Ungrounded internal consistency can produce fluent but factually unsupported AI outputs.

A review of academic literature and empirical studies identifies ungrounded internal consistency as a recognized pathway to AI hallucinations, where fluent, internally consistent generation overrides external evidence such as retrieved facts or perceptual data. This failure mode is one of several causes, not the sole explanation, for factually unsupported outputs in large language models.