Why AI Alone Wonât Fix Cross-Sell in Insurance
In todayâs hyper-competitive insurance market, customer acquisition costs are rising while margins remain thin.
That makes one growth opportunity more important than ever: existing customers. Yet many carriers still overlook it.
The gap is striking. Research shows that eight out of 10 insurance customers never buy another product after their initial purchase, even though 91% say they would consider bundling all their policies with one provider.
In other words, the appetite is there. The follow-through is not.
That failure is especially notable at a time when AI promises to make personalisation far more precise.
McKinsey estimates that AI could unlock US$50bn to US$70bn in revenue for the insurance industry, with the largest gains in marketing, sales, customer operations and software engineering.
Most carriers have already invested in analytics, decisioning tools and recommendation engines meant to identify the next best action.
So why does cross-sell still fall short? Not because insurers lack ambition, or even technology, but because the data behind those systems is often fragmented, incomplete or out of date.
That is where cross-sell starts to break down.
Why AI underperforms in insurance
AI has become one of insuranceâs most promising growth levers, helping carriers improve targeting, personalise outreach and recommend the right offer at the right time.
Bain & Co found that AI can increase cross-sell revenue by up to 25% and improve marketing effectiveness by 10 times.
But AI is only as effective as the data behind it.
At most carriers, customer information is fragmented across policy, claims, billing, CRM, marketing and agency systems.
Each holds part of the story, but few insurers can connect those pieces into a complete, current view.
As a result, AI lacks the context it needs.
A customer may look like a home-only policyholder in one system while a spouseâs auto policy sits elsewhere under a slightly different name.
A claims event may reveal a new coverage need, but the signal never reaches the right channel in time.
The result is familiar: strong technology, weak outcomes. Many insurance AI initiatives show promise in pilots but struggle to create value at scale.
The missing layer: Trusted, unified data
Better cross-sell does not begin with a better model. It begins with a more reliable view of the policyholder and the household.
That requires trusted, unified data.
When insurers connect policyholder, household, claims and product data across the enterprise, they can see what customers already hold, how they are connected and where meaningful coverage gaps exist.
Because insurance is often a household business, visibility matters. It helps carriers spot bundling opportunities, improve recommendations and act with greater precision.
Without it, AI is often guessing. With it, AI can finally deliver on its promise.
The second version is cleaner and more forceful.
From data visibility to action
The real value of trusted data is not simply that it cleans up records. It is what makes AI recommendations more actionable in the moments that matter.
When data is unified and current, AI models can evaluate cross-sell opportunities using real coverage information, household relationships, claims activity, renewal timing and other relevant context.
That helps reduce false positives, cuts down on irrelevant offers and improves the timing of outreach.
Just as importantly, those insights can be embedded into the systems agents, producers and service teams already use.
That means that when a user opens an account, they are not forced to manually assemble the customer story across multiple systems.
They can see a more complete view of the household, active policies, upcoming renewals, recent interactions and a recommendation tied to an actual need.
An alert might indicate that a household has multiple existing policies, significant assets and an upcoming renewal window, making it a strong fit for umbrella coverage.
That is not just a theoretical insight. It is a practical prompt that a producer can act on immediately.
This is where AI begins to move from experimentation to business impact.
A more practical path to growth
The payoff for insurers is straightforward: better-targeted cross-sell, stronger retention, more productive teams and AI investments that deliver measurable results.
But AI cannot create value from a fragmented customer view. It needs trusted, unified data to understand the policyholder, the household and the moment.
That combination helps insurers uncover hidden premiums in their existing books and turn cross-selling into a more repeatable growth strategy.
Explore the new rules of intelligent data. See how industry leaders are unifying trusted data to stay ahead in the AI era.