From Claims to Customer Questions: How AI Agents Help Insurers

In this article, Product Marketer Tom Faas and AI Strategist Thomas van Manen share the customer service challenges they see in the insurance sector, and how AI agents help make customer interactions faster, smarter, and more efficient.

Why does the insurance industry benefit from AI agents?

“In insurance, customer contact doesn’t stop once a policy is signed. In fact, that’s often when it really begins,” says Thomas. “Customers return with questions about coverage, how to file claims, or how to make changes. And because policy terms are complex, challenges are plentiful, and information is scattered across multiple systems, it’s difficult to quickly provide a clear answer.”

AI agents speed up that process. Tom explains: “They can instantly retrieve policy conditions, combine them with customer data, and deliver a personalized response on the spot. On top of that, they can initiate processes such as creating a claim file. That saves employees a lot of time and allows them to focus on more complex cases.”

Beyond information delivery, what other challenges do insurers face?

Thomas: “Besides the complexity of accessing information, communication is often fragmented. Customers reach out through different channels, but because conversations aren’t centrally stored, context is lost and customers end up repeating themselves.”

Outdated IT systems add to the problem. “A large share of administrative work, like registering claims or collecting supporting documents, is still done manually. And integrations with legacy systems are often difficult, which slows down innovation. It’s a huge drag on employee productivity.”

In what ways can insurers apply AI agents?

“The real power of AI agents lies in their versatility,” Thomas says. “They can take over customer-facing tasks, support employees, and automate internal processes.”

According to Tom, handling individual customer requests is one of the most impactful use cases. “AI agents answer policy-related questions on a personal level, without forcing customers to wade through endless FAQ pages. They can also file claims, request supporting documents, and schedule next steps. That dramatically speeds up case handling.”

Thomas highlights the administrative benefits as well: “Many routine tasks can be prepared—or even fully automated—by AI agents. They gather information, check documents, run fraud checks, and log every action in the right system. Manual retyping becomes a thing of the past.”

Tom adds that AI agents should not be seen as replacements but as support for employees. “Their role is to take repetitive work off people’s plates, so employees can focus on tasks that truly require human judgment—like assessing complex or sensitive cases, providing personal advice, and supervising AI agents. By combining human expertise with AI technology, you create a hybrid model where both reinforce each other.”

How does HALO help insurers use AI with confidence?

In a sector where privacy and accuracy are critical, implementing AI can feel daunting. “That concern is understandable, but HALO is built on strict security and governance standards. You decide who can edit agents, who can view conversations, and who can access customer data or connect tools. All data exchange is encrypted, and every change to an agent or workflow is logged.”

How does HALO ensure you stay in control of your AI agents?

“With HALO you always have full visibility into what an agent does,” Tom explains. “Every interaction is logged and backed up with source references, so you can see exactly which information an answer is based on.” AI agents also work only with your own documentation and customer data—never with open internet sources. This ensures responses are reliable, consistent, and up-to-date. “That way, service quality remains high, and confidence grows to also apply AI agents to more complex tasks.”

What advice would you give insurers who want to start with AI agents but face internal resistance?

Tom: “Start small—try something like an internal knowledge base agent first. Employees will immediately experience the benefits. Once the added value is clear, you can scale up to customer-facing use cases, like answering personalized policy questions or handling claims.”

Thomas adds: “By expanding step by step, you build a strong business case and gain internal support. That makes it much easier to drive larger transformations and apply AI more broadly.”