Answer: Compare measurable baseline cost or lost value against the full operating cost of the AI workflow, then validate with real production data rather than projected time savings alone.

What this means in practice

Labor Time Reduced

Measure the hours a task takes today and after the pilot. Count savings only where that time is actually eliminated or redeployed.

Rework Avoided

Multiply the errors avoided by the average cost of fixing them, using your own job data.

Missed Follow-Up Reduced

Count the follow-ups, bids or customer responses that used to slip and value them conservatively as qualified opportunities missed times expected contribution.

Throughput Increased

If the same team handles more bids, documents or cases, record the added volume, and keep capacity gains separate from hard savings.

Cycle Time Reduced

Track how long the workflow takes from start to finish before and after. Faster cycle time matters most where delay has a real economic cost.

Revenue Or Margin Influenced

Keep expected revenue benefits conservative and tie them to a named owner. If you cannot estimate the current cost of the problem, do not claim a future ROI yet.

A practical construction test

  1. Define the business outcome.
  2. Measure how the workflow performs today.
  3. Identify what AI is being asked to interpret or decide.
  4. Define what remains under human authority.
  5. Test with real examples and acceptance criteria.
  6. Measure results before expanding scale or autonomy.

Where governance fits

The AI model can change. The company’s operating rules should not change silently with it. Catha’s Governance Cage is designed to preserve the business authority layer above the model and workflow.