How AI is reshaping the insurance industry

Wide-scale adoption of artificial intelligence is transforming the modern insurance industry from a primarily reactive business to a proactive risk-management and life partner that clients can rely on for personalized, empowering advice and services. At least, this is what Joe Khoury, managing director and partner, Boston Consulting Group’s Insurance Practice, believes. 

“AI is shifting insurance from being primarily a reactive risk-transfer business toward becoming a proactive risk-prevention partner. Insurers are no longer just paying claims; they are increasingly using AI-driven insights to anticipate risks, offer mitigation services and personalize products in real time,” Khoury said.

He suggested that in the next five to 10 years, insurers will begin to function more like risk managers and life partners than product providers as AI enables real-time, contextual interventions. For example, a homeowner could receive a personalized alert from their insurer advising them to turn off a valve before a pipe bursts, or a diabetic policyholder could receive AI-driven lifestyle coaching bundled with their coverage.

This prediction comes into sharper focus every day, as some carriers are already leveraging technology for vehicle telematics that not only provides an insurer with information but also actively coaches drivers toward safer behavior. And others, such as John Hancock’s Vitality program, encourage policyholders to live a healthy lifestyle through special benefits and rewards. 

In this way, “risk prevention as a service” could become a significant new revenue stream for innovative carriers ready to embrace an AI-powered future.

“Over time, AI could blur the line between insurer, health care provider and consumer tech company. Whoever controls the customer interface and data ecosystem will define the value chain,” Khoury said.

At the same time, AI can potentially level the playing field between some of the largest firms and mid-tier insurers, effectively “democratizing advanced capabilities for regional players” as it gives them access to powerful analytics once reserved for major corporations.

However, today’s insurance industry has many hurdles to overcome before it can fully realize the many possibilities offered by AI. 

What hurdles do insurers face with AI?

AI leaders and experts such as Khoury believe insurers face five major challenges when it comes to fully embracing AI:

1. Adoption and scale
2. Talent
3. Regulation, ethics and trust
4. Data ecosystems
5. Internal reluctance

Pilot purgatory

Khoury noted that although many insurers are keenly interested in AI, “many insurers are stuck in ‘pilot purgatory’” — they started enthusiastically with pilot projects but never managed to successfully scale those efforts. 

In fact, the 2024 BCG Build for the Future Global Study and Digital Acceleration Index scored insurance at a high 42 AI maturity. This indicates a strong interest in AI adoption, and the only industry with a higher score was tech, media and telecom at 46. BCG noted this score marks “active experimentation.”

That same report found that only 7% of insurance companies managed to scale after that pilot stage, however. It noted that while the pilot phase starts strong, insurers soon “scale back,” as “even when successful on their own terms, these projects raise concerns about the impact they will have on the rest of the company and existing ways of doing business.”

Khoury emphasized that scaling from dozens of pilots to enterprisewide deployment is critical for insurers to realize the full value potential of AI.

AI translators

The insurance industry also needs what Khoury referred to as “translators — professionals who understand both insurance operations and AI capabilities.”

But that is a unique challenge for the industry, as tech-savvy professionals are often more drawn to high-tech careers. A 2025 study conducted by agentic AI platform Counterpart and the Young Risk Professionals organization underscored this issue. It found the insurance industry’s slow adoption of AI is keeping young professionals from seeing insurance as a top career choice.

“If you look at the results from our YRP survey, around 70% of Generation Z workers believe that AI will improve their workflows, but only less than 10% are strongly encouraged to use it. So there’s a big gap happening between what we’re seeing in the broader economy versus what’s happening in insurance,” Tanner Hackett, Counterpart CEO, noted.

Experts on a panel hosted by insurance software solutions company Send suggested the insurance industry must figure out how to change the perception that it is a “boring,” antiquated industry and effectively “bring sexy back” if it hopes to attract young professionals with AI skills.

They acknowledged that the rapid advance of AI is expected to change job roles and create new skills, urging insurers not to ignore the fact that younger professionals want to and expect to use technology in their daily tasks.

Ethical standards

Some of the biggest risks with adopting AI center around regulation, ethics and transparency that builds trust with clients. Khoury said these issues should not be afterthoughts but must be table stakes.

A “bold improvement” would be “industrywide collaboration to establish shared ethical standards and data trusts” that enable competition based on customer experience, he suggested.

At the same time, he said insurers should not wait for “perfect clarity” from regulators, who tend to move more slowly than technology. Instead, he urged them to engage regulators early and “help shape the guardrails rather than waiting passively.”

