
Your AI Business Cases Are Counting the Same Savings Twice
Nearly every AI use case promises time savings. When several target the same work, the totals stop adding up. Here is how to spot double counting and fix it.
Pick a use case, enter your own volumes and costs, and see a low, mid and high estimate. The ranges come from the MetroMinds Library and are based on real-world implementations.
We use the same structure as the business cases in the MetroMinds platform:
We calculate it three times, with the low, mid and high value of the benchmark range. The three factors at the end keep the estimate honest:
The share of the work the use case actually touches.
How much of that work people will really do with the new tool.
How sure you are about your own inputs.
The result is a range for one use case. When several use cases touch the same work, their savings overlap and cannot simply be added up. The MetroMinds platform corrects for that per business capability.

Nearly every AI use case promises time savings. When several target the same work, the totals stop adding up. Here is how to spot double counting and fix it.

The use cases with the highest value are often the hardest to deliver. Library data shows why the largest AI business case deserves the most scrutiny.

Half of all AI benefits are priced as saved time. Library data shows why that time rarely reaches the cost line, and how CFOs can make sure it does.
See how MetroMinds compares business cases across your whole portfolio, and corrects for savings that are counted twice.