How to Report AI Share of Voice to the Board Without Vanity Metrics
A clear executive framework that connects AI visibility metrics to pipeline and revenue outcomes.
By Lina Brooks - Revenue Strategy Advisor
In this article
Why most AI reporting fails with leadership
Boards do not need another dashboard screenshot. They need confidence that the team can:
- identify early channel shifts,
- make decisions quickly,
- and connect efforts to business outcomes.
If your report only says "mentions increased," it will feel tactical, not strategic.
The 4-metric executive scorecard
Use one page with four metrics:
- AI share of voice in your category prompts.
- Average recommendation position for high-intent prompts.
- Positive sentiment ratio in generated answers.
- Pipeline influence from AI-assisted discovery journeys.
Each metric should include:
- current value,
- month-over-month delta,
- one sentence of interpretation.
What to stop reporting
Avoid metrics that sound advanced but do not drive decisions:
- prompt count without segmentation,
- one-model-only snapshots,
- aggregate scores with no context.
If the metric cannot trigger an action, remove it.
How to link AI visibility to pipeline
Create a simple attribution layer:
- Add "How did you hear about us?" options for AI assistants.
- Track direct traffic spikes after content pushes on target prompts.
- Correlate visibility improvements with inbound demo quality.
You will not get perfect attribution on day one, but directional signal is enough to guide investment.
Sample monthly board narrative
"We improved AI share of voice by 11 points in strategic prompts, moved average position from 5.1 to 3.9, and saw a 17% increase in qualified demos from comparison-driven pages. Next month we are prioritizing schema coverage and competitor-gap prompts where we are still under-indexed."
The leadership takeaway
Strong AI visibility reporting is not about volume of charts. It is about clarity of decisions, pace of iteration, and proof of commercial impact.