How to Measure ROI on AI Automation
A practical framework for proving the value of AI automation — from baselining manual work to tracking the metrics that convince your CFO.
Start with a baseline
You cannot prove ROI on AI automation without knowing where you started. Before you automate anything, measure the current cost of the workflow: hours spent, error rates, cycle time, and the fully loaded cost of the people involved.
The three value levers
Almost every successful AI automation project moves at least one of these:
- Cost saved — fewer manual hours on repetitive work
- Time recovered — faster turnaround on the tasks you repeat daily
- Revenue created — more pipeline, higher conversion, faster response
A simple ROI formula
ROI = (annual value created − annual solution cost) ÷ annual solution cost
Keep the inputs honest. Count implementation, licensing, and maintenance on the cost side, and only count value you can defend with data.
Ship a pilot first
The fastest way to build a credible business case is to ship a focused pilot on a single high-value workflow, measure the result against your baseline, and then scale what works.
Ready to build your business case? Talk to the Clovai team.
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