Hi everyone,
Here is what we learned from you during the Product Breakout Rotation. Thank you again for your insights and feedback. We look forward to continuing the conversation!
Warmly,
Kim Johnson and Jackie Booth
Stay in Touch with Your Breakout Session Team!
Jake Carr, Karen Chiappinelli, Mike Cummings, Keith Eisenhart, Sarah Hudson, Kristin Joyce, Val Labarba, Sandee Lindorfer, Max Malaret, and Shane Simonelli
AI Adoption Varies Widely
Most carriers are experimenting with AI tools like ChatGPT, Copilot, and internal search agents. However, adoption is strongest among business analysts and leaders—it’s not yet fully integrated into adjuster workflows due to data privacy, workflow complexity, and regulatory barriers.
Workflow Integration Is Key
Adjusters need AI tools embedded directly within their claims systems. Having to export data (Ex: printing claims, uploading PDFs, or using separate portals) prevents real-time efficiency and scalability.
Documentation Is the Top Pain Point
Adjusters spend 1-3 hours daily documenting claims. Automating conversation summaries and integrating them directly into claim files is viewed as one of the most valuable opportunities for AI.
Quality Assurance (QA) and Auditing Are Ripe for Automation
Carriers currently audit fewer than 5% of claims manually. Automating file audits, error detection, and compliance triggers in real time could dramatically improve quality, consistency, and regulatory readiness.
Omni-Channel Efficiency is a Shared Goal
Carriers seek seamless integration across email, text, voice, and web chat to eliminate manual duplication and improve the customer experience. Email remains the dominant channel, but texting and chat are gaining ground—especially during CAT events.
Automation Opportunities Identified
“Slam-dunk” use cases include FAQs (billing, payment status), document verification, rental management, and photo submission workflows. Complex tasks like coverage or liability discussions remain human-led.
Regulatory and Fraud Concerns Are Major Barriers
Executives cited risks around fraud (Ex: AI voice impersonation) and compliance explainability. Regulatory transparency and governance frameworks must mature before deploying AI-driven decision-making at scale.
Next-Best-Action and Proactive Alerts Desired
Leaders want systems that can flag key phrases or context (Ex: attorney mentions, delays, rental extensions) to guide adjusters toward the right next step—preventing escalations and improving timeliness.
Need for Smarter Supervisory Tools
Frontline managers struggle to monitor message professionalism, claim prioritization, and escalations. AI could support coaching, “review my message” tone checks, and surface claims that need attention.
