Guide

How to prepare an AI usage review

Prepare a board-ready AI usage review with spend, adoption, shadow AI findings, blind spots, and prioritized next actions.

A useful AI usage review gives leadership a forwardable snapshot of spend, adoption, risk, and blind spots without pretending the picture is complete.

Show totals with signal labels

The first page should show AI spend and usage totals by signal quality. A single blended number is easier to read but easier to misinterpret. Signal labels make the report honest.

Surface shadow AI findings

Expense and card data often reveal tools that never passed through IT. Flag vendors that appear risky, unmanaged, recurring, or tied to personal accounts so owners can review them.

End with three next actions

The review should not become a data dump. It should end with concrete actions such as upload expense evidence, connect a provider, assign owners to risky tools, or review departments with weak coverage.

Key takeaways

  • Show total AI spend with signal labels.
  • List shadow AI tools found through card or expense evidence.
  • Name blind spots explicitly.
  • End with three concrete next actions.

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