VP of Distribution
Manage agent and broker relationships and performance
What You Do Today
Oversee relationships with hundreds or thousands of independent agents and brokers. Track production by agency, manage appointments, and ensure top producers feel valued while addressing underperformers.
AI That Applies
Agent performance analytics with predictive models identifying which agencies are likely to grow, decline, or leave, enabling proactive relationship management.
Technologies
How It Works
For manage agent and broker relationships and performance, the system draws on the relevant operational data and applies the appropriate analytical models. The processing layer applies the appropriate analytical models to the structured data, generating scored outputs that surface the most actionable insights. The output — proactive relationship management — surfaces in the existing workflow where the practitioner can review and act on it.
What Changes
You'll know which agents need attention before they tell you. AI predicts production shifts based on quoting activity, mix changes, and market conditions.
What Stays
Agent relationships are built on trust, responsiveness, and personal connection. Top producers work with carriers whose people they trust, not just whose tools are best.
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 manage agent and broker relationships and performance, 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 manage agent and broker relationships and performance 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 manage agent and broker relationships and performance?”
They shape expectations for how AI appears in governance
your CTO or CIO
“Who on our team has the deepest experience with manage agent and broker relationships and performance, 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 manage agent and broker relationships and performance, 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.