Automation is excellent at volume and blind to context. The errors that cost the most are the ones a rules engine is built not to see.
Automation has a real place in revenue cycle work. It is fast, tireless, and good at high-volume, low-judgment tasks like eligibility checks and clean-claim submission. The problem is that the billing industry has started selling automation as if it replaces judgment, and the most damaging errors are precisely the ones a rules engine is designed not to notice.
It will happily submit two services on the same day that are individually valid and collectively a compliance problem, because nothing in its logic tells it those two codes should not coexist on the same date for the same patient. It will not pause on a pattern that looks fine line by line but wrong in aggregate. It does not ask why. Asking why is the entire job.
On one client, our team caught a same-day coding conflict before the claims went out, a combination that would have passed any automated submission check and then triggered recoupments down the line. No rules engine flagged it, because each code was legitimate on its own. A person who understood the payer's edits and the clinical context saw the conflict and stopped it. That is not a task you automate. It is a task you staff with people who know what they are looking at.
This is what we mean by forensic billing. It is the difference between processing claims and interrogating them. It is reading the data for what it implies, not just what it states. And it is why our work is done by an experienced, stateside team rather than handed to a black-box platform that returns a number with no one accountable for how it got there.