Discover how consumer centricity is fueling life insurance growth
AI can help insurers turn digital transformation into clearer guidance, greater relevance, and stronger long-term consumer relationships.
By Samantha Chow
Our industry isn’t facing a lack of demand. In fact, nearly half of consumers are actively considering life insurance. Yet one in four drops out of the purchase journey before completing it. So, what’s the real issue?
The recently released Capgemini World Life Insurance Report 2027 outlines several reasons why: Thirty-five percent of consumers view life insurance as too expensive, 30% cite a lack of clarity and transparency around coverage and policy terms, and 25% say it is not relevant to their current life stage. In many cases, those perceptions do not reflect the products or actual pricing. Younger U.S. consumers, for example, overestimate the median cost of life insurance by a factor of 10 to 12.
Closing that understanding gap is a natural next step in an insurer’s digital transformation. Over the past few years, life insurers have increasingly used AI to modernize operations and improve efficiency. Now it’s time to extend those capabilities to the consumer experience to deliver clearer communication, more relevant information and guidance, and build stronger relationships with customers at every stage of the purchase and policy lifecycle.
More information alone will not accomplish this. Around 38% of consumers say the life insurance content they encounter is more focused on selling than educating, 37% find it too technical or jargon-heavy, and 34% struggle to compare options.
But a leading group of insurers are already addressing these issues: They are 1.8 times more likely to deliver contextual and interactive education, 1.9 times more likely to explore the use of key life milestones for proactive outreach, 2.1 times more likely to match advisors to consumers based on demographic profiles, and 2.8 times more likely to unify consumer data into a single, accessible view.
And it’s working. These best-in-class insurers have achieved 41% higher revenue growth over the past three years and 12% lower lapse rates than mainstream insurers. Their experience suggests the next competitive advantage will come from using AI to build understanding, relevance, and trust throughout the consumer journey.
Rethinking how we measure distribution
Best-in-class insurers know that distribution begins when someone first begins to research life insurance, not only when a consumer asks for a quote or a policy is issued. It continues through research, purchase, and the years of engagement that follow.
Thinking about distribution in this way changes what success looks like for an insurer. Every interaction becomes an opportunity to help consumers understand what coverage does, how it fits their circumstances, and how its value will evolve with their lives.
And it doesn’t stop there. As many as 36% of policyholders say they rarely or never hear from their insurer or agent after purchasing coverage, while 74% say post-purchase communications are limited to billing and renewals. As a result, many are unaware of features they already have: Only 29% know about flexible premium payment options, and just 22% are aware of grace periods for missed payments or access to cash value or policy loans.
These consequences extend throughout the lifetime of a policy. Twenty-six percent of customers who surrender or cancel policies cite a lack of understanding of benefits and liquidity options as a key reason. And 50% of consumers who discontinue their coverage do so within the first three years, well before insurers have realized the full lifetime value of the relationship. An early exit can signal that the insurer never established enough relevance or value to make life insurance part of the consumer’s long-term financial planning.
Sales efficiency will, of course, remain an important measure of distribution performance. But insurers should also ask how effectively their distribution model helps consumers understand, value, and remain engaged with their coverage. Doing that well requires changes in how insurers educate consumers, enable advisors, and use intelligence across the customer journey.
How AI can transform consumer engagement
Closing the understanding gap requires insurers to rethink how technology supports consumers and advisors throughout the relationship. Here are three ways to start:
Educate before you persuade
Consumers should not need to become insurance experts before deciding whether coverage is right for them. AI can help insurers move education earlier in the journey and tailor it to the questions and circumstances that matter to each consumer.
AI-based conversational guidance can answer questions contextually as consumers research coverage rather than requiring them to navigate static FAQs or decipher technical product materials. Generative AI can also create personalized financial narratives that illustrate what types and amounts of protection consumers may need and why, based on their current circumstances or future scenarios.
That capability applies to both individual and group coverage. Employees, for example, may be enrolled in employer-provided life insurance without knowing whether the amount is adequate. Only 25% of employees receive guidance about coverage adequacy, even though 57% feel moderately confident in employer coverage they have never formally assessed. AI-enabled guidance can help consumers move from knowing what coverage is available to understanding whether it meets their needs.
