OpenAI released ChatGPT in late 2022, and it became the fastest app to reach 100 million users in history. Consumer novelty, not enterprise business utility, fueled the growth. In the enterprise, outside of content creation and coding, AI is still very much a solution in search of problems.

The tech ethos of "move fast and break things" is challenging the enterprise ethos of "move slowly and protect things," such as market share, customers and cash flow, all things tech startups lack.

As unprecedented sums of tech capital flow into AI infrastructure and startups, enterprise executives are asking the question they always ask: "What's all this going to cost?"

See also: AI: Beyond Cost-Cutting, to Top-Line Growth

Anthropic invested $100 million in training the latest version of Claude, their flagship foundational AI model. CEO Dario Amodei recently predicted training costs will climb to $1 billion next year and $10 billion by 2027. Sharing this with an enterprise executive, she said, "Geez, if a great customer service agent is going to cost us $300,000 a year, I'd rather pay a human."

The trend in enterprise AI is toward smaller predictive and agentic models trained on proprietary data. The challenge is enterprise data is without fail scattered across a phalanx of applications and storage tiers. The big cost isn't model development but data transformation, typically a two-comma proposition.

Beyond cost, enterprise executives are asking, "What's the real business utility of this stuff?"

In health insurance and healthcare broadly, new regulators in Washington and disgruntled providers and policyholders are poised to break the status quo in pursuit of better health outcomes per dollar spent, simplicity over complexity, and transparency over opacity.

See also: Who's Getting Results From AI, and Why?

A Gallup survey released recently finds that only 44% of Americans rate U.S. healthcare good or excellent, down from 62% in 2010. A mere 28% rate the country's insurance coverage highly, an 11-point decline over the same period, despite spending $2 trillion more on premiums.

AI will meaningfully improve health insurance and healthcare delivery. Payers and providers are engaging point solutions and proofs of concept in operational efficiency, value-based care models, member engagement, price transparency, and regulatory compliance.

Typically, enterprise AI developers, based in the data science or IT function, get their hands on a data set and ask, "What tool can we develop?" The better approach is to identify the business problem, find the data and develop the tool.

Developing the algorithm tends to be the easy part. The hard part is changing the workflow, often across fiefdoms, to accommodate the new AI. Starting with the business problem generates big ideas, and big ideas transcend siloed self-interests.

Here's an example of a big idea: Blue Shield of California's Pharmacy Care Reimagined replacing their incumbent pharmacy benefits manager (PBM) with a consortium of AI-enabled partners, leveraging AI to orchestrate the new operation. It's a bold initiative that will take two years to implement. As always with new partners and technologies, a lot can go wrong. The executive sponsor of the program is CEO Paul Markovich.

The payoff? An estimated $500 million in annual savings on pharmacy costs with better price transparency for Blue Shield of California's nearly 5 million members. Now those are gains making all the pain worth signing up for. Everyone wins except the status quo.

Outside of payments, customers interact with their insurance carrier an average of once per year. With so few touchpoints to work with, the written communications insurers send throughout the customer lifecycle, such as welcome kits, policy renewals and claims updates, play a major role in shaping the customer experience. Rather than treating these communications merely as a means to satisfy operational and compliance requirements, insurers should leverage them to build trust and emphasize what sets them apart in an increasingly competitive industry.

Unfortunately, the communications most insurers provide are long and unnecessarily complex and are mostly delivered by mail — or, at best, posted as static PDFs on web portals. This won't cut it with today's mobile-first customers, who rely on their phones to manage nearly every aspect of their lives. Consumers of all ages expect businesses to deliver accessible, user-friendly communications that integrate seamlessly into their digital routines. Anything less feels outdated and inconvenient.

Meeting these expectations isn't possible without first modernizing the outdated, often custom-built systems many insurers use. Major advancements in customer communications management (CCM) technology enable insurers to eliminate the manual processes, technical debt and outdated technology that is stifling efficiency and blocking innovation. 

Here are five capabilities insurers should prioritize when evaluating potential CCM solutions:

1. Centralized control of communications for all channels

When adopting a new communication channel, insurers typically set up an operational and technological silo — for example, managing email separately from printed communications, SMS, web portals and others. These solutions are managed by disparate teams, which increases costs, duplicates operational processes, such as managing the same content in multiple locations, and potentially fragments the customer experience.

Insurers can benefit from a centralized content hub from which communications can be delivered to any channel where it's required. These systems manage content independently from channel-specific templates and layouts — known as the "presentation layer." This approach eliminates the need to manage content in disparate systems for each delivery channel and enables teams to reuse content across channels.

See also: Language Barriers Create Claims Challenges

2. A cloud-based platform to lower infrastructure costs

A 2023 report from Capgemini states that 91% of insurers have begun moving to the cloud, recognizing it as essential to reducing costs and eliminating tech debt. While many have focused on migrating their core policy and customer management systems to the cloud, CCM infrastructure is still typically hosted on premise.

Moving to a cloud-based CCM system significantly reduces infrastructure and maintenance costs. Built on modern tech stacks, cloud-based systems reduce reliance on a small pool of specialized employees needed to keep outdated or custom-built systems up and running. The systems also provide seamless upgrade processes, eliminating the need for time-consuming manual updates and regression testing, while enabling businesses to immediately benefit from the latest features and security enhancements. Additionally, cloud platforms support real-time collaboration, enabling teams to access and modify content from anywhere — an essential capability for modern, dispersed workforces.

3. No-code content to accelerate change cycles

For many insurers, minor updates to their communications can take weeks — or even months — because their legacy CCM systems require costly IT resources to code content updates into communication templates.

Insurers need systems that enable nontechnical personnel to design and update content, set targeting rules and arrange layouts without having to write code. This enables business and communication teams to take control of the content, rules and template layout. As a result, change cycles can happen in minutes, not months, giving the business the speed and flexibility to launch products faster and meet regulatory deadlines with ease.