“The key is governance by design. Leading insurers embed explainability, fairness checks and auditability into AI models from Day 1,” Khoury said.

Much of the same has been expressed by other experts, who urge insurers not to “hold their breath” on outside regulation but to establish their own internal frameworks. Data and AI solutions firm SAS has even developed a free tool to help companies with this.

“We believe that it’s table stakes to do AI responsibly, and that it’s essential for us, as a society, to make sure we get this right,” Kristi Boyd, senior trustworthy AI specialist with SAS’s Data Ethics Practice, said.

Rich, structured data

On a more technical level, Khoury noted that insurers must expand partnerships to access richer, alternative data sources — and he’s not the first to note this shortcoming. 

In an earlier interview, Sumit Taneja, EXL’s senior vice president and global head of AI consulting and implementation, said that the insurance data landscape is “still very siloed,” noting in one case that an insurer had up to 28 different legacy systems, all with different, unstructured data.

Taneja likewise asserted that this foundational data challenge is limiting insurers’ ability to scale faster. Further, he believes this may take years for some companies to address because they would have to invest in data warehouses and platform modernization before being able to scale AI solutions.
“There are many foundational problems that the insurance companies have, which limits their ability to accelerate. One is the multiplicity of admin systems, and second is their data landscape is still very siloed. Unstructured data has not been managed properly, so using some of that data for AI is still a few months or maybe a year away,” Taneja said.

Risky reluctance

While AI adoption is steamrolling ahead in insurance, some reluctance remains. This sentiment is another reason, Khoury believes, why many companies have not managed to scale past pilot programs.

He noted that resistance at both the organizational and individual levels, unclear roles and responsibilities, limited business engagement and inconsistent support all contribute to an AI strategy “stalling.” And this is a major risk in an age when many competitors are pulling ahead with advancements.

“Laggards will face margin compression. If a top-tier player uses AI to process claims in minutes instead of weeks, customers will demand that as the industry standard. Those who can’t deliver will see churn rise sharply,” Khoury said.

Considering that BCG’s 2024 Build for the Future Global Study found 27% of insurance companies had not begun taking any action on AI at all, reluctance to embrace technology could prove a critical weakness.

It also highlights a clear differentiation in the approach taken by globally recognized companies such as Manulife, which operates primarily as John Hancock in the U.S.

For comparison, Jodie Wallis, the global chief AI officer spearheading Manulife’s award-winning AI rollout, recently revealed that the company’s vision is to incorporate the technology throughout its entire business model.

“Prior to large language models coming on the stage, we would have said AI is suitable for parts of our business and less suitable for other parts. Now, our perspective is it’s really suitable for all parts of our business,” Wallis said.

What are the key areas for AI transformation?

If these challenges can be managed, Khoury noted that AI will continue to transform four key areas in insurance:

• Client interactions
• Distribution and lead generation
• Underwriting
• Claims

Client interactions

Artificial intelligence technologies such as large language models and natural language processing have changed the way clients engage with businesses. AI chatbots and virtual assistants are now capable of resolving routine queries instantly, providing faster service and granting advisors more time to deal with complex tasks. 

Chatbots, in particular, are a major AI advancement and are being used for customer service, sales, claims processing and underwriting functions. The chatbot market has experienced such enormous growth in the last few years that Allied Market Research predicts it will hit nearly $5 billion by 2032.

Additionally, Cognizant’s AI Inclination Index 2025 shows insurance customers are increasingly comfortable with using AI for research, learning more about certain products before speaking with a professional to make the actual purchase. While this varies based on type of insurance, such as life and annuities or property/casualty, and client age, the overall trend indicates consumers are slowly becoming more willing to engage with AI tools.

Craig Weber, head of insurance strategy at Cognizant, said this represents an opportunity for insurers to make huge gains with their AI adoption and innovation strategy, perhaps even looking to agentic AI as a solution.

“There are small subsets of buyers and users of insurance who are willing to entertain the use of AI. So, my best advice to an insurer is to build the skills around AI and plant the flag because this trend is only strengthening over time,” Weber said.

Distribution and lead generation

Many believe the customization capabilities offered by AI will be a huge differentiator that drives leads, sales and competition from here on out. One such individual is Joe Crawford, director of professional services at Glassbox, a digital experience intelligence platform.

Glassbox has leveraged AI to fight both traditional forms of insurance fraud and the new methods that are emerging in a digitally advanced age. He believes that using AI tools to deliver customization is “pretty much a must these days.”

