way around. This isn't charity—it's smart, future-focused business.

Now is the time to take a hard look at our models and expectations. Are we broadening our understanding of risk? Are we designing products that reflect the real world of entrepreneurship today? If not—why not? The businesses we overlook today are the ones that will define tomorrow.

Let's build an industry that makes room for all of them.

AI is reshaping insurance with high-resolution modeling that allows for more tailored, risk-appropriate solutions—even in high-risk geographies.

Climate change is no longer a future threat—it's a present-day crisis. Across the globe, extreme weather events tell a devastating story of this new reality. In the U.S. alone, more than 52,477 wildfires burned through 8.4 million acres of land, while 27 climate disasters each caused more than $1 billion in damages in 2024.

This pattern of destruction isn't isolated—from bushfires in Australia to floods in Europe and typhoons in Asia, communities worldwide are feeling the impact, with 2024 data showing that 97% of all insured losses stemmed from weather-related catastrophes. And with NASA reporting an uptick in carbon dioxide, global temperature and methane levels (and that 2024 was the warmest year on record) it's no surprise insurance companies are becoming increasingly concerned about protecting their policyholders and preserving their own business legacies.

As traditional approaches prove inadequate in the face of this escalating crisis, the insurance industry finds itself at a crossroads. So how can insurers move forward when traditional risk assessment models lag behind the changing climate reality?

The Rising Challenge: Market Retreat Amid Climate Volatility

As climate risk becomes more localized and unpredictable, certain regions are being deemed "uninsurable," even if they were previously profitable, causing an insurance exodus that leads to lost revenue, erodes trust in the industry and leaves vulnerable communities without coverage. In some cases, brokers can no longer offer relevant products, and customers are left underinsured or uninsured, with no one to turn to.

Without the right tools to assess and visualize climate impacts, insurers can struggle with inaccurate premium pricing and coverage gaps, inefficient underwriting with elevated exposure risk, overburdened claims operations during extreme events, delayed disaster response and customer dissatisfaction.

Artificial Intelligence is bringing clarity to what was once chaos and helping insurance enterprises respond to climate events—and more adequately prepare for them, with speed, accuracy and foresight.

How AI Is Transforming Climate Risk Management

AI isn't just a tool—it's a game-changer. Advanced climate risk modeling solutions marry cutting-edge AI, climate science and insurtech excellence to provide an accurate classification of extreme weather events using adaptive models to enhance response with early warning systems, hazard monitoring and data-driven insights for insurance enterprises. When combined with geospatial intelligence, environmental data simulation technology, continuous portfolio risk assessment and dynamic price adjustments based on evolving risks, AI is helping the insurance industry move from reactive to proactive decision-making across the entire insurance value chain.

Post-event recovery can be the most chaotic phase of all. AI simplifies and speeds this process with automated damage detection via satellite or drone imagery. AI-powered fraud detection during claim reviews easily prioritizes claims based on real-time impact modeling and can assist with resource prioritization and allocation. The result? Faster claims processing, reduced fraud, and improved customer experience.

Who Benefits From AI in Climate Risk Modeling?

The adoption of AI-powered climate risk solutions doesn't just enhance operations—it delivers tangible benefits across the insurance ecosystem, from insurers to brokers to the policyholder.

Insurers see smarter risk segmentation for more targeted products, faster claims handling and reduced fraud, and the ability to re-enter high-risk or previously uninsurable markets with data-backed confidence.

Brokers are finding enhanced risk insight, which helps them provide more personalized advisory services, confidence in offering relevant products in vulnerable geographies, and stronger client relationships through value-driven engagement.

Policyholders are seeing clearer, more transparent coverage terms and more affordable, tailored coverage—even in risk-prone areas. AI also provides them peace of mind with real-time risk alerts and better, faster claims support.

The Powerful Way Forward

The climate is changing faster than traditional insurance models can adapt. But AI-driven climate risk modeling offers a powerful way forward. This isn't just about better data—it's about redefining how insurance enterprises anticipate, adapt to and respond to risk. With artificial intelligence in insurance, we are building a more resilient, responsive future—one where technology empowers the insurance industry, and their policyholders, to thrive in the face of climate uncertainty.

As an independent agent, you're no stranger to juggling multiple tasks—client meetings, policy management, and everything else that comes with running your business. With so many responsibilities competing for your time, it's easy to miss opportunities for growth—and that's exactly where AI can help.

Adopting new technology might sound daunting, but it doesn't have to begin with hunting down the "perfect" AI tool. It starts with identifying the specific challenges your agency faces and exploring how AI can directly solve them—so you can work smarter, close more deals, and ultimately, sell more.

Here are three key areas where AI can help you take better control of your agency's operations.

1. Streamline client renewals

In today's fast-paced insurance market, staying connected with your clients is more crucial than ever. They're not just looking for general updates—they expect personalized communication that speaks to their specific needs.