4. Integrated AI capabilities for improving content clarity

To the average customer, insurance is a complex and unfamiliar subject. Unfortunately, insurers often compound the issue by sending communications filled with industry jargon and dense language that confuse and frustrate customers. A recent report from Forrester states that "customers are 2.7 times more likely to spend more when companies communicate clearly." Insurers that simplify their communications will not only drive better customer engagement but also foster long-term loyalty and trust.

Innovative CCM platforms are making it easier to achieve this with AI-powered capabilities that streamline the process of improving communication clarity. These tools can quickly evaluate an insurer's entire library of content, identifying unclear content using established benchmarks like Flesch-Kincaid scoring. They can also provide rewritten alternatives that simplify complex information, such as coverage details, claims instructions or compliance notices, into language that is easily digestible by the average customer, or even align content with plain language standards like those set by ISO. Some platforms also have capabilities for AI translation, offering insurers the ability to cater to the 22% of Americans who speak a language other than English at home. AI can translate content more than 20 times faster than humans while validating semantic similarity and translation accuracy, thereby reducing translation teams' effort to one of reviewing exceptions and inaccuracies that are caught by the algorithms.

See also: 3 Steps for Insurers to Keep the Human Touch

5. Capabilities that streamline responses from frontline teams

With the agent-led sales model on the decline, a carrier's claims, adjustor and customer service teams are more essential than ever to building a personal connection with customers. These frontline teams often need to follow up with customers after speaking with them, sending personalized, one-off communications that address specific inquiries or provide additional information discussed during their interactions.

Modern CCM platforms enable frontline teams to quickly locate, personalize and send communications while giving their managers control and visibility into what gets sent. These systems integrate seamlessly into the portals and platforms frontline teams use every day, saving them from having to search through shared servers and Word templates to find the most up-to-date version of the desired communication.

Agents can quickly personalize content and graphics using a guided interview process, after which a purpose-built communication using the customer's specific data is generated. Predefined sections of the communication can then be customized through a controlled editing process, which achieves true one-to-one personalization without the risk of sensitive branding and regulatory content being altered. From there, if required, the communication can then be passed to other stakeholders for approval before being delivered to customers on their channel of choice.

Insurers can't afford to wait any longer. The technical debt from legacy systems is only going to keep growing, and the bar for customer experience will only get higher. By moving to modern customer communications management systems which have the capabilities outlined above, insurers can drive efficiency, reduce costs and equip themselves with the agility needed to stay competitive in a rapidly changing market.

The auto insurance industry has long relied on underwriting methodologies that focus on demographic data to determine premiums. However, this static approach ignores critical dynamic factors, such as driving behavior and environmental conditions, that play a significant role in assessing risk accurately.

The application of artificial intelligence in auto insurance is more than just a technological evolution — it's a fundamental shift in how the industry approaches risk, pricing and customer engagement. With advancements in telematics, app-based innovations and computer vision, insurers now have the tools to create data-driven solutions that enable fairer premiums, safer roads and a better customer experience.

See also: Underwriters' Productivity Can Double

Moving Beyond Traditional Underwriting

Traditional auto insurance underwriting relies on static demographic data — age, ZIP code, gender and car type — to determine premiums. While this approach is straightforward, it overlooks key variables that directly influence risk, such as driving habits, routes and time of day. For example, highway driving carries five times more potential loss magnitude than urban driving. Similarly, driving at night is three times more dangerous than daytime driving.

Conventional methods fail to factor in these real-time behaviors, often resulting in generalized risk assessments that either overcharge or underprice premiums. AI-led underwriting changes this equation. By leveraging telematics data, insurers now have access to real-time insights into individual drivers' behavior.

Telematics for Real-Time Risk Assessment

Telematics serves as the backbone of real-time risk assessment. This technology captures data-rich insights from drivers, vehicles and their surroundings, enabling insurers to create comprehensive driver profiles and dynamic, behavior-based premiums. Over the years, telematics has evolved across four key generations:

1. First-Generation Telematics (Hardware-Based)

The earliest telematics involved installing hardware like OBD (on-board diagnostics) devices or black boxes in vehicles. While these devices could accurately track driving data, their high operational and logistical costs made them unscalable. Installing, maintaining and managing these devices presented numerous challenges for scaling across broad consumer bases.

2. Connected Car Telematics

Every new vehicle sold today comes with built-in connectivity features. Connected car telematics taps directly into the vehicle to extract key driving data without the need for additional hardware. While this data may not always be used for underwriting, it enables insurers to promote driver safety through rewards and enhanced risk insights.

3. App-Based Telematics

Smartphones are redefining telematics with their advanced sensors, such as gyroscopes and accelerometers, enabling insurers to collect rich driving data via mobile applications. App-based telematics is cost-effective and scalable, accessible to virtually any policyholder with a smartphone. This tool is expected to dominate over the next decade, as insurers adopt app-driven models for capturing real-time behavioral data.

4. Computer Vision and Video-Based Telematics

The latest innovation in telematics is video-based technology using computer vision. For instance, Tesla's fleet uses multiple cameras to assess contextual driving behavior, predict accidents and enhance safety through automated maneuvers. Commercial fleet owners are rapidly adopting this technology to improve road safety and implement precise risk assessments. Beyond underwriting, video-based telematics also optimizes claims management, offering highly accurate reconstructions of driving incidents.

Together, these advancements in telematics form the foundation for scalable, actionable and real-time risk analysis, driving the future of the auto insurance industry.

Real-World Impacts of AI in Auto Insurance

The integration of AI into insurance is already yielding significant outcomes:

• Dynamic Premium Adjustments: AI factors in diverse variables, such as time and environment, for more precise underwriting. Studies suggest that despite 60% less traffic on the roads, more than 40% of all fatal car accidents occur at night. Real-time data allows dynamic adjustments to reflect these risk levels more accurately.
• Personalized Policies: Customers can now benefit from policies tailored to individual driving habits, replacing one-size-fits-all models. Drivers with safer habits, such as daytime local commutes, may pay significantly lower premiums.
• Improved Customer Experience: Using AI-driven systems, insurers can provide instant quotes, reduce processing times and offer actionable insights for safer driving behavior.

This level of personalization is unprecedented in auto insurance, offering fairer pricing models and incentivizing safer driving.

