What is Credential graph?

A credential graph is the machine-readable web of links from an author entity to the external profiles and records that corroborate the author’s claimed expertise — sameAs links to LinkedIn, a personal site, X, ORCID or a professional registry, published work, and speaking or media appearances — that lets an AI engine confirm the person is real and the credentials are genuine.

It is what turns a byline from a name string and a self-described bio into a verifiable identity: an engine weighting authorship needs to corroborate the expertise somewhere less motivated than the author’s own bio, and the credential graph is the set of external anchors it checks. The graph must actually resolve and cohere — a sameAs link to an empty, inconsistent, or contradictory profile is worse than none, because it signals a weak or fabricated identity. The credential graph is the author-scoped analog of the brand’s sameAs entity graph, and it is one of the most under-built signals in AI-search entity work: most brands ship author bios with zero external corroboration, so wiring a real credential graph is a fast, differentiated way to raise the accountability an engine reads behind citable content.