Guide

How to explain AI coverage to leadership

A practical guide to explaining observed, inferred, enforced, and not covered AI usage to executives and boards.

Coverage is the difference between what the company can prove, what it can infer, what it can enforce, and what remains outside the map.

Coverage is not the same as usage

A company may have heavy AI adoption and still have weak coverage. Coverage explains how much of the picture comes from reliable signals and how much still depends on estimates, controls, or known blind spots.

Use four labels consistently

Observed means direct telemetry or authoritative billing evidence. Inferred means likely usage from secondary evidence such as expenses, SSO, CSV imports, or discovery data. Enforced means the path is governed by a real control. Not covered means leadership should not rely on that area for complete reporting yet.

Make blind spots board-readable

Executives do not need a technical taxonomy first. They need to know which AI spend and usage can be seen, which is estimated, which is controlled, and where the company is still exposed.

Key takeaways

  • Observed usage is directly measured.
  • Inferred usage is likely but not directly measured.
  • Enforced usage is governed by an approved control.
  • Not covered usage should be named as a blind spot, not hidden.

Turn AI evidence into a ledger.

Start with a free AI Exposure Assessment, then replace estimates with observed and inferred signals from your own workspace.

Start with the assessment