See also: The New Era of Underwriting

Benefits Across the Insurance Value Chain

AI in auto insurance extends its value beyond underwriting and pricing. It also addresses key components across the insurance value chain:

• Claims Management: Telematics data assists in reconstructing accident scenarios with high accuracy, ensuring fair claims processing. Video-based systems are proving invaluable for settling disputes efficiently.
• Driver Safety Programs: By capturing real-time driving habits, insurers can offer safety recommendations and reward responsible drivers with premium discounts, promoting overall road safety.
• Fraud Detection: AI algorithms identify anomalies and flag potential fraud, saving insurers billions annually. Telematics data brings transparency to claims and mitigates fraudulent activities.

AI's Role in Defining the Future of Auto Insurance

AI is enabling insurers to shift from generalized, outdated methods to dynamic risk assessments grounded in data science. The adoption rate of telematics and AI in the insurance landscape is expected to grow significantly in the coming years. According to McKinsey, the telematics insurance market could grow by more than 25% annually through 2025, driven by a push for personalized services and regulatory support for safer roads.

For auto insurers, this presents both an opportunity and a necessity. Those who fail to integrate real-time, AI-driven solutions risk being left behind, unable to meet evolving customer expectations or compete with agile, tech-enabled players.

For consumers and insurers alike, the benefits are compelling — fairer pricing models, safer roads and streamlined claims experiences. The adoption of AI signals a new era of risk management, allowing insurers to not only respond to risks but actively mitigate them. This is the next generation of auto insurance, and it has AI driving the wheel.

Insurance Thought Leadership

You’ve been pushing hard to help the insurance industry innovate ever since you founded WeGoLook 15 years ago. How are we doing?

Robin Roberson

With the advent of insurtech, we've seen significant advancement in collaboration and multiple types of technology. Many carriers and brokers have become more welcoming of digital transformation, though this shift took time. We witnessed a surge of insurtech companies developing various technologies for risk assessment, underwriting, and claims modeling. Today, thousands of companies worldwide can interface with any point of the insurance ecosystem, whether it's carriers, brokers, TPAs, IAs, or third-party providers. 

Despite these advances, we still observe considerable manual work in the claims process itself. While data capture tools have improved significantly - going from mailed photos to mobile phone submissions, and resolving connectivity issues - the actual claims workflow from FNOL to close remains largely manual. Desk adjusters and claim handlers continue to face challenges, including toggling between multiple systems, managing various file types, handling both unstructured and structured data, and dealing with spreadsheets and photos. We've even seen people still taking notes on scratch paper and searching through large binders to determine proper procedures for specific carriers and situations. 

This represents an area of opportunity, which is one reason why we started Agentech. Overall, the industry's willingness to adopt and leverage technology has improved significantly compared with just a few years ago. Everyone's more comfortable with it now, though it's worth noting that insurance has traditionally been a legacy-oriented, archaic, and risk-averse industry.

Insurance Thought Leadership

To provide a bit of background on how you think about innovation, tell us about WeGoLook and its eventual acquisition by Crawford.

Robin Roberson

WeGoLook was an incredible journey that leveraged the gig economy before it became widely known through companies like Uber. We created a platform that dispatched contractors on demand to capture data through photos and videos and to perform simple tasks. One of our major successes came through partnering with one of the nation's largest insurers, helping them shift from their legacy model to a new auto model. 

We pioneered desk adjusting within their organization, transforming what traditionally required licensed adjusters several days into a much more efficient process. For example, tasks like photographing parking lots, cart barns or construction work or documenting ingress and egress points could be completed quickly using our geolocation technology. We reduced what was typically a three- to seven-day process down to just 45 minutes for the carrier, while also handling police reports and other documentation needs.

We also made significant inroads in the auto industry, including working with Tesla before they developed their own app for trade-in models. WeGoLook was ultimately sold to Crawford in early 2017, and I stayed on for about two and a half years before moving on to ClaimCentral.

My business partner Kenneth and I collaborated with ClaimCentral, an Australian company, where I served as managing director for North America. Our focus shifted from working with independent contractors to becoming providers of claims services. We recognized that adjusters and TPAs were struggling with the inefficiency of logging into multiple platforms to manage various services - from EMS to roofing, roof tarping, and drywall work. In response, we built a comprehensive ecosystem to streamline these processes. This solution proved so successful that we eventually sold a portion of the platform and exclusively licensed the remainder to Eberl Claim Services. As part of contract negotiations, I moved to Eberl as SVP of platform partnerships for two years. 

Throughout this journey, I've remained deeply committed to driving efficiency in the insurance space. And naturally, it's been impossible to ignore the transformative potential of AI in this field.

Insurance Thought Leadership

You also started a consulting business after leaving Crawford, to help others innovate. You’ve been busy.

Robin Roberson

After leaving Crawford, we started a company called Goose and Gander. It was a boutique insurtech consulting firm that worked with multiple clients, many of whom we still have today. Our services covered a wide range of areas including cyber, data tokenization, cybersecurity, digital strategy, and even branding. We helped multiple clients with various aspects of their business. TokenX was one of our customers. We helped them secure a position with Marsh McLennan, and they eventually exited for approximately $140 million - quite an impressive outcome.

Insurance Thought Leadership

That brings us to Agentech. Where did that idea come from?

Robin Roberson

I grew up watching Star Trek and was the only girl in chess club. I’m a self-proclaimed nerd, and I've always loved artificial intelligence. When a colleague reached out about a problem that could be solved using agentic AI, that led to Agentech.

The idea began with ethnographic research in the pet insurance space, specifically looking at creating pet health profiles. They identified a significant bottleneck in the claims process where someone had to manually compile health histories and verify them against policies. As a pet lover myself, with dogs and koi fish, and coming from a foster rescue background, I understood how critical quick claim processing is when people need to make decisions about their pets' medical procedures. 

What really caught my attention was realizing how similar this process was to property and casualty insurance claims. The parallels between pet insurance claims and residential property or auto claims were striking. In fact, we discovered these processes were remarkably similar across multiple lines of business. 