One of the most important opportunities for client engagement is when a policy is up for renewal. According to the Independent Insurance Agents of Dallas, it costs seven to nine times more to attract a new customer than to retain an existing one—making client retention a crucial part of any agency's growth strategy.

Managing dozens (or even hundreds) of clients, each with different policies and renewal dates, can feel like a lot to handle. The good news is that AI-driven renewal technology can automatically track your clients' policy expiration dates, ensuring that no renewals slip through the cracks. It can also retrieve remarketed rates automatically, allowing you to offer your clients better options before they start looking elsewhere or let their policies lapse.

This not only boosts client retention but also saves you hours spent manually researching and switching between carrier sites to find alternative options. To save even more time, some AMS platforms include AI-powered email assistants. With just a simple prompt, these tools help you quickly generate professional, personalized emails. You can choose the tone and set the length, making it easy to reach out to clients about renewals and clearly explain any relevant policy changes. The result is a faster, more consistent renewal process that keeps your clients informed, your agency running smoothly, and your sales pipeline steady.

2. Turn data into revenue

In today's rapidly evolving insurance industry, you can't afford to rely on outdated, manually compiled spreadsheets for critical decision-making. These traditional methods are not only time-consuming and prone to human error, they also limit your ability to stay ahead. Spreadsheets provide static snapshots, not the real-time insights you need to make strategic decisions.

To stay competitive, agents need to adopt modern agency management platforms that deliver real-time performance insights. These systems leverage AI and analytics to generate intuitive reports, offering a comprehensive snapshot of your agency's overall health. With everything in one place, you can easily track key metrics across areas like accounting, sales pipeline, and revenue. In fact, a report by Collibra found that data-centric businesses are 58% more likely to exceed their revenue goals—highlighting the value of using data to drive smarter decisions.

A great solution will also provide access to industry benchmark data, offering valuable context on how your agency compares with peers within the same category. Insights such as premium and policies per customer, customer longevity, and the personal-to-commercial business split can reveal whether you're performing above or below the industry average. By understanding where your agency excels and where there's room for improvement, you can focus your efforts on the areas that drive the most revenue—helping you close more deals and grow your business strategically.

3. Boost campaign performance in real time

Promoting your services can feel overwhelming—especially when it's not always clear where to start or how well your marketing efforts are paying off. However, crafting the right message is key to connecting more deeply with your audience and building long-term loyalty. That's where AI-powered marketing tools, built into today's agency management systems, can really help.

These tools take the guesswork out of marketing by giving you the ability to track and fine-tune your campaigns in real time. You can quickly run reports on completed campaigns to see which messages are resonating and which formats are driving the most engagement, helping you streamline your communication strategy.

But what does this mean for your agency? A/B testing gives you the insights to understand what truly resonates with your audience—whether it's subject lines, content, or design. By running campaign reports to analyze the performance of different variations, you can move beyond guesswork and refine your messaging to boost results. When your content aligns with what your audience wants, you're not just improving engagement—you're also increasing conversions and driving more sales.

Ready to embrace AI in your agency?

Now that you've seen what AI can do, it's time to take the next step. Think about the areas in your agency where AI could really make a difference, whether that's renewals, driving revenue, or improving marketing. Look into the solutions that match your goals and begin integrating them into your workflow. By embracing AI, you'll stay competitive and drive growth for your agency in ways you might not have imagined.

A boss of mine once observed that he'd benefited repeatedly through his life and career because he was born just a few years before the Baby Boom began in the U.S. after World War II. He applied for college when there was little competition and went to Penn, then had no trouble finding a good job. He bought a house and moved to a lush suburb before the horde of Boomers had the inclination or the money. He developed enough management experience that, when the Boomers did flood into the work force, he moved into supervisory roles that eventually took him to the top of a large consulting firm. 

His experience came to mind as I read through Capgemini’s World P&C Insurance Report 2025, which makes a compelling case about how global demographic shifts are going to require major changes in insurance over the next 25 years and beyond. The report states:

"These shifts are... a call to redesign how risk is assessed, products are structured, and portfolios are shaped."

The winners will be those insurers that, like my old boss, are a few years ahead of the pack. After my cross-country move last week, I'm still digging through boxes trying to find silverware, bath towels and other items I've long taken for granted, so I'll be brief, but here is what stands out for me in the coming tidal wave of demographic shifts:

The summary for Capgemini’s report says:

1. "Aging and urbanization are concentrating risk, requiring new underwriting and pricing models
2. Ownership is evolving, pushing insurers toward flexible, modular coverage.
3. Customers want proactive protection, not just payouts — ecosystem partnerships are key."

To me, the key predictions for aging and urbanization that have to be accounted for are:

• "By 2050, for every 100 working-age people, there will be 26 seniors to support, up from 16 today — a 63% increase. And in most regions outside of Africa, the imbalance intensifies, approaching nearly one dependent for every three workers."
• "Nearly 70% of the global population will live in cities by 2050, concentrating people, and the risks they carry, into denser, more complex environments.

