A model's usage price is easy to put into a spreadsheet. The cost of operating a useful AI-assisted workflow is harder to summarize.
Someone must prepare the source material, review the output, handle exceptions, and maintain the connection to the rest of the business. Leaving those activities out can make a weak proposal look inexpensive.
Count the work around the model
Consider a tool that produces draft reports. The relevant cost includes retrieving the data, checking the report, correcting errors, and answering questions from readers. Generation time is only one part of the process.
Some of that effort exists in the current workflow too. The comparison should not charge the new approach for every human activity while pretending the old approach is free. Measure the complete before-and-after process with comparable tasks.
Keep one-time setup separate from recurring operation. A pilot may need extra attention while the team learns, but it should still reveal which costs are likely to continue.
Look beyond the average case
The ordinary task may be inexpensive while the difficult exception consumes substantial staff time. Understand how often exceptions occur and what they require. A workflow that occasionally enters a long, unproductive sequence of attempts needs a clear stop condition.
Quality matters to the calculation. A cheap output that cannot be used is not a completed unit of work. Define the acceptable result before comparing cost per task.
Budget for maintenance
Source documents change. Integrations need updates. The business revises its rules. A workflow should have an owner who can test changes and recognize when a previously acceptable result is no longer good enough.
These considerations do not make AI uneconomic. They make the investment question more honest. A useful tool can still justify its cost through better preparation, improved service, or reduced repetitive effort. Those benefits need evidence rather than an assumption that lower generation cost equals lower operating cost.
The strongest business case is one the team can explain without hiding the people who keep the system useful.