The company was born out of Gitwit, a venture studio in Tulsa with a strong research team, business analysts and engineers. They've already launched two other AI-focused companies, so there was tremendous expertise behind the project. When Alex approached me about collaborating, it was an exciting opportunity to combine their technical expertise - including our founding engineer, who's an astrophysicist - with my passion for customer service and process improvement. 

What makes this solution special is its flywheel effect. When adjusters have the best tools, claims are processed more quickly and accurately. This leads to happier policyholders and reduced costs for carriers, allowing for continued improvement.

Insurance Thought Leadership

How has your business progressed since completing your recent capital raise?

Robin Roberson

We're already generating revenue with paying customers, and we've been operating for just over a year now. We emerged from stealth mode in September and immediately pursued aggressive growth, successfully raising a $3 million seed round in just 30 days. The investment round was supported by Oklahoma-based investors, with just two exceptions that we had previously engaged. One is a major IA firm, and the other is Thomas Brown from Clickclaims, who owns a claims management platform and serves as one of our technology advisers. 

What's particularly exciting is seeing how our AI agents can be applied to field adjusting, not just desk adjusting. We're also seeing great potential with third-party service providers I've worked with over the years, as they all interact with the claims workflow in different ways. This technology allows us to orchestrate and manage these processes more efficiently, streamlining the entire workflow.

Insurance Thought Leadership

What is your vision for the company's future, particularly regarding services for agents and brokers?

Robin Roberson

Our primary focus is helping to process claims much more quickly and triaging them properly. For brokers and agencies, this means enabling immediate information sharing when incidents occur, even in the middle of the night, and facilitating smooth communication among policyholders, TPAs, and carriers. We want to eliminate the need for policyholders to repeat incident details multiple times to different parties. 

It's important to understand that agentic AI within the claims process provides digital agents that function like highly efficient administrative assistants. We're not making decisions or adjudicating claims - we're simply a support tool automating many time-consuming manual tasks. For brokers dealing with multiple carriers, guidelines, and jurisdictional rules, our orchestration agents are particularly valuable. 

We currently have a catalog of over 200 agents that we leverage, and we're continuously expanding this number. These agents communicate with each other to rapidly identify and process all necessary components for effective claims triage. Looking ahead, we're focused on improving adjusters' quality of life. I recently spoke with an adjuster who takes her laptop to her children's ball games during hurricane season. The surge of claims doesn't stop just because the storm passed - it continues for weeks. With our technology, we believe this kind of around-the-clock work shouldn't be necessary except in rare circumstances. 

Our technology also addresses the industry's talent shortage. Younger professionals expect better technology and don't want to spend their days doing repetitive work. By providing excellent tools that automate routine tasks, we allow adjusters and claims handlers to focus on complex decisions and claim adjudication. 

We're already seeing success through our integration with Snapsheet, where our APIs are automating tasks with minimal change management needed. For example, we can automatically generate and schedule status update letters based on state guidelines, simply notifying the claims handler when it's done. This eliminates the need for handlers to manually complete numerous status letters each morning - a simple but significant improvement in efficiency.

Insurance Thought Leadership

Any final thoughts?

Robin Roberson

I would highly recommend to your readers that if they haven't already identified at least 100 or 200 ways that AI can help support and improve their business, they're already behind. It's important to understand that the companies that best leverage technology will be the clear winners moving forward. 

Obviously, I'm passionate about this whole topic, and I'm always happy to talk to anybody if they have questions about anything – it doesn't even have to be about AI agents. I'm here to help if I can.

Insurance Thought Leadership

Thanks, Robin. It’s been great getting to catch up a bit.

 About Robin Roberson

As a serial entrepreneur, Robin has more than 25 years of experience working with clients to develop solutions to improve their business. She has held numerous leadership roles throughout her career and has won multiple awards highlighting her commitment to customers, business organizations and her community. Cyber security, artificial intelligence, and digital strategies are primary passions for Robin, and she is eager to share agentic AI solutions, which deploy AI agents to automate the most tedious tasks within the claims process, as co-founder and president of Agentech.com. Previously, Robin was co-founder and CEO of WeGoLook, where she changed the way insurance carriers (along with other industries) leveraged the gig economy, by dispatching on-demand “Lookers” to capture field data, then selling her company to a global TPA for over $36 million. Recently, she held a dual role for the North American expansion of an Australian repair vendor platform and was president of Livegenic, continuing to service multiple P&C carriers. After successfully positioning the platform with leading IA firm Eberl, she helped launch the FLEX Repair program as SVP of Eberl platform partnerships. Robin is also an investor in Array, a low-code/no-code platform that enables customers to digitize all manual forms while easily creating custom workflow processes for maximum efficiency, and is an advisor to Aptly, a SaaS platform designed to ensure authority is properly delegated across an enterprise to reduce risk, improve governance, and facilitate rapid, informed decision-making to enhance operational agility and competitiveness. Robin is a board director at BancFirst, board member for United Way of Central Oklahoma, and member of Leadership Oklahoma, Committee of 100. She was the first female director at OESC for the state, responsible for 450-plus employees and 27 offices. She regularly attends and speaks at industry events. However, her favorite role is ‘mom’ to two amazing adult sons and three dogs. As a breast cancer survivor, Robin is grateful for the opportunity to continue thriving personally and professionally.

Large business enterprises have the internal resources or can hire a broker to help them make smart decisions about the types of insurance coverage they need to safeguard their companies. But leaders of small and medium-sized businesses (SMBs) often find themselves without the resources they need to do the same.

No one ever starts a small business with a top goal of buying insurance. In fact, it may feel like the worst purchase they have to make because the best-case scenario is they'll never use this product at all because nothing bad happened and they don't have to make a claim.

The insurance industry's job is to ensure that when they need that coverage, SMB owners have it and paid a fair price for it.

Unfortunately, that doesn't happen enough. Studies show that 75% of U.S.-based small businesses do not have the appropriate insurance coverage for their needs. Another study found that 90% of SMB owners weren't certain they had the right insurance.

One reason SMBs aren't properly covered is that knowing the right coverage to purchase can be challenging. Not to mention, carriers offer seemingly similar products at different prices.

