Document AI is powerful, but not every document-heavy process deserves it. Sometimes the volume is too low, the business value is too weak, or the real problem is not extraction at all.
Bad reasons to use it
"We have documents" is not enough. If the process is low-volume, rarely repeated, or not tied to an important operational outcome, AI may create more complexity than value.
Good reasons to use it
Document AI becomes compelling when important information is trapped in documents at meaningful scale, when manual handling creates measurable delay or error, and when better structure would improve downstream reporting, workflow, or decisions.
The question is not "do we have documents?" It is "does extracting this information unlock a measurable business outcome?"