For the shifting definition of property and value, the key point is:

"People are delaying — or forgoing — buying homes, and when they do, they often choose smaller, more urban spaces.... 45% of consumers plan to increase spending on experiences like travel and leisure rather than accumulating goods or property.... 70% say they don’t plan to change their housing situation, reinforcing the trend toward more flexible, less asset-heavy lifestyles.

In terms of the desire for protection, the key points are the need for:

• Enhanced safety and security – Aging individuals, particularly those living alone, need real-time protection....
• Reduced complexity – Older consumers often prefer simple, predictable coverage that reduces cognitive burden.
• Service-integrated protection – Insurance can’t just reimburse; it must assist. As insurers integrate with service providers, policies can evolve into holistic solutions: home maintenance, health checks, ergonomic evaluations and more....
• Support for businesses with aging workforces – Aging workforces bring new risks — from increased injury potential to challenges in knowledge retention.

Capgemini recommends four best practices:

1. Recalibrate geographic focus: That means moving beyond mature markets like North America and into growth markets, such as India, whose economy is expected to be $30 trillion by 2050. It means more focus on urban areas and on climate-related problems.
2. Create age and lifestyle-friendly service models: This involves moving to a Predict & Prevent model from the traditional repair-and-replace approach, as well as supporting aging in place.
3. Build strategic ecosystem partnerships: As technology bring us autonomous vehicles, smart homes and more, insurers will need to work together with technology companies and governments.
4. Transform talent strategies: As the population ages, insurers will need to accelerate the transfer of knowledge from retirees to younger employees, retain older workers and attract talent from nontraditional pools.

I realize that predictions based on demographics can be tricky. When I decided to write about the Capgemini report, I considered using as the headline: "Demographics Are Destiny." I quickly realized the phrase was floating around in my head because the Democratic party had rallied around the idea a decade or so ago, comforting itself that an influx of young voters and new citizens into the electorate would move the country away from the Republican party. Oops. 

But it's still clear that those who get the demographic shifts right will win. 

Mitch Kapor, the founder of Lotus, once told me that he got his big break in computing because he was literally a day ahead of the curve. As a recent graduate of Yale in the early 1970s, he had kicked around in a variety of jobs. A computer enthusiast, he bought an Apple II right after it came out in 1977. A day later, he returned to the store. As he stood in line, the person ahead of him bought an Apple II and asked the clerk whether he knew of any consultant who could help him figure out how to use it. 

"I'm a consultant," Mitch said, after one day with his machine.

That one gig led to others, which led him to Electronic Arts, the maker of the first electronic spreadsheet, which led him to the idea that became Lotus. And the rest is history. All because he was one day ahead of what became the computer revolution.

Cheers,

Paul

P.S.  My horrors with Xfinity continue. I wrote last week about my nightmare experience with the company as I canceled service in advance of my move East and assumed that would be the end of that. I was even impressed when I turned in my cable box and wireless router. The customer service rep told me I could just set them on a table, and he'd scan them into the system. No need to fill out any form. Well, today, nine days later, I got both a dunning phone call and an email from Xfinity demanding that I turn in my cable box and router. 

When I called Xfinity, a rep told me, "Oh, don't worry about those. It takes two weeks for our systems to update. You only need to worry about something like a notice that your account is being sent to collections if we send you one after the 24th."

Two weeks to update based on a scan? At a major corporation? That spends money on its IT systems?

In 1950, Alan Turing asked a wonderfully weird question:

"Can machines think?"

Not "Can machines solve math problems?" or "Can machines compute faster than humans?"

Those were already givens. Turing wanted to know something deeper. Something unsettling. Could a machine act so human that we wouldn't know it wasn't?

His proposed test was simple: Have a conversation with someone behind a screen. If you can't tell whether it's a person or a machine, the machine passes. The Turing Test was born.

Now here we are, more than 70 years later, with AI writing poems, beating humans at Go, and giving startup founders existential dread. So it's time for a new version of the question, one which the founders of WealthSmyth set out to answer:

Can an AI imitate—and eventually outperform—a top licensed life insurance producer?

And no, we're not talking about filling out a form or sending a follow-up email. We're talking about the whole enchilada:

• Finding the client
• Building trust
• Understanding complex financial needs
• Navigating regulations
• Recommending a solution
• Closing the deal
• And doing it better than the best human could.

Sound crazy? Maybe. But here's why life insurance just might be the ultimate Turing Test.

Act I: Why Life Insurance Is Such a Beast

Let's start with a fun fact: Life insurance and annuities are some of the most human-dependent financial products on earth. Why? Because they're weird.