AI can also make education more timely. Best-in-class insurers are 1.9 times more likely to explore using life milestones for proactive, needs-based outreach. Combining CRM information with appropriate third-party data and using AI to analyze those signals can help insurers identify changes in household, wealth, career, or other circumstances that may signal a need for guidance.
Significant life changes like marriage and a new job can become opportunities for a relevant conversation, rather than waiting for a policy anniversary or renewal. Those insights can also inform next-best actions and help advisors tailor their outreach.
Equip advisors to deliver better guidance
Greater use of AI does not diminish the importance of human expertise in life insurance. In fact, quite the opposite as consumers still want it when decisions become consequential – 67% prefer agent interaction when evaluating pricing and making purchase decisions. At the same time, they expect those interactions to reflect what the insurer already knows about them.
AI can give advisors the context needed to meet that expectation, but the human touch remains key. Real-time behavioral insights, life-event alerts, unified interaction histories, and next-best-action recommendations can reduce the time advisors spend assembling information and help them focus on interpreting it for consumers.
The same technology can also improve how consumers and advisors are matched. Half of consumers prefer advisors who reflect their demographic profiles and can provide personalized advice, yet only 24% of insurers have fully deployed demographic- and life stage-based advisor matching.
Conversely, best-in-class insurers are 2.1 times more likely than mainstream insurers to match advisors based on consumer profiles. AI can help analyze consumer personas and life-stage signals and route consumers to appropriate advisors, while in-language and in-culture tools can help advisors engage different communities more effectively.
Automating administrative work and providing real-time customer intelligence can give advisors more capacity for complex conversations and relationship building as well. The objective is not to replace the advisor relationship, but to make each advisor interaction more useful.
Build intelligence that serves every interaction
Neither personalized education nor AI-enabled advice works at scale without the right data foundation.
Consumer information often sits across policy administration systems, CRM platforms, digital interactions, advisor records, and external sources. When those systems remain disconnected, consumers may receive inconsistent guidance depending on the channel they use, while advisors lack a complete picture of the people they serve.
And the majority of insurers are in this situation: Only 18% currently have a unified strategy and roadmap for the consumer journey, and only 33% have deployed even partial AI orchestration. Best-in-class insurers, meanwhile, are 2.8 times more likely to consolidate consumer data into a single, accessible view and 3.1 times more likely to deploy agentic AI capabilities.
A unified intelligence layer can support decisions across the relationship, enabling AI to access connected consumer data to personalize interactions, surface relevant information to advisors, and identify when human involvement is warranted.
The same principle applies beyond distribution. Automating standard underwriting decisions, routine servicing tasks, and claims triage can help insurers meet expectations for speed and efficiency while reserving human expertise for deeper analysis and more complex work.
This matters because while using AI for isolated tasks can drive efficiency. Connecting data and intelligence across the operating model creates the foundation for more consistent experiences and allows insurers to apply human judgment where it delivers the greatest value.
The next evolution of digital transformation
AI is becoming foundational infrastructure for insurers. As these capabilities become more widely available, competitive differentiation will come less from whether an insurer has AI, and more from how effectively the organization redesigns its operating model and customer engagement around it.
The first wave of digital transformation gave insurers new ways to automate processes, accelerate decisions, and improve efficiency, and those capabilities remain essential. But the next evolution can extend their impact to the consumer by making coverage easier to understand, engagement more relevant, and advice more informed.
To succeed, insurers will need to make changes across the full distribution journey, delivering more active consumer education that helps people recognize their protection needs before a sales conversation begins. Providing advisors with the intelligence to offer relevant guidance at critical moments. And connecting data to ensure insurers maintain that understanding as circumstances change long after a policy is issued.
Life insurance will remain a human-centered business, because decisions about financial protection are personal and often complex. But AI can strengthen that model by managing complexity behind the scenes and giving consumers and advisors better information when it matters. And insurers that use AI this way can move beyond digitizing existing processes and build lifelong financial protection relationships grounded in relevance, trust, and understanding.
About the Author
Samantha Chow, Global Life and Annuity Sector Leader
Samantha is a global expert in life, annuity, and benefits. With nearly three decades of experience, she leads transformation across the industry through AI innovation, technology modernization, and customer-centric strategies. A recognized thought-leader, she helps insurers redefine distribution, strengthen engagement, and build future-ready organizations.