AI is changing everything—including how insurers define and deliver quality.
When I began my career in insurance more than 30 years ago, insurance QA teams operated deep in the back office. Their primary role was to feed into performance reviews by documenting leakage, missed steps, or underwriting oversights. Insurance quality assurance was checklist-driven, and a passing score didn’t always reflect a job well done.
The focus was on what got done, not how it was done. A question like “Was contact made within 24 hours?” might earn a checkmark, but it missed the point: Was that outreach appropriate given the customer’s situation? Was it helpful? I still remember reviewing a file with a perfect score—only to see a complaint later filed with the Department of Insurance. It was a wake-up call: the audit program wasn’t showing us the full picture.
I’m not here to dwell on the past—but to understand where we’re headed, we need to know where we started.
The Traditional QA Model
Before AI, quality programs in insurance tended to follow a familiar pattern:
- Purpose: Primarily used for individual performance management
- Sample Size: A small slice—typically 3–5 files per month or 5% of work
- Audience: Direct managers, supervisors, and their teams
- Impact: Focused on a single domain (Claims, Underwriting, Service)
- Criteria: Mostly random selection with some targeted audits
- Results: Scores rarely below 80; feedback often limited to coaching
If this sounds familiar, you’re not alone—many organizations still operate this way. But AI-powered QA is ushering in a new era of quality, one that goes far beyond scores and file reviews.
The AI-Powered QA Evolution
Today, AI is helping insurance carriers move from basic audits to conversation intelligence, and from isolated metrics to enterprise insight. It’s not just about compliance anymore. It’s about connection, context, and continuous improvement.
Modern insurance QA programs enhanced by AI look very different:
- Purpose: Broader insight. Teams can now analyze trends, uncover process friction, and solve real business challenges
- Sample Size: Limitless. Every call, chat, email, and bot interaction can be reviewed
- Audience: Organization-wide. Insights benefit product, operations, compliance, and customer experience teams alike
- Impact: Cross-functional. Findings lead to root cause analysis and systemic improvements
- Criteria: Targeted reviews aligned with strategic priorities, not just checklists
- Results: Deep issues are uncovered, coaching becomes more effective, and playbooks evolve in real time
We’re no longer just asking “Did the rep do the thing?” We’re now exploring how well it was done, why issues arise, and what we can do to fix them—for good.
By leveraging AI powered QA Software, insurance carriers are developing more effective insurance compliance solutions that actually reflect the customer experience and support operational improvements across the board.
🚀 Request a demo to discover how AI-powered QA can elevate your compliance, improve claims accuracy, and unlock insights across your organization.
What’s Next
In our next post, we’ll share how leading carriers are making the leap from traditional audit teams to fully integrated QA Centers of Excellence.
%201.svg)
.jpeg)
.jpg)
.jpeg)
.avif)
.avif)
.avif)
.avif)
.avif)
.avif)
.jpeg)
.jpeg)
.jpeg)
.jpeg)
.jpeg)
.jpeg)
.jpeg)
.jpeg)
.jpeg)
.jpeg)
.jpeg)
.jpeg)
.jpeg)
.jpeg)
.jpeg)
.jpeg)
.jpeg)
.jpeg)
.jpeg)
.jpeg)
.jpeg)
.jpeg)
.avif)
.avif)
%2520(1)-p-800.avif)
.avif)
-p-500.avif)
%2520(1).avif)
.avif)
.avif)
%2520(1).avif)
.avif)
%2520(1).avif)
%2520(1).avif)
%2520(1).avif)
.avif)
%2520(1).avif)
%2520(1).avif)
.avif)
%2520(1).avif)
.avif)
.webp)
.jpeg)
.jpeg)
.jpeg)
.jpeg)
.avif)
.jpeg)
.jpeg)
.jpeg)
.avif)
.avif)
.avif)
.jpeg)
