Over the past 30 years, technological progress has radically altered the way we live and work. Some product lines and job categories have disappeared, while entire new industries have sprung up in their place. Each wave of innovation triggers a familiar question: Is this technology truly transformative, or is it another overhyped trend that will eventually fade? Individuals and organizations alike face the same dilemma: invest time and resources now or adopt a wait-and-see approach? If the technology proves durable, early adopters can reap outsized rewards while those who wait risk losing ground. But the reverse is also true: Investing too soon in the wrong technology can waste time, capital, and strategic focus.

For individuals, the choice often hinges on opportunity cost—learning curves are steeper when existing routines need to be changed or unlearned. Even so, these barriers are typically lower because individuals can act independently. For organizations, adoption becomes more complex. Collective decision making, meeting business objectives, legacy systems, and competing internal priorities all need to be aligned in a twofold challenge: justify the investment across multiple stakeholders and implement the new technology successfully within operational constraints.

Artificial intelligence (AI) now sits squarely at this crossroads. Although opinions still differ on how far AI will ultimately go, one reality is already clear: Adoption is widespread. Typical consumers rely on generative models to summarize information, compare options, draft communications, plan travel, and complete daily tasks. In the corporate sphere, pilot projects using AI abound, though full-scale deployment is taking time as firms weigh accuracy, compliance, and return on investment. For insurers and other financial institutions, the conversation has typically focused on operational efficiency—how to underwrite faster, detect fraud sooner, or automate customer service. Yet a potentially larger disruption may come from the demand side; there is a growing population of AI-fluent customers who expect the same speed, transparency, and personalization in financial products that they experience elsewhere.

How AI-powered decision making could disrupt life insurance buying behavior

Historically, insurers have understood consumer behavior largely through macroeconomic variables. AI introduces a different kind of behavioral shift. Consider a fixed-annuity policyholder who is still within the surrender charge period. Even when competing products offer higher yields and attractive incentives to overcome the current surrender charges, replacement activity is often constrained by practical friction points: researching alternatives, comparing contract terms, navigating unfamiliar digital channels, re-entering application data, and interacting with the current carrier (which may persuade the policyholder to keep the policy in force). If a financial advisor is involved, the advisor must also weigh the benefit of searching for replacements against time constraints, competing client needs, and the tangle of incentives from the different insurers. This process may ultimately result in the policyholder staying with the current contract.

AI removes much of this friction: Market scans occur in seconds, net-of-fee comparisons can be automated, and pre-filled transfer paperwork may soon be the norm. Some consumers may eventually authorize AI agents to execute certain transactions autonomously. Although not everyone will behave with perfect efficiency to optimize their financial gains, a critical mass of AI-enabled consumers could erode profits that once relied on inertia and expose loopholes, design flaws, or ALM mismatches at scale. Ultimately, products that customers perceive as structurally adversarial—or as a zero-sum game between consumer and insurer—will become increasingly vulnerable.

AI can help life insurance policyholders understand complicated products

The same forces, however, open new avenues for insurers, especially where company and customer incentives are naturally aligned. AI can act as a full-time interpreter and educator, helping prospective policyholders understand how specific products protect income, manage health risks, or build long-term financial security. Historically, this education fell to agents and distributors whose reach is limited by time, economics, and the customer’s personal trust. If customers already place confidence in AI, a well-designed product can instantly be explained in plain language to audiences once considered out of reach. In the best scenarios, this reduces acquisition costs, mitigates “trust gaps,” and unlocks underinsured segments—without requiring carriers to embed advanced AI in every corner of their own operations. What they must embrace, instead, is a deeper understanding of an emerging customer base that will arrive already equipped with powerful analytical tools and heightened expectations.

Pragmatism still matters. Greater efficiency and more proactivity mean some policyholders will arbitrage contracts, exploit edge cases, and optimize relentlessly for financial gain. When optimization narrows to a single metric—typically financial gains—herd behavior can build quickly and send shockwaves through the broader market. Yet money is only one dimension of value. Other industries have mitigated pure price competition through layered reward ecosystems and engagement models that resonate beyond immediate financial return: status tiers, loyalty points, exclusive experiences.

For example, life insurers may glean lessons from other fields:

• Loyalty programs build brand loyalty through functional, psychological, and social value — not just dollar amounts — driving emotional commitment and making switching to competitors feel far less appealing.¹
• 15% of cardholders cited credit card rewards programs as a top driver of increased card spending/continued use, with 7 in 10 seniors specifically citing rewards-program benefits as their reason for staying with a card.²
• Access to loyalty programs has let hotel brands reduce dependency on third-party online travel agents, saving an estimated 15 to 25% in commission fees per direct booking.³
• The closer airline frequent flyer members are to earning elite status, the more likely they are to choose that airline even when it costs more than a competitor.⁴

Insurers and asset managers can follow suit, transforming protection and savings products into platforms that reward healthy habits, financial literacy, or long-term engagement. By blending hard economics (account values, crediting rates, premium levels) with softer but still meaningful benefits (well-being credits, partner perks, community status, personalized experiences), carriers gain new levers to guide behavior, dampen volatility, and cultivate durable relationships. In an AI-enabled market, recognizing the full range of how customers perceive value will be essential to any sustainable product strategy.

Looking ahead: Life insurers must adapt their products and services to AI-fluent customers

As AI continues to reshape how consumers gather information and make decisions, trust and transparency will become defining competitive advantages. AI is likely to reduce information asymmetries, compress margins on commoditized features, and expose incentives that are poorly aligned with customer interests; but it will also create new possibilities for personalization, engagement, and more efficient matching between products and needs. For insurers, the challenge is not simply to deploy AI internally, but to prepare for a marketplace in which customers themselves are increasingly AI-enabled. The firms best positioned to succeed will be those that recognize AI fluency not as a niche behavior but as an emerging consumer norm and adapt their products, value propositions, and customer relationships to withstand continuous comparison, explanation, and recommendation.

¹ The role of loyalty programs in boosting hotel guest loyalty: Impact of switching barriers - ScienceDirect (Koo, Yu & Han (2020), "The role of loyalty programs in boosting hotel guest loyalty: Impact of switching barriers," International Journal of Hospitality Management, 84, 102328).

² PYMNTS. 15% of Cardholders Cite Rewards for Increased Credit Card Spending Retrieved July 9, 2026, from https://www.pymnts.com/news/loyalty-and-rewards-news/2023/15percent-of-cardholders-cite-rewards-for-increased-credit-card-spending/.

³ White Sky Hospitality. (n.d.). The state of hotel loyalty 2025: trends, challenges, and strategic opportunities. Retrieved July 9, 2026, from https://whiteskyhospitality.com/the-state-of-hotel-loyalty-2025-trends-challenges-and-strategic-opportunities/.

⁴ Orhun, A. Y., Guo, T., & Hagemann, A. (January 26, 2022). Reaching for gold: Frequent-flyer status incentives and moral hazard. Marketing science. Retrieved July 9, 2026, from https://pubsonline.informs.org/doi/abs/10.1287/mksc.2021.1341.