Who is accountable when an AI answer is wrong?

Diffuse accountability is the default in AI deployments: the vendor points at configuration, engineering points at the policy, the business points at the model. Nobody owns the answer. Establishing accountability requires that each governing rule has a person attached before anything goes live, so a wrong answer resolves to a specific rule and a specific owner rather than to a general sense that the system misbehaved.

Skill Owner is a field on the skill record in Centralpoint, paired with a review cadence, and the Interaction Log ties each execution to the skills that governed it. A disputed answer can therefore be traced to the rules in force, and each of those rules to the person accountable for it — which turns a post-incident discussion about the model into a specific conversation about a specific policy.