AI Agents revolutionize the claims settlement process, going beyond the limits of traditional RPA to offer insurance companies greater operational efficiency, embedded compliance, and unprecedented strategic control over workflows.
The insurance sector is at a crucial moment in its digital transformation journey, especially regarding complex policy management. As highlighted by Antonio Burinato, General Manager of Innovaway, artificial intelligence represents a unique opportunity not only because of the volume of data managed, but due to the very nature of operational processes themselves.
Today, a single claims settlement file requires cross-referencing multiple unstructured documents, such as medical certificates, notarial deeds, and policy extracts. This manual approach creates significant bottlenecks, pushing settlement times to a minimum of 30 days (according to estimates by ANIA and IVASS) and negatively impacting both operational efficiency and the customer experience.
Beyond RPA: The Rise of "Intelligent" Automation
To maintain competitiveness and profitability, process innovation is essential. In this scenario, AI Agents represent the natural evolution of automation. Unlike traditional Robotic Process Automation (RPA)—which is limited to executing rigid rules on static interfaces—AI Agents introduce "reasoning" automation. Operating autonomously, these systems can interpret unstructured content, query company databases, communicate with customers to request missing documents, and flag ambiguities for human operators, all without interrupting the workflow.
Historically, the insurance process has been structurally suited for the adoption of AI Agents due to three key characteristics:
Innovaway’s Methodology: Process Leads Technology
On a strategic level, the main obstacle to agentic AI projects is sequence error—that is, starting with technology rather than process. To ensure a genuine Return on Investment (ROI), it is essential to analyze operational processes, identify friction points, and map out a structured digital workflow before implementing the technological solution. Without this clarity, AI risks simply amplifying existing organizational inefficiencies.
Human-Machine Synergy and Business Governance
The adoption of AI Agents does not aim to replace human operators, but to enhance their role. While human work is sequential and subject to fatigue, AI Agents operate in parallel across multiple files simultaneously. This allows operators to focus on high-value tasks: managing exceptions, handling ambiguities, and making final critical decisions.
Furthermore, compliance with strict industry regulations (such as those dictated by IVASS) becomes an intrinsic, verifiable condition embedded directly within the agentic system.
Finally, the most significant strategic advantage for C-Level executives lies in governance. By cataloging agent actions within dynamic dashboards, management gains real-time visibility into claims status and operational bottlenecks. This rich data pool transforms operational oversight into a powerful lever for making faster, more informed business decisions.
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