They involve:

• Long time horizons (think decades)
• Deep personal decisions (family, health, legacy)
• A maze of carrier rules, state regulations, and suitability requirements
• And a distribution system that's still powered by notepads (the kind you write on), whiteboards, and—yes—fax machines

So unlike travel agents or mortgage brokers, life insurance agents can't just be friendly and organized. They have to:

• Understand behavioral finance
• Know how to simplify complexity
• Follow strict compliance protocols
• Match clients to the right products across multiple carriers
• AND make the client feel heard and supported along the way

It's sales, psychology, and legal compliance… all rolled into one.

Which is why if AI can do this, it's not just a narrow tool anymore. It's something more.

Act II: Narrow vs. General vs. Super Smart Machines

To put this in context, let's zoom out and talk about the AI hierarchy:

1. Narrow AI – This is most of what we use today. It's great at specific tasks. ChatGPT can write an email. Your CRM can assign a follow-up. Spotify knows when you're about to cry and queues up Bon Iver.
2. General AI – This would be an AI that can do anything a human can do. Understand context. Learn new tasks. Adapt. Reason. Flirt (yikes). OpenAI Operator is starting to do this, and others are closer every day.
3. Superintelligent AI – Smarter than all of us. Together. Please unplug it if it starts talking about nanobots.

Most sales tech lives in Category 1. But actually selling life insurance and annuities—especially the way humans do it—demands something closer to Category 2. It's relational, strategic, and adaptive.

You're not just responding to questions. You're guiding a 35-year-old single mom who just lost her job, taking her through a conversation about estate planning, financial security, and what happens if she dies next week. That's not just math. That's trust.

Act III: Why Sales (Yes, Sales) Might Be the Holy Grail for AI

Ask an AI researcher what the "holy grail" of general-purpose AI might be, and they'll usually say something like scientific discovery or autonomous robotics. But here's a contrarian idea: A truly general AI needs to be good at sales.

Sales isn't formulas and forecasts. It's:

• Timing
• Emotional nuance
• Navigating ambiguity
• Persuasion
• And—especially in insurance—compliance

It's one of the few jobs where success can't be brute-forced. You can't just A/B test your way to a $1 million annuity close.

That's why life insurance might be the most honest test of AI's human-like potential. It's not about logic. It's about trust.

Act IV: Why Life and Annuities Is the Perfect Proving Ground

Why start here?

Because life insurance is:

• Massive ($3.6 trillion market)
• Fragmented (millions of agents; thousands of distributors, carriers, and intermediaries)
• High-margin (over $100 billion in annual commissions)
• Still analog (you'd be amazed how many policies are sold with paper apps)
• And regulated (no rogue AI cowboys allowed)

Here's the twist: Unlike other industries, life and annuity sales legally require a human agent on every transaction—and in the U.S., that means state-by-state licensing. No two states are exactly the same, and every agent has a "bag of providers" they're contracted with and a personal playbook they've built over time.

At the federal level, SEC's Regulation Best Interest ("Reg BI") was designed to elevate consumer protection. But in practice? Most agents still recommend the products they know and the ones they're compensated to sell. It's not malicious—it's structural.

Want better outcomes for clients?

Don't just tweak the incentives. Change the system.

Imagine a future where:

• Agents are still involved (and accountable),
• But every one of them is required to use an AI assistant that understands all available products across all carriers,
• And every recommendation is benchmarked against a fiduciary-grade best-interest standard—not just what the agent knows.

We don't just meet Reg BI. We transcend it.

This is the real opportunity with AI—not just to replicate what top agents do, but to raise the floor for everyone.

In short: life and annuities are just hard enough to be a meaningful benchmark but just structured enough to be solvable.

The industry is moving toward AI that sells like a top producer—across channels, products, client profiles, and compliance frameworks.

Not just a copilot. Not just an assistant. A producer.

And the goal?

Pass the Turing Test for life and annuities distribution.

Final Act: What Comes Next

If AI can't pass this test, then we still need human agents. And that's fine—many of them are incredible at what they do.

But if it can?

Then everything changes:

• Commissions get restructured
• Roles evolve
• Compliance frameworks adapt
• And distribution becomes digital-first at the core

But before that happens, we need to answer one big question:

Can AI truly become a producer—not just an assistant?

That's what we'll explore in Part 2: How the industry is already moving through three major phases—copilot, autopilot, and autonomous agent—and what it means for the future of life insurance.

Spoiler: it's happening faster than most people think.

Like earthquakes that gradually build up stress before releasing it in sudden ruptures, the sun undergoes cycles of mounting magnetic tension. This cyclical solar activity occurs about every 11 years, marked by phases of low and high activity, known as solar minimum and solar maximum. During the solar maximum, the sun unleashes powerful forces, including solar flares and coronal mass ejections, which can significantly disturb Earth's magnetosphere, leading to geomagnetic storms that may disrupt communication systems, power grids and satellite operations.

