AI for insurance
The quote that arrives second already lost.
Most carriers quote only half the submissions they receive. Manual intake and rekeying across portals consume the day while faster competitors close the deals. Speed to quote is the single highest-leverage capability in commercial insurance.
from submission to quote-ready
weeks to first value
loss ratio improvement
The forces working against carriers and brokers right now
Operational friction and market shifts are compounding. These pressures reward the teams that move first.
Manual rekeying across portals
Underwriters and brokers spend hours rekeying the same data between submission systems, rating platforms, and policy admin. Every portal means another round of copy-paste.
Slow quoting loses business
Most carriers quote only about half the submissions they receive. The rest expire or go to a faster competitor. Speed to quote is speed to revenue.
Personalization gap widens
74% of insurance customers want personalized offerings, but only 44% feel their insurer delivers. The expectation bar keeps rising while legacy systems hold teams back.
The technology gap is compounding
64% of agencies already use AI for quoting, with early adopters compressing quote times by 60-99%. Carriers still running manual workflows are structurally locked into legacy costs that consume 14% of operational budgets on error correction alone. The capability gap widens every quarter.
What we hear
If your team spends the day rekeying data into portals, they are missing revenue-generating activities.
We cut over 90% of the rekeying our underwriters were doing.
A simple quote should not take three days, but ours does.
Six ways to win your quarter back
Each targets a real drag on underwriting and servicing operations, from quoting speed to renewal retention, plotted by the impact it creates against the effort to stand it up. Upper-left is the most return for the least lift.
Quoting automation
A standard quote takes 2–3 days of manual data gathering, rekeying, and rating across systems.
Where a person stays. An underwriter reviews and approves every quote; the system handles the data assembly, not the risk judgment.
Time-to-value estimates draw on published deployments and are indicative only. Every organization's data, systems, and starting point are different.
What would your team do if quoting took hours instead of days?
The biggest gains come from eliminating rekeying and manual data assembly, the work that scales with submission volume rather than underwriting expertise.
Quoting
Data gathering, rating, proposal
Rekeying
Portal-to-portal data entry
Underwriting processing
Submission triage and analysis
Claims routing
Intake, classification, assignment
Most carriers channel those hours into quoting more submissions, improving risk selection, and deepening broker relationships.
What tends to move
Loss ratio improvement
Better risk selection and faster identification of adverse trends improve underwriting results.
source ↗New business premium growth
Quoting more submissions and retaining 5–10% more brokers compounds into top-line growth.
Quote capacity with 60% faster cycle time
The same team handles significantly more submissions without adding headcount.
Customer churn reduction
Proactive renewal engagement and personalized coverage close the retention gap.
source ↗Ranges from published deployments and industry studies; your starting point sets where you land.
What would your book look like if you quoted every submission?
Tell us how your underwriting runs today and we'll map where AI actually fits, and where it honestly doesn't, for your setup.