Thankfully, technology can help all customers make smart business insurance decisions.

See also: Win in the Small and Medium-Sized Business Market

How insurance agencies can serve SMB customers with technology

Improve efficiency with intelligent automation to help SMBs take the guesswork out of evaluating multiple carriers

The reality of today's insurance marketplace is that each carrier's appetite for risk and the types of SMB customers they want to serve changes all the time. A leading carrier may have been willing to write a certain type of business in the past but not today.

Independent agents and brokers need to know carriers' preferences in real time so they can match them with customers efficiently. Recommendation engines overlaid with machine learning can help better understand which prospects are best for carriers' current needs. These are updated as preferences change.

SMB owners, on the other hand, want to understand what they're buying, how to make sure they have the right coverage and how to avoid unnecessary coverage. When an owner has to shuffle through 100 carriers with different approaches to the same type of coverage, technology can help them navigate and narrow down their options.

By continually drawing on up-to-date carrier information, agencies can more efficiently get SMBs over the finish line and make sure their businesses are protected.

Automate repetitive work, freeing agents to answer owners' questions

One of the chief benefits of technology is that it lets agencies do the simpler things quicker.

Insurance agents and brokers are able to block and tackle by not requiring agents or SMB owners to enter the same information repeatedly. For example, an owner who previously had to fill out each carrier's intake form can now answer a few questions and see multiple carrier quotes.

Another example: Recommendation engines that identify the right coverages for specific risks can speed customers through the top of the funnel and take pressure off human agents. This frees them to do the value-added work of helping SMB owners understand their coverage and find the best value.

Offer SMB owners more intelligent self-service options

As generative AI evolves and improves, agencies will want to consider freeing time through AI chatbots that can have initial conversations with SMB owners about what coverages they need and what options make the most sense for them.

Many SMB owners are using artificial intelligence tools to make their own businesses more efficient and may appreciate how it can make their lives easier as insurance customers, too.

They can learn more about providers and plans without talking to a representative and have more efficient conversations with agents because they're already better informed.

Personalize communications and relevant content at scale

The reality is that most SMB owners only think about insurance when they initially need to purchase it or at renewal time, so insurance carriers and insurance agents need to be thoughtful about when they reach out to their customers.

Algorithms can help agencies create and deliver relevant content, educational resources and tools that help customers better understand their current policies at renewal and if they need to make any changes to their coverage or move to a new carrier.

In addition, agencies can use data they have or are able to acquire to identify other important events – such as anniversaries, changes in company size, regulatory changes in the SMB's state or emerging risks in their industries – and trigger communications to re-evaluate coverage.

See also: Insurance Industry Embraces Tech, Trust in 2025

Use technology to augment – not replace – expert agents

Finally, one of the best ways to look out for SMB owners is making sure they can continue to have consultations with trusted human experts.

Technology is unlikely to replace humans completely in the insurance chain. Instead of replacing them, it should make them better. Human agents are needed for the important work of providing guidance that comes from deep knowledge and experience.

The goal of any insurance agency should be to provide technology that can get a customer as far along the decision chain as they want. But even when SMB owners are offered the chance to purchase online, they typically get to the buy button and become concerned about whether they're choosing the right coverage. That's when they want to pick up the phone and talk to an agent.

Technology works best when it makes humans on both sides of the equation smarter. It can help customers use self-service tools to get smarter about policies and understand different offerings. It can also help insurance agents have more productive conversations with prospective and existing customers, leading to increased loyalty.

The move toward automation is happening every day

SMB owners may not want to think about insurance, but it can make or break their business if something goes wrong. Thankfully, the insurance industry is embracing technology as a way to help these customers make smarter decisions quicker so they can put their main focus on their businesses.

Technology helps SMB owners become more informed on their own and augments human agents so they can find the right coverage for any customer more efficiently.

The insurance industry should embrace technology and educate their SMB customers about the value it provides, so the marketplace more easily matches buyers and sellers with the right policies and growing companies have the protection they deserve.

The workers' compensation industry is undergoing a profound change powered by artificial intelligence. Historically, the sector has grappled with inefficiencies, inconsistencies and costly delays that undermine trust and fairness. Workers face a prolonged claim process, while insurers and employers contend with inflated costs and administrative burdens. AI offers a new tool that is starting to help automate complex tasks, improve claim accuracy and provide a data-driven foundation for equitable decisions.

However, this is only the beginning. The application of AI in workers' comp is poised to expand. But AI's current and future benefits will only come with careful architecture and consideration. As the industry embraces this new era, stakeholders must balance innovation with ethical considerations to ensure a fair, consistent and effective system.

Enhanced Fraud Detection and Prevention

Fraudulent claims have long plagued workers' compensation, eroding trust and driving up costs. AI may offer a new form of fraud detection with unprecedented capabilities.

Through pattern recognition, AI systems analyze large datasets to identify anomalies, such as duplicate claims, inconsistent medical histories and exaggerated injuries. These tools detect fraud in real time, flagging suspicious claims and enabling insurers to act more quickly, preventing unnecessary costly payouts. AI will also be used for predictive fraud modeling; it will assess the likelihood of fraudulent behavior based on historical data and an evolving set of risk factors or "red flags." This will allow insurers to focus investigative resources where they are most needed, reducing overall fraud. In other words, AI will help convert fraud prevention from a reactive pursuit to a proactive one.

Integration of Advanced Technologies

AI's potential in workers' compensation is enhanced significantly when combined with other advanced technologies, enabling larger, expansive adjacent industry solutions that address every aspect of injury prevention and claim management. The internet of things plays a pivotal role on the injury prevention front. Wearable sensors and environmental monitors collect real-time data on workplace conditions, which AI analyzes to identify potential hazards. This approach may reduce injury rates, while fostering safer work environments.

Virtual and augmented reality are revolutionizing rehabilitation, providing personalized recovery plans and immersive environments that can help injured workers regain function. These tools, enhanced by AI, optimize rehabilitation outcomes and may accelerate return-to-work timelines through simulated environments customized for specific jobs.

