How should I measure the ROI of an AI feature?
Measure AI ROI by comparing the value of a completed workflow with its full incremental cost. Define a baseline, a measurement period, and the quality threshold before launch. Include review, corrections, integration, and ongoing operation rather than treating lower token cost as the business result.
What does the source say?
Google’s guidance on measuring ML success distinguishes business metrics from model metrics. The product implication is to connect a technical improvement to a result that matters to a user or the business.
How can you apply this?
Pick one workflow and write its current completion rate, time requirement, and acceptable quality level. Estimate the new process including human review and failed attempts. Run a bounded comparison and record assumptions beside each value. Keep a separate guardrail for outcomes you must not worsen, such as error severity or unauthorized access.
What should you watch out for?
Avoid claiming every minute saved becomes revenue. Small samples, changed demand, and selection effects can distort an apparent improvement; state what the comparison can actually support.