AR
AI ROI Audit
🔵 Stable 🕐 updated 2026-07-02
🔷 SkillSpec L3
pm-aiwork
Audit whether the organisation's AI spend actually paid — measured against baselines, not vendor math or vibes. Use when a CFO asks what the AI tools returned, when renewing AI contracts, when consolidating overlapping AI subscriptions, or to build the measurement plan before the next spend. Produces an ROI audit with per-tool verdicts (keep/consolidate/cut), the honest-measurement method behind each number, and a baseline plan for whatever can't be scored yet. To forecast ROI before an investment use roi-estimator; this skill measures what already happened.
What to give it
▸ The AI tool inventory with costs — subscriptions, API spend, seats — and utilisation if known
▸ What each tool was bought to do — the promised outcome, from the original business case if it exists
▸ Available evidence — usage data, before/after metrics, time studies, quality data, anecdotes (labelled as anecdotes)
▸ The decision at stake — renewal? consolidation? budget defence? (calibrates depth)
✅ The bar it holds itself to
Every skill in this library self-verifies — these are this skill's own quality checks, straight from its definition.
✓ Every figure carries its measurement method and confidence — no naked numbers
✓ Self-reported savings are discounted and labelled as self-reported
✓ Hidden costs appear as line items, not a caveat sentence
✓ Time→money conversions state the loaded rate and the capacity-vs-cash claim
✓ Every "unknown" has a baseline plan with a date — the audit compounds
⚠️ What it refuses to do
Do not use adoption or engagement as return — usage is a cost signal until an outcome moves
Do not accept vendor ROI calculators as evidence — reconstruct from your own data or score it unknown
Do not average across tools into one triumphant number — the verdict is per-tool or it decides nothing
Do not claim headcount avoidance without the counterfactual hiring plan that was actually cancelled
Do not punish honest "unknowns" by cutting them reflexively — cut requires a *failed* measurement attempt, not a missing one
Install
npx pm-claude-skills add --agent claude # or codex · cursor · gemini · hermes
# or one-line MCP (every skill, any client):
claude mcp add pm-skills -- npx -y pm-claude-skills-mcpRelated skills
🔌 Embed this skill
Drop this on your blog, docs, or site — it renders a "Run this skill" card:
<div data-pm-skill="ai-roi-audit"></div>
<script src="https://mohitagw15856.github.io/pm-claude-skills/embed.js" async></script>💬 Discussion