---
name: mohitagw15856/ai-roi-audit
source: https://app.decimal.ai/s/mohitagw15856-ai-roi-audit@1/SKILL.md
source_sha256: 5c44df48ccb3
---

# AI ROI Audit Skill

Every org now spends real money on AI tools, and most justify it with adoption counts ("80% weekly active!") — which measure enthusiasm, not return. This skill audits what the spend *returned*, using methods that survive a sceptical CFO: baselines, counterfactuals, and quality deltas, with "we can't know yet" said out loud where it's true.

## What This Skill Produces

- A **per-tool verdict table**: keep / consolidate / renegotiate / cut, each with its evidence
- The **measurement behind each number** — method, baseline, confidence — so the audit is checkable
- A **hidden-cost ledger** (the part vendor ROI decks omit)
- A **baseline plan** for every "unknown", so next year's audit has data

## Required Inputs

Ask for (if not already provided):
- **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)

## Audit Method

1. **Reconstruct the promise.** Per tool: what outcome justified the purchase — time saved, quality improved, headcount avoided, revenue created? A tool without a stated outcome gets audited against the best-fit guess, *flagged as retrofitted*.
2. **Score with the strongest method the evidence allows**, in descending order of credibility:
   - **Natural experiment** — teams/periods with vs without the tool, same work (best available in most orgs)
   - **Before/after with baseline** — the metric before adoption vs after, seasonality noted
   - **Task-level time study** — 10-20 real tasks timed with/without (cheap to run *during* the audit — do it rather than skip to tier 4)
   - **Structured self-report** — users estimating time saved, discounted (self-reported AI savings run ~2× actuals; say so)
   Never present a tier-4 number with tier-1 confidence. Every figure carries its method and a confidence label.
3. **Count the hidden costs.** Verification time (humans checking AI output), rework from AI errors that shipped, licence sprawl (seats bought > seats active), integration/prompt-maintenance time, and training time. These come off the gross benefit — an ROI audit that skips them is a vendor deck.
4. **Convert honestly.** Time saved → money only via a stated loaded rate *and* a stated assumption about what the time became (more output? earlier finishes? — different values). "Saved 400 hours" that nobody redeployed is capacity, not cash; label which one you're claiming.
5. **Verdict per tool.** Keep (positive with tier ≤2 evidence) · Consolidate (positive but duplicative — name the overlap) · Renegotiate (positive but mispriced vs utilisation) · Cut (negative or unmeasurable after a fair baseline attempt). Ties break toward the tool with a measurement plan.
6. **Leave the audit better than you found it.** Every "unknown" verdict gets a baseline plan: the metric, how it's instrumented, and the review date. The first audit is mostly this; that's a finding, not a failure.

## Output Format

### AI ROI Audit: [org/team] — [period]

**Total AI spend:** [sum] · **Verdict summary:** [n keep / n consolidate / n renegotiate / n cut / n unknown]

| Tool | Annual cost | Promised outcome | Measured return | Method (tier) | Confidence | Verdict |
|---|---|---|---|---|---|---|

**Hidden-cost ledger:** [verification, rework, sprawl, maintenance — quantified where possible, listed where not]

**The math shown:** [for each material number: baseline, method, conversion assumptions]

**Baseline plan for the unknowns:** [tool → metric → instrumentation → review date]

**One-paragraph CFO summary:** [net position, the two decisions to make, and what will be measurable by next audit]

## Quality Checks

- [ ] 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

## Anti-Patterns

- [ ] 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