“We’re in a situation today where people are looking for personalized experiences. They are looking for instant experiences. They’re looking for intuitive experiences, frictionless experiences with their digital platforms,” Crawford said.

To this end, BCG underscored how AI-assisted agents can “efficiently process large volumes of unqualified leads, directing customers to the most suitable sales journey,” whether that’s fully digital, phone assisted or in person.

“AI-driven analytics help brokers identify micro-segments and design hyper-personalized outreach,” Khoury said. 

Underwriting

One of the most important aspects of insurance being transformed by AI is underwriting. In recent times, dozens of new patented underwriting technologies have emerged to speed up the process and even provide instant decisions. 

“Models can process nontraditional data such as IoT sensors or satellite images to sharpen risk selection,” Khoury noted.

Munich Re’s alitheia platform is just one example of the many AI-powered underwriting tools that have emerged in recent times, using machine learning and a patented natural language processing tool to accurately determine risk.

Insurance Software Automation’s Best Plan Pro is another tool assisting with prequalification from the moment a customer calls in to get a quote — before the application process even begins.

But experts have pointed out that technology has also enabled underwriters to assess new factors they previously may not have had access to, making risk analysis more robust.

For example, Darcy Rittinger, chief risk officer at global insurtech provider Cover Genius, said insurance carriers are looking at traditional underwriting parameters such as age and health in smarter ways thanks to alternative data sources.

“By accessing this enhanced data and utilizing AI, insurtechs can create more tailored products and better risk models and streamline the underwriting processes,” she said.

Claims

Claims processing, being one of the biggest aspects of the insurance business, is likewise a major aspect of insurance that has been permanently transformed by AI for staff and clients alike.

“Historically, claims have been the most painful customer moment,” Khoury said. “With AI-powered image recognition and straight-through processing, settlements can now occur within hours. This redefines customer trust.”

As an example, he noted how generative AI tools can draft settlement communications and analyze images of car damage with “near-human accuracy.”

Now, specialized AI-powered tools are being developed for claims in specific areas or at specific points of the journey — such as for health insurance, P/C and more.

One recent example is Qumis, an
attorney-trained AI platform designed to support insurance professionals with complex policies and documents. While it helps with analyzing claims, the platform is versatile and can also be used for insurance marketing documents and content, for example. 

Qumis founder Dan Schuleman emphasized how this level of technology is especially necessary as social inflation drives claims costs higher and never-before-seen forms of coverage are emerging, such as cyber insurance.

“The claimants are only going to get more sophisticated, the claim types are only going to get more complex, and so the carriers are going to need tools that radically help with that in order to combat the very unsustainable trends happening,” Schuleman said.

Efficiency gains are just step one

Perhaps the biggest shift brought about by AI is the speed of decision-making in insurance. Khoury noted, for instance, that what once took weeks — such as underwriting a complex risk — can increasingly be done in hours or even in minutes.

However, he noted that stopping at efficiency gains would be a mistake. While those are a crucial part of the equation, he said insurers should also think about how AI can aid growth and provide a pathway to new revenue streams.

“If insurers stop at efficiency, they will simply be leaner versions of today’s business. Growth requires the courage to rethink products, not just processes,” Khoury said.

He estimated that efficiency gains may free up 15% to 20% of costs but maintained that “true transformation comes from new streams — personalized wellness add-ons, pay-as-you-live coverage and
real-time risk advisory.”

AI can drive growth not just through traditional sales but also through merger and acquisition activity, according to David Crofts, insurance M&A lead, West Monroe Partners, who noted a trend of larger insurance brokers shedding underperforming assets in favor of diversifying their product landscape, finding cross-sell opportunities and pursuing strong adjacencies.

“For a broker to be successful in the wholesale and managing general agency space, it’s becoming more and more table stakes to have a very strong data and analytics competency,” Crofts said. “We’re seeing much more use of AI, much more heavy use of data-driven insights as part of the sales, the selling model and sales enablement process by brokers.”

Khoury noted that if insurers can succeed with maximizing growth opportunities through AI and technology, they may “substantially reduce claims volume, shrinking the traditional premium pool while opening new service-based business lines.”

“There is growing discussion in the market about how AI will generate revenue streams beyond traditional risk-based offerings,” Khoury said.  

Rayne Morgan is a journalist, copywriter, and editor with over 10 years' combined experience in digital content and print media. You can reach her at [email protected].