Timeline
10-15 working days
AI ROI Audit
Find the AI use cases that deserve budget.
A focused audit for leaders who need to prove where AI creates measurable value, where usage is just activity, and what should be funded next.
The AI ROI Audit starts with a definition: ROI is verified value after full cost, quality, review, risk, and ownership are counted. Usage alone is not return.
Details
Indicative price
€6k-€18k depending on scope and data access
definition
Definition
The AI ROI Audit starts with a definition: ROI is verified value after full cost, quality, review, risk, and ownership are counted. Usage alone is not return.
who
Who it is for
This page is for leaders, finance, operations, and IT teams that already have visible AI usage but not enough evidence to decide.
framework
Framework
We use the Four Leaks of AI ROI: spend, adoption, leaks, and role drift. Every signal is tied to a cost, an owner, and a decision.
deliverables
Deliverables
- AI use-case inventory with owner, cost, risk, and value hypothesis
- AI Waste Index and domain scores
- ROI evidence map by workflow
- Stop, fix, scale recommendations
- Board-ready 30/60/90 roadmap
sample-report
Sample report
Executive one-page with waste index, dominant leak, value hypothesis, and recommended next move.
Appendix with workflow evidence, cost assumptions, risks, and decisions to stop, fix, or scale.
timeline
Timeline
10-15 working days
price-band
Price band
€6k-€18k depending on scope and data access
objections
Common objections
- If you already measure ROI, the audit validates the evidence instead of repeating it.
- If your data is messy, the audit begins with the decision log and cost trail that exist today.
- If the team fears cuts, the framing is value recovery, not tool punishment.
Deliverables
- AI use-case inventory with owner, cost, risk, and value hypothesis
- AI Waste Index and domain scores
- ROI evidence map by workflow
- Stop, fix, scale recommendations
- Board-ready 30/60/90 roadmap
Objections
- If you already measure ROI, the audit validates the evidence instead of repeating it.
- If your data is messy, the audit begins with the decision log and cost trail that exist today.
- If the team fears cuts, the framing is value recovery, not tool punishment.
FAQ
Do we need perfect data first?
No. The audit separates available evidence, reasonable assumptions, and the measurements to install next.
Is this a technical project?
Not first. The starting point is the business decision: cost, value, risk, owner, and stop threshold.
Will teams have to stop using their tools?
Only when a use case proves nothing or exposes too much. Useful tools are protected and measured better.
What happens after the audit?
You leave with a decision: stop, consolidate, fix, scale, or govern each priority use case.
AI ROI Audit