AI ROI
5 Common Mistakes in AI ROI Models
Why AI business cases often overstate value, miss operating costs, or fail finance review, and how to make the model more credible.
Counting all time saved as cash savings
Time savings create capacity, but they do not automatically reduce payroll expense.
Ignoring adoption
Expected value depends on how many users adopt the solution, how often they use it, and whether the new workflow replaces the old one.
Leaving out production costs
Prototype cost is rarely the full investment. Include integration, governance, training, change management, monitoring, support and model usage.
Using one optimistic scenario
Finance teams need to understand downside as well as upside.
Starting with the technology instead of the business problem
The strongest AI business cases begin with a measurable operating constraint.