We are currently in solar cycle 25, which began in December 2019 and is expected to reach its peak around July 2025.

Earthly consequences

In May 2024, the world experienced the most powerful solar storm in over 20 years. While these solar outbursts are spectacular to observe, they also have the power to significantly affect our technology-dependent society. Recent disruptions include:

• Satellite failures - In February 2022, two coronal mass ejections caused up to 40 Starlink satellites to re-enter Earth's atmosphere shortly after launch, costing about $25 million.
• Communication disruptions - In December 2023, one of the largest solar radio events disrupted radio aircraft communications. In November 2015, a solar storm closed Sweden's airspace, disrupting flights.
• Power outages - A major coronal mass ejection in March 1989 significantly interfered with the U.S. power grid and caused a nine-hour power failure in Quebec, costing $13.2 million.

Not quite black or white

Solar flares epitomize the concept of a grey swan event. Unlike black swans, which are unpredictable and exceptionally rare events with severe consequences (such as the 2011 Tōhoku earthquake), grey swans like solar flares are not entirely unforeseen. They are characterized by some level of predictability based on historical patterns or scientific forecasts.

The challenge with solar flares lies in their irregular occurrence and significant variance in intensity, making accurate predictions difficult. Consequently, existing underwriting processes inadequately account for the risks posed by solar flares due to the lack of a reliable predictive model and limited historical loss experience.

The most powerful solar storm in known history

The great geomagnetic storm of 1859 – known as the "Carrington Event" after the British astronomer who reported it - caused telegraph systems in Europe and North America to fail. More than 150 years later, our planet has yet to experience a solar storm comparable to the Carrington Event.

But we should not assume the odds of a similar event in our future are zero. According to the growth rings of trees, Earth has been hit by at least six solar events larger than Carrington, by an order of magnitude or more, during the past 10,000 years.

If such an event were to occur again today, the impacts would be unprecedented. With advancements in technology and increased dependency on electronic systems, our society would be intensely vulnerable and severely affected by a modern-day Carrington Event.

Estimating the potential effects on vehicles, property and power grids is challenging due to limited historical precedents. However, current best estimates indicate that U.S. insurance industry losses could range between $71 billion and $433 billion (in 2024 dollars), with global losses significantly higher. To put these figures into perspective, Hurricane Katrina in 2005 resulted in insured losses of approximately $105 billion (in 2024 dollars), and total insured losses from all natural catastrophes in 2024 reached approximately $140 billion.

Unlike other natural disasters, which are often regionally confined, the effect of a Carrington-style event would be global - directly affecting supply chains and disconnecting large populations from power for weeks or months. The wide range of potential outcomes demonstrates the significant financial implications that solar flares could impose.

A near miss

As we approach the peak of solar cycle 25, the likelihood of severe solar storms – and their potential effect on the insurance industry and global economy – is on the rise. A near miss in July 2012 highlights the risk: A solar storm comparable in magnitude to the Carrington Event erupted, but Earth was not in the line of impact. 

Recent research from Lloyd's estimates that a storm of this severity could inflict global economic losses of up to $2.4 trillion over a five-year period, with potential losses ranging from $1.2 trillion to $9.1 trillion. These figures correspond to a reduction in global GDP between 0.2% and 1.4% over that time frame. This event emphasizes the need for robust preparedness as we near a solar maximum.

By developing scenarios, such as a repeat of the Carrington Event, risk managers will be in a better position to understand and quantify exposures to geomagnetic storms and potential financial losses, including both direct and indirect impacts.

Disaster preparation is also key. This should include implementation of measures to mitigate the risks associated with solar flares, development of contingency plans for rapid response, and ensuring risk management frameworks account for the potential scale and scope of solar flare impacts. Also, using insights from near-misses will enhance preparedness and resilience plans, as well as ensuring adequate insurance coverage and robust business continuity plans are in place.

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Because I'm in the midst of moving from California to the East Coast to be nearer to my daughters and my siblings, I've been canceling service with various companies. One handled a question horribly — and I think offers lessons for insurers, both in general terms and in terms of how they integrate chatbots into their service operations. 

So I'll tell the story here, then suggest an exercise that can keep executives from falling into the most common traps.

Because my problem wasn't with an insurance company — Xfinity is the villain here — I don't even need to pretend to be polite.

Here goes.

Some weeks ago, I canceled service with Xfinity as of May 14 but recently got a bill for service through June 3. The bill was $150 or so more than it should have been, so I went to the website and began a chat to find out what was going on. Xfinity has nickeled and dimed me in the past and generally been hard to deal with, so I was prepared to believe they had just missed my cancellation notice. 

I quickly made it past the chatbot and got to a human, who took a long, long time to dig into my bill and then gave me what turned out to be a very wrong answer. The person told me my cancellation hadn't been recognized because I hadn't provided a "verbal confirmation." 

