Is Your Insurance Tech Stack Ready for AI?

Last year we surveyed insurance executives to better understand the state of modernization across the industry.

At the time, the findings highlighted familiar challenges: aging core systems, fragmented data, rising maintenance costs, and organizational barriers slowing transformation efforts.

Looking back, those findings also revealed something more consequential: the factors that now determine AI readiness.

As carriers race to deploy AI across underwriting, claims, customer service, distribution, and operations, a clear pattern is emerging. The organizations generating the most value from AI are often the same organizations that have invested in modernizing their technology, data, and operating models.

In other words, AI readiness has become the new modernization maturity.

The insurance industry has spent the better part of a decade modernizing infrastructure. The next decade will be defined by what insurers do with it.

Legacy Systems Are Slowing Insurance AI Readiness

One of the clearest findings from our research was how deeply legacy technology remains embedded across the industry.

What the research showed: Nearly half of insurers reported operating policy administration systems that are 6 to 10 years old, while nearly a quarter reported systems more than a decade old. More than half said they continue to maintain between six and 15 mission-critical COBOL modules supporting core business processes. At the same time, most organizations expect modernization efforts to continue for another 3 to 7 years.

Historically, insurers viewed these systems primarily as operational challenges. Legacy environments increased maintenance costs, slowed project delivery, and made integration more difficult.

Today, those same constraints have become barriers to AI adoption and scale.

Modern AI capabilities depend on connected data, flexible architectures, interoperable systems, and the ability to rapidly deploy new workflows. Legacy environments were never designed with those requirements in mind.

This challenge is becoming increasingly visible in customer-facing areas of the business. Insurers recognize the value of delivering more personalized experiences, but many remain constrained by technology environments that make it difficult to activate customer data at scale.

The result is that technical debt is increasingly becoming competitive debt.

Organizations that once viewed modernization as a long-term efficiency initiative are discovering that it’s become a prerequisite for innovation. AI may be the catalyst creating urgency, but legacy technology remains the obstacle standing in the way.

Innovation isn't underfunded—it's trapped

One of the most revealing findings from our research involved technology spending.

What the research showed: More than half of insurers reported spending between 51% and 75% of their IT budgets on "keep-the-lights-on" activities. At the same time, 52% said they had delayed or canceled two to three strategic technology initiatives during the previous year because of budget constraints.

Most organizations understand the need to invest in AI, analytics, and automation. Yet many are simultaneously supporting aging systems that consume the majority of their technology budgets.

The challenge is not a lack of investment appetite. Rather, modernization and innovation are often competing for the same resources.

Many insurers remain trapped in a legacy tax cycle. Aging systems require ongoing maintenance. Maintenance consumes budget. Budget constraints delay modernization initiatives. Delayed modernization increases future maintenance costs.

AI is forcing organizations to confront this cycle more directly, and the carriers making the most progress are increasingly treating modernization and AI as a single investment strategy rather than separate initiatives.

This is why modernization discussions can no longer focus solely on infrastructure upgrades or cloud migrations. The real question is whether those investments are creating the foundation necessary to support future innovation.

AI Readiness Is the Future of Insurance Modernization

For years, modernization maturity was measured by cloud adoption, digital capabilities, and progress toward replacing legacy systems.

Today, those measures are necessary but insufficient.

In the age of AI, maturity is increasingly defined by an organization's ability to turn data into decisions, deploy new capabilities quickly, and scale innovation across the enterprise.

Our modernization research identified a consistent pattern: Insurers that outperform their peers are not distinguished by technology investments alone but by their ability to convert those investments into faster decisions, greater adaptability, and sustained competitive advantage.

The insurers that lead the next decade will be the organizations that have built trusted data foundations, reduced operational drag from legacy systems, aligned business and technology priorities, and created the organizational capacity to embrace change.

AI readiness is not separate from modernization; it’s modernization's next chapter.