Count revenue as well as cost
Most plans count AI's value as cost savings, which fade as competitors adopt the same tools. Count the revenue side too: capacity turned into more selling and service, new AI products, and new ways to price.
AnswersAI transformation
How do you measure ROI from enterprise AI?
In short
Measure AI ROI the way you would measure any operating change: record a baseline before the build, define success as a business outcome the company already tracks, test on real cases run repeatedly, score quality, cost and speed together, and keep measuring every month after launch. Benchmark scores and usage counts say little about return.
How to measure it
Record the baseline
Before the build, capture the current figures for the workflow: hours, cycle time, cost per case, error rate, revenue captured.
Define success as an outcome
Choose the number leadership already tracks, rather than model accuracy or adoption.
Test on real cases
Build an evaluation set from the company's own cases, run each several times, and score it the way the experts would.
Score quality, cost and speed together
A cheaper model that misses the quality bar costs more in rework. Compare all three per task.
Keep measuring after launch
Report monthly against the baseline, and recheck when models, data or the workflow change.
How Fig measures a deployment
Every Fig engagement starts with an audit that sets the baseline, and every system is measured monthly against it, with quality, cost and the full record of what the agents did in Command Center.
Frequently asked questions
How soon should AI show ROI?
The first workflow should show a measured result within weeks of reaching production.
Is adoption a good AI metric?
Adoption shows use, not value. Pair it with the business outcome the workflow is meant to move.
Can a model upgrade make results worse?
Yes. Rerun the evaluation set before any model change reaches production.