The default is nobody
AI employees are usually deployed by a technical team and then used by an operational one, which leaves the question of who is responsible for its quality unanswered. Systems with no owner do not stay still — they decay, because the business around them keeps changing.
Ownership is three separate jobs
Someone owns the knowledge it works from, someone owns the workflow it sits in, and someone owns the platform it runs on. Those are rarely the same person, and pretending they are is how the knowledge job — the one that determines quality — ends up unassigned.
The knowledge owner belongs in the business
Whoever owns the knowledge must know what a good answer looks like, which means it belongs with the team doing the work, not with engineering. They decide what gets documented, what the decision rules nobody wrote down actually are, and what the system should refuse to handle.
An AI employee with no owner doesn’t stay the same. It gets worse, quietly, as the business moves on without it.
Give it a review, like anyone else
A monthly review — sampled conversations, escalation rate, corrections made, questions it couldn’t answer — takes an hour and is the mechanism by which it improves. Without it you are relying on complaints, which surface only the worst cases and only after damage.
Escalations need a destination that exists
A hand-off is only as good as the person waiting on the other end. If escalations land in a shared inbox nobody owns, the automation has moved the failure rather than removing it.
Name the owner before launch
The question “who is responsible for this being right?” should be answered with a person’s name before the system handles its first real request. Teams that can’t answer it usually can’t answer it six months later either, by which point it is no longer worth its seat.