Blockchain technology complements AI by ensuring secure, transparent sharing of critical data (e.g., QME reports, patient history, etc.) among stakeholders. This combination creates a robust ecosystem for claims processing, safeguarding sensitive information while enhancing efficiency and trust.

Lawful and Reliable Data

With great power comes great responsibility. To reap some of the powerful rewards that will come with the integration of AI into the workers' compensation system, the insurance industry will need to develop robust regulatory frameworks to guide implementations and ensure ethical use. These frameworks foster compliance with existing regulations without stifling innovation, helping insurers and employers balance risk and reward.

For example, data privacy and security will always need to be thought through with any implementation of AI in the workers' compensation arena, as these systems must work with sensitive claimant data in compliance with laws such as HIPAA. Robust cybersecurity measures mitigate the risk of data breaches, which will be necessary to preserve trust from all stakeholders.

Many current systems suffer from inconsistent documentation and fragmented records, limiting AI's effectiveness and oftentimes causing erroneous results. Establishing industrywide standards for data collection and reporting is crucial to overcoming these barriers. Equally important: training staff to oversee the application of these guidelines to ensure proper use of AI.

Algorithms must be transparent and equitable, free from biases that can lead to unintended consequences. Bias can creep in via incomplete information or datasets that are skewed by the motivations (conscious or unconscious) of the design engineer and "expert" consultants driving workflows and decision trees, which could lead to disparities in claim outcomes. Diverse datasets and rigorous audits are key to mitigating this issue and fostering equitable decisions. In short, responsible AI development is tedious and requires high levels of both intellectual and financial investment.

The Human Factor

Workforce adaptation is another critical factor. Claims adjusters, medical evaluators and attorneys must embrace AI as a tool to enhance their roles rather than view it as a threat. Training programs that equip workers with the skills to collaborate around AI-enhanced processes while instilling an understanding of the technology's limitations will enhance problem solving and illuminate the parts of an organization's operation that need improvement.

Balancing efficiency and empathy remains a delicate task. While AI accelerates claim resolution, human interaction is irreplaceable for workers navigating physical and emotional challenges, and an individual must ultimately be responsible for the work AI produces and be able to communicate the process to auditors and courts. A hybrid approach that combines AI precision with human compassion ensures the best outcomes.

Preparing for the AI-Driven Future of Workers' Compensation

The future of workers' compensation lies in the effective integration of AI and complementary technologies. By enhancing fraud detection, streamlining claims processing and leveraging innovations like IoT and VR, AI continues to show great promise for the industry. However, success depends on addressing challenges such as data quality, workforce adaptation and ethical considerations.

As stakeholders navigate this transformative era, they must prioritize fairness, transparency and empathy. AI-driven systems must balance efficiency with human-centric values, ensuring that injured workers receive the care and support they need. With thoughtful implementation design and appropriate technical collaboration, AI can lead the way for a more equitable and effective workers' compensation landscape, benefiting all stakeholders.

As the adage says, "Trust takes years to build, seconds to break and forever to repair." The extensive and growing loss of trust in our most treasured institutions is responsible for the recent and rapid transformation of behavior and attitudes across the entire landscape. 

Trust is created by the belief that institutions will uphold their stated values, follow established rules, and act with integrity, leading to a willingness to rely on them and respect their decisions. High levels of institutional trust are crucial for a well-functioning society, enabling cooperation, social stability, and citizen engagement. 

When trust in institutions is low, it can lead to cynicism, social unrest, decreased participation in civic life, and difficulty implementing policies. The insurance industry ranks high on the list of vilified industries. Unfortunately, the murder of Brian Thompson and the ensuing criticism of healthcare insurance from many quarters is likely to bring more scrutiny to all segments of the insurance industry, including P&C. And some of that negativity may be justified. 

Aftermath of UnitedHealthcare CEO Brian Thompson Assassination

The shocking number of sympathetic voices in support of the accused murderer of Brian Thompson appearing in social media and several insurance publications are the latest manifestation of this corrosive loss of trust. Consumer activist Sen. Elizabeth Warren even stated that the killing served as a “warning” of sorts that “you can only push people so far and then they take matters into their own hands.” Other opportunists are jumping on the bandwagon and fanning the flames even before we know the reasons why the alleged killer acted and if it was truly motivated by insurance outrage. 

The P&C Insurance Industry

The P&C insurance industry is expected to exceed $2 trillion this year in the U.S. alone and is experiencing its own turmoil and breaches of trust. From the beginning, insurance was centered on the "ultimate covenant," with the promise to pay should an event occur, subject to specified conditions, including payment of premiums. However, underlying sentiment combined with the recent inflection point in healthcare serves as an alarm bell to all forms of insurance.

There are several generally perceived breaches of trust in P&C, as well. Massive rate increases and recent uninsured events and denials of coverage are in the forefront of consumers' minds. Questionable use of personal information collected in conjunction with connected vehicle programs along with overall insurance distrust has limited opt-in of usage-based auto insurance. A common refrain is, "I don’t want my insurance company watching me drive.” Use of aerial imagery has sparked commentary: “Is my insurer spying on me?” Recurring regulatory fines, class action suits and settlements focused on claims practices are extensively reported as tying reduced payouts to higher profits. The suspension and withdrawal of coverage, and threats of that by carriers, in higher risk markets such as California, Florida, New York, and New Jersey have only added to the animosity and loss of trust. 

See also: Building Trust in Insurance with Technology

Trail of Broken Trust

Trust in general has been slowly deteriorating in numerous and serious ways across a broad swath of society.

