Practical guides for insurance call centers
Short, sourced explainers for the people who run the floor. Each one answers a real question. How to measure the work after the call, what to ask an AI vendor, how recording and capture actually connect, and why a record should trace to the call instead of being guessed. No fluff, no fake posts.
How to use these guides
These are reference pages, not a blog. Each guide states the question, gives you the plain-language answer, and cites where the numbers and standards come from so you can check them yourself. Read the one that matches the decision in front of you.
- Sizing the paperwork problem on your own floor
- Building a short list of AI vendors to compare
- Deciding how calls get captured into your systems
- Explaining to your team why a record can be trusted
The guides
Five questions floor leaders ask before they change anything. Start anywhere.
A buyer's guide to AI for insurance call centers
What to actually evaluate before you buy: where the work happens today, what runs on your existing dialer and CRM, and where a person stays in the loop. Contact-center and customer-service automation is among the most common AI uses organizations report, per McKinsey, so the question is no longer whether to look, it is how to compare honestly.
How to measure after-call work on your floor
After-call work, or ACW, is the wrap-up an agent does before the next call: notes, CRM updates, forms, dispositions. You measure it as total ACW time divided by total calls, and industry benchmarks put it at roughly 6 to 12% of an agent's paid time, higher on compliance-heavy lines. This guide shows how to pull that number from your own data.
Questions to ask an AI call-center vendor
A short list drawn from the NIST AI Risk Management Framework, which names valid and reliable, accountable and transparent, and explainable as traits of trustworthy AI. Ask for evaluation artifacts, who owns the data, where a human approves, and how you exit cleanly. A vendor who cannot answer these is the answer.
Choosing your capture tier: SIPREC, recordings, or locked box
How a call reaches your systems decides what is possible. SIPREC is the IETF standard (RFC 7866) for streaming live call media to a recording server, while a stored recording is simpler to connect. Recording-consent law varies by state between one-party and all-party rules, so this guide pairs each capture option with what it asks of you.
What "provenance, not generation" means and why it matters
A hallucination is a confident answer that is not grounded in a true source, which IBM calls a lack of groundedness. Grounding the model in real call data reduces that risk but does not erase it, so a regulated record should trace to a moment in the call, flag anything unsure, and move only after an agent approves. That is provenance over generation.
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- Voiso, "After Call Work (ACW): Definition, How To Measure It." ACW formula and the 6 to 12% of agent-time benchmark. voiso.com
- NIST, "Artificial Intelligence Risk Management Framework (AI RMF 1.0)." Characteristics of trustworthy AI used to frame vendor questions. nist.gov
- IETF, RFC 7866, "Session Recording Protocol" (SIPREC). The standard for streaming live call media to a recording server. rfc-editor.org
- Justia, "Recording Phone Calls and Conversations (50-State Survey)." One-party vs all-party consent rules by state. justia.com
- IBM, "What Are AI Hallucinations?" Hallucination as a lack of groundedness; grounding reduces but does not eliminate it. ibm.com
- McKinsey, "The State of AI" 2025. Contact-center automation among the most common AI uses reported. mckinsey.com