That made no sense. I had spoken with a representative on the phone, had told the person I wanted to cancel and had received confirmation. But the rep on the other end of the chat wouldn't budge. 

The rep said they could have someone call me to get that confirmation, but before that could happen the chat dropped. I tried to reinitiate but got several error messages from Xfinity telling me to try later. When I finally reconnected, the new rep offered the same nonsensical "verbal confirmation" line and said I had to call the main service number. 

I did so and got a recorded message about some sort of billing issue related to new channels that apparently lots of people in northern California were calling about but that had nothing to do with me. After maybe a minute, the message said I could hold for a representative. I held. No representative. Instead, the recorded message started again. At the end, I held again. Still no rep. Just the recording again. I waited a third time. No rep appeared. I hung up and tried again. Same deal. I phoned again. Same thing. 

Finally, a rep from Xfinity called me — apparently, that first online rep had managed to initiate a call before our chat dropped; Xfinity just took half an hour to make the call. The rep calling me needed only a few seconds to diagnose the actual problem. Xfinity had registered my cancellation, but its information systems couldn't see the halt when it generated the bill at the beginning of the month. I should rest assured, though, that Xfinity would later adjust the bill based on my days of actual usage before hitting my bank account.

Fine, but... the rep blamed me for not understanding the intricacies of Xfinity's (brain dead) approach to billing, rather than acknowledging that Xfinity should have at least told me at the top of the final bill that it would prorate the charges for May. Nor would she acknowledge that her colleagues at the online chat shouldn't have led me on a wild goose chase based on bad information. 

In her harsh New York accent, she kept saying things like, "I'm sorry you didn't understand, but we've been billing you early in the month for years, so you really should have expected a bill from us." 

Yes, I expected a bill from you. I just expected it to be correct. Silly me. I also expected to get an accurate explanation when I contacted customer service.

I never did get any satisfaction from her. She and Xfinity were in the right, and I was just a dumb customer.

The house I'm moving into this week is serviced by Xfinity. Guess who won't be signing up with them. 

Xfinity's Strategic Mistakes

But setting my obvious frustration aside, I think Xfinity made some core strategic mistakes about customer service and believe some in the industry are making the same ones, or at least will be tempted to as the industry adopts more chatbots.

Just about every company these days, certainly those in insurance, talks about wanting to be "customer-centric," a truly ugly term that is hard to define in operational terms (a point Alan Demers and Stephen Applebaum address in their excellent piece on empathy that is one of the six articles I've highlighted this week). Companies may track whether an issue was handled on the first try, a valid concern for any customer, but typically mix in efficiency goals that complicate life for the customer. 

In my case, Xfinity was clearly trying hard to reduce the number of phone calls that get through to live agents. That's why it steered me toward the chat in the first place, and that's why they posted the long message about a billing issue that they made everyone listen to before they could even request an agent. (I hit "0" and said "agent" or "representative" any number of times with no result.) Who knows, Xfinity may have even deliberately kept the message on repeat to frustrate customers into dropping the call.

I'm all for efficiency, but those goals have to be kept separate from goals to keep customers happy and serve them better. Xfinity should have offered an easy handoff from the chat to a live call with an agent, once I hit a dead end online. The handoff should never be: Call the main number. 

I suspect Xfinity has a silo problem. Its chatbot and live online agents worked together smoothly — the chatbot really just served as a simple front end to direct inquiries to the right sort of live agent — but weren't at all integrated with the agents reachable via phone. The agent I spoke with on the phone had much more experience, likely more training and seemingly even access to more information than the online agents had. It's as though the online functions were grafted onto an existing call center organization but never really integrated. 

Xfinity certainly has a problem with the agent on the phone. She's fallen into the trap that can come with expertise. She knows everything about what she's discussing, and, if you don't, too, then you're deficient. She also seemed excessively defensive about her employer, which can come with long service. And she'd lost the good grace that would have at least tried to hide from me her low opinion of my knowledge about Xfinity's billing systems. 

Assuming what she told me is accurate, Xfinity also has an IT problem. It boggles my mind that its systems generated a bill for me on May 3 while unable to see that I had called weeks earlier to cancel service as of the 14th. 

The Dangers for Insurance Companies

I imagine many insurers also have a silo problem, perhaps an even bigger one than Xfinity has, because insurers may sell many different lines and have traditionally organized data by business group. To truly serve customers, insurers need to make sure data about them is integrated so that anyone interacting with them — whether online, in a call center or in an agency or brokerage — can see the whole picture. 

As insurers have chatbots increase their responsibilities for customer service, companies will surely measure what percentage the chatbots handle on their own and will try to keep increasing that number. But that measurement can lead to a mindset that discourages handoffs and even the sort of recorded message that Xfinity afflicted me with in an attempt to keep me from connecting with a phone agent. Customers need to be able to self-service when they want, interact with a chatbot when they want, and clear up problems with a phone agent when they want. 

