Find the AI use cases that deserve budget.

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.

The work is not another scorecard. It turns AI spend, usage, or risk into a decision leadership can act on: what should stop, what should be fixed, what deserves more budget, and what must stay controlled before it expands.

This page is for leaders, finance, operations, IT, and business teams that already have visible AI activity but not enough evidence to decide. The common symptom is not lack of AI; it is too much activity without ownership, full cost, or a shared quality threshold.

It is useful before renewals, when several teams buy similar tools, when pilots stay in permanent demo mode, or when nobody can say whether AI truly improves the workflow that matters.

We use the Four Leaks of AI ROI: spend, adoption, leaks, and role drift. Every signal is tied to cost, owner, risk, and decision. This structure avoids confusing enthusiasm, usage, and measurable return.

The framework also forces a simple discipline: an AI use case needs scope, a pre-AI baseline, a quality threshold, a value measure, and a review date. Without those five elements, the company funds a story instead of an operating asset.

Deliverables are designed to be used in decision meetings, not merely read. They separate available evidence, reasonable assumptions, risks to reduce, and measurements to install. Every item should support a concrete decision.

• 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

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.

The report avoids broad abstract recommendations. It shows the workflows involved, the evidence behind each conclusion, confidence limits, and the next expected decision. A good Harmondale report should make the next meeting shorter.

10-15 working days

The first phase gathers inventory, cost, past decisions, and field examples. The second qualifies priority workflows, checks assumptions with owners, and separates spend, quality, risk, and adoption issues. The end converts analysis into a decision backlog.

€6k-€18k depending on scope and data access

Budget depends mainly on the number of teams, quality of available traces, data sensitivity, and expected analysis depth. A short scope can be enough when the decision is urgent; a broader scope is justified when several budgets or departments are involved.

Objections are normal because the audit touches budgets, team habits, and sometimes tools people genuinely like. The role of the audit is to make decisions defensible, not to turn AI into a search for blame.

• 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.