In no particular order of either severity or chronology, some major examples of breaches of trust;

• Rising rates of urban crime, from carjackings to “smash and grabs” and theft have contributed to retail store closings and reduced foot traffic in the nation's premier retail shopping areas.    
• Trust in several federal agencies to keep us safe has been broken repeatedly: FEMA’s inadequate responses to Katrina and, recently, Helene in North Carolina and other extreme events illuminated DHHS/CDC/NIH/FDA’s failures with regard to the pandemic response, food safety, vaccination policy, water quality and more.   
• Trust in our politicians has declined noticeably as polarization between the two-party system has eroded civility and ignited retribution between these factions, spilling over into negative campaign ads and social media jibes.
• Our social media platforms are sharing our personal information and habits for profit and are disseminating disinformation that manipulates our opinions on a range of issues    
• Frequent data breaches and abuse of private information have resulted in consumer loss of trust in companies to protect their personal information, safety and security.
• Increasingly, large media organizations (broadcast and print) have become aligned with one of the two political parties and no longer present independent and balanced reporting. Local and community reporting is quickly vanishing.
• The most current example of government failure is the inability of numerous law enforcement and national security agencies to address the mysterious drones flying over the Northeast, leading to a variety of concerns, frustrations and fears.

Legal System Abuse and Social Inflation

Insidious and exploding “nuclear” jury verdicts and the impact of litigation funding have driven up the cost of insurance defendant settlements, which inevitably are passed along to policyholders in premium increases. General opinion is that the industry is not sufficiently focused on containing and combatting these threats but rather relies on lawmakers, who move slowly and often reluctantly. In the meantime, the costs from legal abuse are passed on to businesses and consumers, raising additional ire. 

Protection Gaps

The global insurance protection gap is the difference between the total economic losses from natural disasters and the amount that is insured. It's a measure of how well societies and economies can withstand disasters. In 2023, the global protection gap was estimated to be $1.83 trillion, and only 38% of global economic losses from natural disasters were insured. As claims mount from extreme weather disasters, policyholders who assumed they had coverage are shocked to learn that it is not so in many cases. Naturally, their disappointment turns to anger directed against their insurers. This gap is only growing for businesses and consumers as rates and deductibles increase and coverages are dropped or policy conditions are re-written. Many are concerned with the cascading impact to the housing market as combined mortgage rates, taxes and insurance push the American dream of homeownership further away.

P&C Industry Lobbying

Property and casualty (P&C) insurance companies have outspent health and life insurance peers in lobbying the U.S. government over the past 10 years, according to an S&P Global article. In 2023, P&C insurers spent approximately $57.2 million on lobbying, while health insurance spent about $49.2 million and life insurance about $31.1 million, the article says. Industry analysts question the accuracy and transparency of these expenditures as being inconsistently reported and in some cases understated.

Recent media reports claim the P&C industry has seen a $4.1 billion net underwriting gain for the first nine months of 2024 after raising annual car insurance premiums by 26%, on average, nationally. The link between the lobbying investment and these premium increases should be obvious and one can understand the impact on public opinion.

See also: Embedded Insurance: A Major Disruptor

On the Horizon

The full impact of AI in insurance cannot be fully imagined just yet, but there are already great concerns. Bias, hallucinations and privacy are just a few. Carriers are going to great lengths to wall off AI programs for fear of data breach. Shortly after the launch of ChatGPT, concepts of widespread job replacement quickly reshaped to ideas of using AI as a copilot, underscoring this unknown and double-edged new power. AI for the purpose of approving/rejecting health claims is going through enormous criticism as the matter of fairness is questioned. There is tremendous room for the insurance industry to demonstrate how AI in claims can bring consistency, fairness and transparency while delivering efficiency and healthy stewardship of premium revenue. 

Restoring Trust

It may not take “forever to repair,” but the insurance industry can do a lot to begin the process and start making progress. The industry needs to speak to consumers with one voice.

 Communications should be in plain, candid and concise language (not corporate speak) and include details of the steps they plan to take and changes they plan to implement. Communication around claims should be especially speedy, clear, frequent and accurate. The healthcare segment will have to face up to public criticism and conduct a basic re-evaluation of their business model, practices and procedures – and do it before the federal government imposes its own version.

Addressing the enormous protection gap described above is a prime opportunity to not only rebuild trust but also represents an enormous economic opportunity for innovative carriers. A recent example from the North Carolina Insurance Underwriting Association involves grant monies to homeowners to invest in home resilience before a claim happens and raises the question of what further role should P&C play in avoiding losses? 

We trust in the fundamental integrity of the many thousands of insurance industry professionals and call upon investors, boards and executives to do the right thing to ensure the health and longevity of this critically important industry. While the industry response is yet to be seen, it begins with introspection.

Like most of us, you're probably still coming to grips with the disruptive effects of the generative AI boom that began just two years ago, but there's no rest for the weary. 

It's time to gear up for the next wave, known as agentic AI. 

Basically, this form of AI goes beyond the sort of gathering and processing of information that generative AI does as it responds to prompts and produces text or images. Agentic AI can act as a sort of personal assistant and execute tasks on your behalf. To pick a simple example: Rather than just telling you what information is available on a claim, your agentic AI could ping people on your behalf and ask for the detailed cost estimate you need or for an update on when car repairs will be finished, then notify the client, without the need for you to be involved.

AI's reputation for "hallucinations" will make for cautious implementation of agentic AI, at least in the early days, but you're going to hear a lot about it in 2025. So let's get started. 

While AI has burst into the public consciousness in recent years, especially once ChatGPT was introduced in late 2022, the first wave traces all the way back to 1956. Computing pioneer John McCarthy was making a presentation at a conference at Dartmouth and needed a term to describe the work he was doing. "Artificial intelligence," it was. 

The work took a number of different routes during its first few decades — limited, of course, by computers that were a tiny fraction of a percent as powerful as they are now. I came in during the expert system and natural language processing phases in the 1980s and early 1990s. Expert systems, which tried to encode the knowledge of human experts, eventually fell out of fashion because it turned out that there were too many subtleties to fully capture what humans did. Natural language processing, by contrast, eventually gave us "Hey, Siri..." and "Alexa..."

Let's lump all that together and call it the first wave and, despite many false starts, label it a success. No, we aren't yet answering to the robot masters than some futurists predicted decades ago, but, I mean, Siri, Alexa and their ilk are remarkable. 

The second wave came when generative AI rocked the world two years ago. Suddenly, AI not only had a brain, it had a mouth — in the broadest sense. It could speak, write and draw or animate, on command. 

