AI ROI diagnostic sample report

A public sample report showing the waste index, dominant leak, levers, roadmap, and next-page routing used by the diagnostic.

The sample does not promise a magic score. It shows the shape of a useful deliverable: waste index, dominant leak, operating levers, confidence limits, and a recommendation leadership can discuss without rebuilding the analysis.

Scores summarize four signal families: spend, adoption, leaks, and role drift. A low score is not a verdict; it shows where evidence is missing or where the workflow does not yet have enough control.

The value of the report is tying each score to a possible decision. The reader should understand what can stop quickly, what needs more measurement, and what deserves reinforcement despite visible cost.

The complete diagnostic asks for real examples: paid tools, workflows involved, reviewer roles, past decisions, open risks, and field symptoms. The public sample shows how those signals become usable analysis without exposing sensitive data.

• Use-case inventory
• Costs and renewals
• Quality and rework
• Risk and owner
• Expected decision and review threshold

Each dominant leak points to the closest page, resource, and use-case family. Routing avoids answering every problem with the same audit: a spend leak, a shadow AI leak, and role drift do not need the same first move.

The right next step depends on the priority signal: recover budget, install policy, review quality, clarify roles, or build a broader roadmap. The report narrows the field instead of opening every workstream at once.

Aggregate signals do not contain lead contact details. The goal is to build a collective view of AI waste without turning individual diagnostics into identifiable publication material.

That separation matters for trust. Personal answers support the report and possible follow-up; anonymous trends improve the model and, over time, support useful market distributions.

Use the sample as a reading grid before completing the diagnostic. If a section feels impossible to answer, that is already a signal: the company may lack a baseline, tool register, quality threshold, or value owner.

After the diagnostic, compare your report with the sample to spot what is specific to your context. The goal is not to fit an average; it is to know which decision now becomes reasonable.

The useful reading is to circle the three areas that need more evidence and the two decisions that can be made without waiting. That turns the sample into a meeting tool instead of a simple marketing preview.