Insurers possess extensive data and analytical expertise, yet only seven percent have reportedly scaled AI effectively across their organisations. Legacy systems, fragmented information, specialist shortages, and organisational resistance keep promising pilots from becoming everyday operations.
Agentic AI offers a different proposition from a chatbot. An agent can move a claim through several steps—capturing the first notice of loss, requesting documents, updating systems, and telling the customer what happens next.
The operational shift is from routing work toward resolving bounded portions of it under human supervision.
Claims Work Offers Measurable Agent Value
Sedgwick and Microsoft developed Sidekick Agent to provide real-time guidance to claims professionals, improving processing efficiency by more than 30 percent according to the source.
Another major insurer deployed more than 80 models in claims. It cut liability assessment for complex cases by 23 days, improved routing accuracy by 30 percent, and reduced complaints by 65 percent.
These metrics show why claims is attractive. Cycle time, routing, documentation, customer updates, and complaints are observable, while professionals remain available for exceptions and judgment.
An agent should not optimise speed at the expense of fair assessment. Claims involve vulnerable customers, uncertain facts, policy interpretation, fraud concerns, and financial consequences. Escalation must be easy and accountability clear.
Resolve, Not Route, Requires System Access
Conventional chatbots answer a question or transfer the customer. An agent completes connected tasks across policy, billing, claims, documents, and communications.
That capability depends on identity resolution, reliable data, least-privilege permissions, and interfaces into legacy systems. An agent that sees only part of the record may resolve the wrong problem faster.
Actions should be separated by risk. Collecting missing information may proceed automatically; determining liability, changing coverage, or releasing a significant payment may require professional approval.
Complete logs need to show data sources, decisions, tool calls, approvals, and customer messages. Monitoring should identify drift, uneven outcomes, and situations where employees repeatedly override the recommendation.
Organisational Readiness Is the Larger Barrier
The source attributes roughly 70 percent of scaling challenges to organisation rather than technology. Siloed teams, unclear priorities, and scarce actuarial or underwriting talent slow adoption.
An AI centre of excellence can provide shared governance and technical expertise, reducing fragmented experiments. Industry accelerators and prebuilt frameworks may shorten implementation when adapted to the insurer’s processes and controls.
Centralisation should not remove business ownership. Claims leaders, underwriters, service teams, compliance, security, and technology functions need common outcomes and authority to stop unsafe deployment.
Starting with high-volume, repeatable work creates feedback and operating experience. Expansion should follow evidence that quality, customer outcomes, and employee workload improved alongside cost.
Claims also expose the limits of averages. A system may reduce overall handling time while performing poorly for unusual losses, vulnerable customers, or disputed coverage. Insurers should segment outcomes and preserve an accessible human route for exceptions. Operational efficiency earns trust only when people with the hardest cases are not forced through an automated process designed for the simplest ones.
The insurance sector faces sustained financial pressure, including annual losses above $100 billion for six consecutive years according to the source. Agents cannot solve structural property risk, climate exposure, or pricing by themselves. They can reduce the operational cost and delay surrounding each case.
That distinction keeps the strategy honest. Agentic AI is not necessary because it is fashionable; it becomes useful when it resolves a real process more consistently than a fragmented handoff.
Insurance leaders should judge the technology by complete claims outcomes. A faster automated step matters only if the customer receives a fair decision sooner, employees can explain it, and the company spends less handling the case from first notice to closure.