A key shift began with the realization that machines could learn, that they didn't need to be taught everything. Yes, you could do a lot by interviewing the world's best players at chess or Go, but you could also just tell a computer the rules, let it play hundreds of billions of games against itself in a few hours and emerge with a system that could overpower the best human players. 

Transformers, which appeared on the scene in 2017, took the handling of data to the next level. Rather than looking at a sequence of data and predicting what comes next, like previous forms of AI, transformers can look at entire (even massive) data sets and process the connections simultaneously. (If you're curious, there's a good description of them here.) 

We're still dealing with the implications of that second wave, but now we're facing the prospects of AI agents that don't just serve as research assistants but that can act on our behalf. 

As futurist Bernard Marr explains here, we could be looking at a world "with humans taking on roles similar to chiefs of staff who coordinate and manage teams of AI agents. This transformation is already sparking the emergence of exciting new positions like AI agent trainers, AI workflow orchestrators and AI ethics compliance officers....

"But this is just the beginning. Consider a near future where your personal AI agent contacts an AI agent of a car rental company to negotiate the best deal based on your preferences and schedule. In healthcare, specialized agents could create patient medication summaries, while in finance, AI agents might handle dispute resolution and insurance claims....

"For organizations still focused on earlier waves of AI, the time to explore agentic AI is now. The transition isn't just about adopting new technology, it's about reimagining how work gets done.... The future of work will be shaped by our ability to effectively collaborate with AI agents."

As Marr acknowledges, there will need to be some guardrails for these AI agents, and there will be a learning curve.

I'd go even further. I've been hearing for decades that software agents are imminent. Remember internet refrigerators and the like? They were going to keep track of everything in them and reorder as necessary. But how was my refrigerator supposed to know what I planned to eat for dinner in the next week? I'm pretty idiosyncratic. Aren't you? Besides, with my daughters about to come home for Christmas, I'm going to need a lot more food, including items I never buy on my own. (Matcha, anyone? Gluten-free pasta?) When they head back to DC at the end of the month, I'll get back to normal. An internet refrigerator wouldn't have a clue. 

Based on history, I think AI agents will be heavily circumscribed for some time, maybe years, just as their earlier counterparts have been, even though I acknowledge that the new versions are far more intelligent. 

In any case, as I said, you're surely going to hearing a lot about them in the New Year. Get ready.

Cheers,

Paul 

The insurance industry is at a pivotal crossroad, grappling with the realization that traditional operational models and legacy technologies are no longer sufficient in a rapidly evolving world. To remain competitive, insurers must shift from the mindset of “this is how insurance is done” to embracing innovation and transformation. Read this new report to understand the lasting impact of early InsurTech disruptions, and why further changes is still essential.  

Read Now

Sponsored by ITL Partner: Majesco

The insurance industry needs a facelift, and 2025 promises to provide just that. Due to growing cyber threats, demands for increased service speed and expectations for growing transparency, this coming year will be characterized by advanced technologies and a mindset of earning customers' trust.

The mission? Not only to protect insurers' clientele but to amaze them. In such a competitive environment, insurers are prioritizing innovation, personalization and peace of mind. The shift involves quicker claims processing, seamless communication and products tailored to modern consumers.

In this race, technology isn't just a tool; it's front and center in driving transformation. Advanced AI, real-time data insights and predictive analytics help insurers provide superior and more relevant coverage. In general, 2025 is about reimagining what insurance can be: secure, transparent and, above all, customer-centric. It is no longer just about risk management but about creating an experience where clients are celebrated and supported at every turn.

Rebuilding Trust in the Industry

Insurance, in itself, remains a source of frustration for customers: complex policies, slow claims and even a lack of clear communication. The J.D. Power 2024 U.S. Auto Insurance Study showed that only 15% of auto insurance customers had high levels of trust in their auto insurance. How can insurers win back trust? By prioritizing transparency, delivering faster claims processing and adopting straightforward pricing.

There is also a growing tendency toward ethical business practices while firms implement ESG principles into their business models. Insurers are regaining trust and improving perceptions with increased care about sustainability and social responsibility.

See also: How AI, Tech Reduce Friction in Insurance

Cybersecurity: A Mandate, Not an Option

This past year, the volume of cyberattacks continued to escalate, leaving no one feeling safe and putting more pressure on insurers to safeguard customer data. Cybersecurity is not an option; it's a mandate. In 2025, insurers are stepping up with significant investments in AI-driven threat detection, blockchain for secure transactions and robust encryption.

Insurers will introduce new types of cyber insurance coverage to help businesses protect against data breaches and other digital vulnerabilities. By prioritizing robust cybersecurity measures with comprehensive coverage, the industry will become key players in managing cyber risks.

Technology Redefines Customer Experience

Technology and customer experience are progressing in parallel. Companies will adopt digital platforms that make insurance easier and more convenient for customers. User-friendly apps, digital payment solutions and online portals will allow clients to access policies, file claims and receive support with just a few clicks. Intuitive and responsive user design reduces friction on these platforms, making insurance less of a hassle.

Surveys done by the National Association of Insurance Commissioners in 2022 and 2023 show that 88% of auto insurers, 70% of home insurers and 58% of life insurers are using AI. These numbers are only going to continue to grow.

Advanced AI, real-time data insights and predictive analytics are reshaping the way insurers connect with customers. These tools enable tailored coverage that meets unique policyholder needs while streamlining the entire process. Routine inquiries will be handled by AI-powered chatbots, offering quick resolutions without the frustration of delays. Even complex claims are simplified with guided, step-by-step support that eliminates stress for the customer. By integrating these technologies, insurers aren't just making life easier—they're reducing risks, improving operating efficiency and delivering the kind of experience today's customers expect.

See also: How Cloud Tech Improves Customer Experiences

Rethinking Insurance Today

As 2025 unfolds, the insurance industry will make bold moves to rebuild trust, combat cyber threats and revolutionize customer experience. With these steps, insurers can demonstrate their readiness to adapt and thrive in a fast-moving world, remaining relevant and trusted by their customers.

The question isn't whether the industry will evolve—it already is. The real question is: How will insurers lead the charge?