Insurance companies are increasingly adopting agentic artificial intelligence (AI) systems that automate workflows across claims, underwriting, and policy servicing. Unlike traditional automation, these systems can process unstructured data (emails, PDFs) to extract coverage and risk information, enabling them to automatically route tasks to human adjusters or initiate actions like payments.
In claims operations, AI enhances the intake and triage process, minimizing manual review bottlenecks and improving customer experience. Companies like Sedgwick and Allianz leverage AI to optimize claims workflows and manage surge responses, respectively. Underwriting also benefits, as AI systems can analyze broker submissions, extract risk data, and ensure consistency in decision-making, thereby improving risk assessment speed and quality.
However, with widespread AI orchestration in insurance, regulatory scrutiny increases. Insurers must navigate model risk management frameworks, ensuring decisions are documented and transparent, as oversight becomes essential when AI systems trigger actions affecting multiple functions.
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