AI for Insurance:
Cut the Admin. Free Up the Team.
Most agencies have access to AI tools — far fewer have trained their team to actually use them. The difference isn't the technology — it's structured team training. Kiingo delivers AI enablement built for insurance workflows, from CSRs to producers.
What Your Team Could Do with AI
Claims Management
Give your team better tools for the claims process — match claims to relevant coverage terms, draft carrier correspondence, and track open claims so nothing falls through the cracks.
Submission Preparation
Build complete, accurate submissions faster — extract key data from applications and ACORD forms, organize supplemental documents, and catch missing information before the underwriter sends it back.
Book of Business Review
Audit your accounts for coverage gaps, cross-sell opportunities, and retention risks — so your producers walk into every renewal conversation with a strategy, not just a price.
Carrier & Market Selection
Cross-reference loss history, exposure data, and current terms to identify which carriers are the best fit for each account — and spot renewals where it's time to go to market.
Customer Service
Handle policyholder inquiries faster and more consistently — so your team focuses on relationships, not repetitive questions.
Coverage Gap Analysis
Review policy terms against a client's actual risk profile, flag coverage gaps before renewal, and give your producers a consultative reason to reach out — not just a price comparison.
How could your team start using AI for this?
Insurance AI Prompts You Can Try Today
Want to learn how to set up AI safely, with proper context and configuration? Talk to us about joining a bootcamp.
Before You Prompt: A Quick Note on Data Handling
These prompts are designed to work with tools your agency has approved for use with client data. Before pasting submission details, loss runs, or carrier terms into any AI platform:
- Confirm the tool is on your agency's approved technology list
- Check whether your firm's AI policy requires client data to be redacted or anonymized before input
- Review the AI tool's data retention and training policies — enterprise plans (ChatGPT Team/Enterprise, Claude for Work) typically don't train on your inputs, but verify with your IT team or carrier partner
- Be aware that carrier confidentiality provisions may restrict how pricing and underwriting data can be shared with third-party tools
Don't have an agency AI policy yet? That's one of the things we help build.
[Paste your commercial insurance submission here — use your organization's approved AI tool for client data.] Extract the insured's industry classification, annual revenue, employee count, prior three-year loss history with incurred totals, expiring premium and carrier, requested coverage lines, any notable exclusions or sublimits, and unusual risk factors the broker buried in the appendix. Flag anything missing that would delay a carrier response. Return as: submission summary (one page) + missing data list + three questions to ask the broker. Note: Verify all extracted data points against the source documents before acting on this summary.
Turns a 45-minute submission review into a structured 10-minute scan — so you spend time on decisions, not document hunting.
[Paste your broker submission narrative and loss runs here — ensure your AI platform doesn't train on inputs containing claims data.] Compare them to identify where the broker's description of the account's loss history conflicts with the actual claims data — frequency trends they downplay, severity spikes they skip, or open reserves they don't mention. Note any periods where loss runs are suspiciously absent. Flag claims that closed at zero but were open for more than 120 days. Return as: conflict summary table (broker claim vs. actual data) + discrepancy summary + questions to raise before proceeding.
Catches the discrepancies that cost you a bad bind — turning a 45-minute manual cross-reference into a structured first pass.
[Paste the renewal terms for this account here — confirm this data is handled per your agency's AI use policy. Include rate changes, coverage modifications, and new exclusions or conditions.] Predict the top five questions or concerns the client will raise, ranked by likelihood. For each, explain the business rationale behind the change and draft a response that acknowledges the concern while explaining the rationale. Identify the one term most likely to trigger a request to remarket. Return as: concern-response pairs + the single concession that would cost the least but matter most to the client + alternative coverage structures or market options if the client pushes back on terms.
Turns "I'll follow up on that" into "here's exactly why" — so you walk into every renewal meeting with prepared, data-backed responses.
All prompts should be used in accordance with your agency's AI usage policies, applicable state insurance regulations, and any carrier confidentiality agreements. AI outputs are starting points requiring professional review — they do not constitute underwriting decisions, coverage opinions, or completed work products.