AI has changed what is possible in technical documentation. Tasks that previously took hours now take minutes. First drafts from structured inputs. Consistency checks across large document sets. Release notes from ticket data. Style guide compliance at scale.
These are genuine improvements and teams that have not adopted them are working harder than they need to.
But AI does not solve the source fidelity problem. It makes it worse if you are not careful.
A model that generates content from incomplete or ambiguous inputs produces fluent, confident, incorrect documentation. It fills gaps. It infers. It produces text that sounds authoritative and reads smoothly and contains errors that a rushed reviewer will miss because the writing is good enough to trust.
The discipline that makes AI useful in documentation is the same discipline that made good documentation before AI existed: source fidelity. AI accelerates that process when the process is sound. It accelerates the problems when it is not.