Timeline
7-12 working days
AI Waste Audit
Cut the AI spend that does not return value.
A spend and tool rationalization audit for teams with overlapping AI tools, unused seats, pilots that never end, and budget that renews by inertia.
The AI Waste Audit defines waste as paid capacity, human rework, vendor dependency, or duplicated tooling that does not improve a measured workflow.
Details
Indicative price
€5k-€14k depending on tool count and teams covered
definition
Definition
The AI Waste Audit defines waste as paid capacity, human rework, vendor dependency, or duplicated tooling that does not improve a measured workflow.
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 spend register by tool, team, owner, and renewal date
- Duplicate and dormant-seat map
- Hidden cost estimate including review and maintenance
- Consolidation and renegotiation priorities
- Savings plan with risk notes before cuts
sample-report
Sample report
Savings waterfall by subscription, seat, duplicate use case, and process rework.
Decision table for keep, consolidate, renegotiate, stop, or rebuild.
timeline
Timeline
7-12 working days
price-band
Price band
€5k-€14k depending on tool count and teams covered
objections
Common objections
- The audit does not remove tools that teams rely on without a transition path.
- Savings are separated from risk so finance does not cut the wrong control.
- The goal is fewer weak tools, not less useful AI.
Deliverables
- AI spend register by tool, team, owner, and renewal date
- Duplicate and dormant-seat map
- Hidden cost estimate including review and maintenance
- Consolidation and renegotiation priorities
- Savings plan with risk notes before cuts
Objections
- The audit does not remove tools that teams rely on without a transition path.
- Savings are separated from risk so finance does not cut the wrong control.
- The goal is fewer weak tools, not less useful AI.
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 Waste Audit