How to Build an AI Success Story in Insurance
At InsurTech Insights USA 2025 in New York, one thing was impossible to miss: AI was everywhere. For insurance carriers, that visibility can create its own kind of pressure. When every conversation and vendor booth mentions “AI”, and executive teams want to signal their technology-relevence by pushing operational teams, it is tempting to launch a AI project simply to say you have one.
At Expert,ai, we believe that’s the wrong place to start. “Before you even look at the technology, think about the issues inside your organization. Find the valid use case. Don’t just look for an excuse to deploy technology.” – Nick Carter, Senior Sales Director, Expert.ai.
How can carriers take advantage of AI in ways that deliver lasting value? This post shares key takeaways from “Targeting Insurance Distribution with Advanced Technology / Finding the Right Risk,” a panel discussion at InsurTech Insights USA 2025 where Nick Carter joined other industry leaders to explore how insurers can move beyond AI hype and focus on solutions that solve real business challenges.
Three Building Blocks for AI Success in Insurance
Every successful AI initiative in insurance rests on three essentials.
- Start with the problem
The right AI project begins by identifying a specific business challenge. Too often, carriers feel pressure to “do something with AI” without a clear reason why. However, the right use case often comes from a pain point that directly affects business performance. In a distribution context, this might mean addressing slow submissions processing from agents or finding ways to reduce market blocking. When the starting point is a well-defined problem, with measurable success criteria, the end result is far more likely to deliver value. - Scope it with the right stakeholders
Once the problem is clear, bring the right people into the conversation. If AI is limited to the IT team, you’re missing out on the perspectives of those who deal with those critical processes day in and day out. Underwriters, claim teams, operations leaders, distribution managers and compliance teams can all help shape a solution that works in practice, not just on paper. - Partner for the long run
The technology is only part of the equation. The right partner brings insurance-specific expertise and is willing to challenge your assumptions. A good vendor will help you see the bigger picture and keep the project aligned with business goals, even if that means pushing back on requests that add complexity without adding value.
In insurance, experience matters. The processes, data and regulatory considerations are too specialized for generic solutions. Expert.ai’s track record in the industry means customers can draw on proven methods for scoping, implementing and scaling AI.
Balance Automation with Human Expertise
The days of using people to manually extract data from documents should be over. This is work machines can do faster and more accurately, freeing employees to focus on higher-value activities.
But in 2025, carriers are also facing a talent challenge. Fewer new professionals are entering the industry each year, so retaining people by giving them meaningful, engaging work is vital. Automating repetitive tasks helps keep that talent engaged.
However, not every decision should be automated. Risk acceptance, claims adjudication and other high-stakes choices still require trained professionals who understand the full context: “Underwriting is a hybrid of art and science. The science is getting and serving the right data. The art is the human judgment that makes sense of it,” Carter said.
Final Takeaway: Building AI Success in Insurance
Building AI success in insurance starts with identifying the right problem, scoping it with the right people, and partnering with someone who understands the industry. When those elements are in place, technology becomes a powerful tool for delivering real business value.
