VP of Claims
Catastrophe Response
What You Do Today
Activate and manage the catastrophe response when a hurricane, wildfire, or severe weather event hits — deploying adjusters, managing surge capacity, coordinating with vendors, and communicating with regulators and media.
AI That Applies
AI-powered catastrophe response tools that estimate claim volume from event severity data, optimize adjuster deployment, and auto-triage incoming claims by likely severity.
Technologies
How It Works
The system ingests event severity data as its primary data source. Predictive models fit to historical outcome data identify which variables are the strongest leading indicators, then apply those weights to current inputs to generate forward-looking scores. The results integrate into the practitioner's existing workflow — presenting recommendations, flags, or automated outputs alongside their normal working context. The leadership under pressure.
What Changes
Response planning starts before the event makes landfall. The AI predicts claim volumes by geography and severity, enabling pre-positioning of adjusters and vendor activation.
What Stays
The leadership under pressure. Managing thousands of claims simultaneously while customers are displaced, adjusters are exhausted, and media is watching requires operational excellence and composure.
What To Do Next
This section won't tell you what your numbers should be. It will show you how to find them yourself. Every instruction below produces a real, verifiable result in your organization. No benchmarks, no projections — just the steps to build your own evidence.
Establish Your Baseline
Know where you are before you move
Before adopting AI tools for catastrophe response, understand your current state.
Without a baseline, you can't measure whether AI actually improved anything. You'll adopt tools without knowing if they're working.
Define Your Measures
What to track and how to calculate it
Time per cycle
How to calculate
Measure how long catastrophe response takes end-to-end today, then after AI adoption.
Why it matters
The most visible improvement is speed. If AI doesn't save time, question whether it's adding value.
Quality of output
How to calculate
Track error rates, rework frequency, or stakeholder satisfaction scores before and after.
Why it matters
Speed without quality is just faster mistakes. Measure both.
Start These Conversations
Who to talk to and what to ask
your board chair or lead independent director
“What data do we already have that could improve how we handle catastrophe response?”
They shape expectations for how AI appears in governance
your CTO or CIO
“Who on our team has the deepest experience with catastrophe response, and what tools are they already using?”
They own the technology infrastructure that enables AI adoption
a peer executive at a company further along on AI adoption
“If we brought in AI tools for catastrophe response, what would we measure before and after to know it actually helped?”
Their lessons learned are worth more than any consultant's framework
Check Your Prerequisites
Confirm readiness before you invest
Check items as you confirm them.