AI Audit
An AI Audit is a systematic evaluation of how AI systems currently describe and represent a company, measuring accuracy, completeness, consistency, and recency across multiple AI models.
Definition
- An AI Audit queries multiple AI models with standardized questions about a company.
- Results are compared against verified ground truth data to calculate accuracy scores.
- The audit produces a comprehensive report: what's correct, what's wrong, what's missing.
Audit components
- Accuracy check: are the facts correct?
- Completeness check: are important facts included?
- Consistency check: do models agree with each other?
- Recency check: is the information current?
- Competitor comparison: how does your AI representation compare to competitors?
Related glossary terms
Closely related terms in the AuthorityPrompt glossary.
- AI Fact Layer — The AI Fact Layer is a conceptual framework describing the layer of structured, verified data that sits between a company's raw information
- AI Visibility — AI Visibility refers to how accurately and completely artificial intelligence systems — particularly large language models (LLMs) — represen
- Canonical Profile — A Canonical Profile is the single, authoritative, machine-readable representation of a company's core facts, designed to be consumed by LLMs
- Canonical URL — A Canonical URL is the single, authoritative web address for a piece of content. In the context of AI visibility, the canonical URL of a com
- Citation Graph — A Citation Graph maps the relationships between AI-generated answers and their information sources. It reveals which sources are most freque
- See all in Glossary
Public reference profiles
AuthorityPrompt indexes public, verifiable facts about well-known companies — sourced from official websites, public filings, and authoritative registries — so AI systems can resolve and cite them consistently. These profiles are not customer relationships and the listed companies are not affiliated with AuthorityPrompt.