Somebody entering invoices by hand is doing two jobs at once, and only one of them is in the job description. They are typing, and they are noticing: an unfamiliar supplier, an implausible amount, a duplicate they half-remember. Automating the typing removes both, and the second loss has to be replaced deliberately or errors travel straight through.
What the noticing catches
An invoice from a supplier you do not use. An amount that makes no sense for that supplier. A date in the future or from years ago. A second copy of something processed last week. None of these are extraction problems, and all were being caught incidentally by somebody who had to read the document to type it.
The rules that replace it
Supplier exists in your records. Invoice number not seen before for that supplier. Lines sum to net, net plus tax equals total. Date within a plausible window. Bank details match what you hold. Five cheap checks that catch most of what the person was catching without meaning to, and that run in milliseconds rather than minutes.
And a queue for what remains
Fields extracted with low confidence should reach a person, on a screen showing the document beside the value. That queue is where the remaining human attention belongs, and it is much smaller than checking everything. Designing it well is what turns automated entry into a saving rather than a relocation of work.
Questions people ask about invoice data entry
Will automation eliminate the data entry role?
It changes it into reviewing exceptions and resolving queries, which is different work and usually more of what the person was good at anyway.
How accurate does extraction need to be?
Accurate enough that the review queue is smaller than the typing was. Measure that on your own documents rather than accepting a headline figure.
Should rules block or warn?
Duplicates and bank detail mismatches block. Arithmetic and plausibility warn, since they are usually extraction errors.