Insurers also need to watch out for the problems that come with expertise. I can't imagine any insurer's rep being as strident and rude as the Xfinity rep was, but insurance is a complicated product, and those who sell and service it know an awful lot more than customers do, so there's a lot of potential for miscommunication.

The good news is that generative AI will help with some of these problems. It's really good at assembling information, so it can pick and pull from different information systems to provide a deep, integrated picture of a customer and perhaps avoid the kind of mistake that Xfinity's online service function made with me. 

Generative AI can also produce communications that provide an even, appropriate tone, heading off the sort of rogue behavior that the Xfinity phone rep showed with me. 

But insurers will need to be careful as they rely more on AI chatbots, to make sure that they're fully integrated with the other aspects of customer service and that all handoffs are smooth.

An Exercise That Uncovers Deficiencies

Beyond those general cautions, I recommend an exercise that comes from the Silicon Valley dictum that "You have to eat your own dog food." In other words, don't just get reports about metrics on your customer service. Experience it.

You obviously aren't going to file claims or apply for policies to see how you're handled. But you can latch on to perhaps one customer a month and follow them from start to finish. 

If you're involved in supervising customer service in any way, get notified when someone first makes contact with your organization, whether you're with a carrier, a TPA or other service provider, or an agency or brokerage. Then get notified every time your organization contacts them or they contact you. Read every email, text or letter. Listen to every call that's recorded. And do it in as close to real time as you can, so you wait with the customer for that week or two or three before something happens. You'll get a sense of what frustrates customers, both with your organization and with others that are part of the process, and can perhaps improve how you do things. If nothing else, you'll be more empathetic.

I hope you learn some useful things. In the meantime, I'll let you know if Xfinity really does prorate my May charges. I'm not betting on it.

Cheers,

Paul

The expression “empathy in insurance” is as abused and misunderstood as “innovation in insurance.” The underlying intent and value of both are important but vague. They are also contradictory at times and often misapplied by industry practitioners. 

Insurance innovation began to emerge with the insurtech wave roughly a decade ago. Insurance carriers added “innovation” in job titles, opened “labs” and launched corporate venture funds attracted by the prospects of modernizing insurance. Despite these advances, outsiders and many insurance insiders appropriately viewed “insurance innovation” as an oxymoron, challenging the notion that the industry is or can be legitimately innovative. This was most evident when sincere expressions of cheerleading for true breakthroughs evoked gushing terms like “transformational,” “revolutionary” and “game-changing.”

The same can be said about the debate over empathy in insurance, including empathy in claims. Escalating this debate is the introduction of conversational AI, emergence of generative AI and opposing views on just where and how far to apply these in insurance. A popular explanation from insurance executives is that artificial intelligence should have boundaries to certain functions or in replacing people. Rather, they advocate equipping people to perform better in their jobs by automating repetitive, menial tasks so people can concentrate on more valued work. Connecting information in new ways, faster, better and cheaper while keeping humans in the loop is the popular current thinking. After all, insurance is considered a relationship business. 

What Is Empathy in Insurance?

The answer to what is insurance empathy really depends on who is asked. Departments of Insurance evaluate customer service in terms of complaint volume and regulatory compliance as observed in market conduct studies. Yet there is no generally accepted standard measure for how much or how well insurers deliver empathy. The metrics associated with measuring empathy are elusive, inconsistent and focused on activities and time lines.

The JD Power 2024 Auto Claims Satisfaction Study examined auto repair cycle times which averaged 22.3 days, down one day from 2023. However, the report goes on to say that those with premium increases prior to a claim were highly unsatisfied, while those using mobile apps to file claims received scores above call centers and live agents. These may be a current example of the many contradictions and fluid criteria affecting insurance empathy.

In 2003, Fred Reichheld, while at Bain, developed the famous NPS (Net Promoter Score), which has been embraced by some of the largest companies across diverse industries. The concept focuses on customer loyalty determined by the highest survey scoring and subtracting low scoring “detractors.” In short, it’s all about keeping and attracting customers in which insurers monitor retention rates and loss of policyholders after a claim and a variety of survey findings. Yet measuring empathy delivery remains subject to assumptions or a belief more than a tangible finding.

Measuring Empathy

Elusive to measure, so-called empathetic service is best illustrated by examples and testimonials, whether through hand-holding following a home fire or battalions of adjusters descending on weather-ravaged communities to provide relief. Empathy can also be found in the everyday transaction whether during loss reporting or answering questions about recent rate increases, which can go much more smoothly with a friendly, caring touch.  

However, empathy is often more complicated and dynamic. Efficiency, competence and outcomes can matter even more than the delivery itself. Consequently, insurers persistently place a high value on the potential degradation of empathy when it comes to evaluating AI more than any other previous technology. And for good reason – agentic AI has the power to replicate human judgment and the many associated functions.

One pathway to business excellence is to apply the principles of; what gets measured, gets done. JD Power also reported that the highest-ranked key performance claim service indicator involves good communication. Conversely, the top reason for claim dissatisfaction stems from customers not being informed and updated during the process. Yet adjusters, pressed for time, often default to a reactionary mode by responding to inquiries and complaints. Therefore, insurers measure things such as the speed of customer contact and claim cycle time, while empathetic delivery can only be sparsely observed and subjectively gauged.  

Obstacles to Empathy

Meanwhile, claims leaders constantly strive to juggle loss costs, expenses, employee engagement and a cascade of organizational priorities. Better said, insurers strive for blended positive outcomes in which the right amount is paid with efficiency, keeping expenses contained -- all with satisfied customers. 

Claim adjusters receive extensive policy coverage education, claim system and estimating software training with a heaping of technical development and customer service training during their apprenticeship-styled onboarding and often-lengthy career paths – all of this with the goal of reaching claim excellence. But empathetic claim delivery in which adjusters are tested and stretched to balance work volume, complaints and customer pressures is one of those acquired skills and remains inconsistent at best.

What does the customer want?

Large enterprises probably are the most challenged to know exactly what customers want. Layers of structure get in the way. The customer may be nearly out of sight, left to reports, spreadsheets and data augmented by marketing analytics to decipher. Insurers face additional obstacles as there are numerous uncoordinated touchpoints during a claim, including medical providers, agents, repairers, solution providers and others staking individual ownership for the customer experience. 

Today’s insurance claim model is highly specialized, and a single claim can include multiple adjusters assigned, laden with handoffs and reassignments along the way. Communication channels span phone, email, text and insurer apps, clouding how empathy is experienced. All of which raises the key question of what do customers really want? This question further recognizes differences in wants and needs in a moving target scenario throughout the claim life cycle.

Redefining Empathy in Insurance

As technology advances and digital channels become more effective and commonplace, human interaction is evolving. Generational differences account for shrinking demand for live call support, especially when an automated or self-service channel is competent and efficient. Acceptance of digital-first is widespread. No need to call a taxi cab company when a few clicks of a rideshare app is much more efficient and friendly, introducing driver by name, car and license plate and live mapping pick-up time. Numerous other experiences are blending efficiency and friendliness, thus personalizing – a key ingredient in empathy. The insurance industry has already started on the path of offering digital and self-services, albeit cautiously, by providing options and soft-selling such as offering paperless and other hassle-free alternatives. 

AI and Empathy

In our related article, AI Can Fix Everything in Insurance we explore the outdated claim intake process, which remains highly dependent on human touch. Yet the claim reporting process is mainly about information gathering, only to hand off to others who routinely confirm and repeat these steps. While this model can lend a human expression of empathy, it is often outweighed by a lengthy Q&A conversation – all of which is automated and can replace live agents in all but a few circumstances. Several newer insurtech entrants take a digital-first mindset and are proving effective and efficient.

Redefining empathy in insurance must consider outcomes vs methods. Such outcomes should entail efficiency and completeness of the service experience as well as the degree of confidence assessed by how far users are able to navigate the process, whether a claim, policy change or other function.

Insurance is complex, so human experts will likely remain involved for a long time. Modern systems allow for reaching or scheduling a human-to-human conversation when the customer wants/decides. But this is the opposite of today’s typical, human-first funnel throughout insurance. Although bots probably deserve a D- grade, they are now getting smarter and more capable, with conversational AI causing insurers to consider just how far to go.

Creativity in non-human interactions can go a long way in making things friendly and welcoming. Allstate recently said Gen AI communication letters were found to be superior to human-written communications because of clarity. Digital responses can and do include friendly messaging such as, “sorry for your loss” or “congratulations on your new car/home.” This is similar to how human agents are trained, with a key difference – consistency in application. Such examples tend to muddy the water in delineating value of human touch from other customer expectations of clarity and competency.

Agentic AI offers the prospect of replicating judgment. This is crucial when it comes to personalization. The P&C industry strives for more personalization when it comes to premiums, marketing products, changing coverages and knowing their customers. Sensor technology enables real-time data capture to monitor, alert and guide risk behavior, which opens the door to Predict & Prevent imperatives designed to make insurance more effective and affordable. 

Our Take

Empathy is the ability to understand and share the feelings of another. Technology need not and does not displace sharing of feelings. Empathy will always be important – especially in claims – but it would be irresponsible of insurers not to leverage high-impact technology or remove humans from the process where judgment and experience are critical. 

The future success of insurance depends on repositioning the industry for higher relevance to the new consumer and stakeholder alike. Redefining empathy amid exponential gains in technology is a big step forward in thoughtful and responsible use of AI in insurance.

Human touch in insurance is not going away any time soon, but your next co-worker is likely to be AI-powered.