Understanding AI authority evidence
The reference library explains how to read AI authority evidence before deciding what it means for an organization. Start with identity, then distinguish presence, citation and recommendation, inspect the source and check the observation conditions. The references describe what research can reveal and what each evidence object cannot establish. They are reusable explanations, not findings about a particular company or guaranteed optimization tactics.
Read what the answer says about the organization
Start with entity identity if a name, group, domain or location may be confused. An attribution error can undermine every later count. Then use presence, citation and recommendation to identify the organization’s role rather than treating all appearances alike.
Authority and visibility explains why presence alone does not describe positioning. Narratives and positioning examines attributes, comparisons and recurring accounts. Together these references help turn a vague concern such as ‘AI misunderstands us’ into a specific question about identity, facts or buyer suitability.
Keep the original wording and question. An answer can be accurate but irrelevant to the intended buyer, or positive but based on the wrong company. The evidence determines which concern is supported.
Follow the source relationships
Source provenance explains how a reference connects a source object, publisher, host and claim. It helps assess whether a page supports the statement, whether several references repeat one origin and whether a platform is being mistaken for a provider.
Website evidence compares owned claims with external accounts and captured answers. Social and video evidence adds account attribution, available content and collection limits. These sources can reveal useful facts or contradictions without proving hidden influence on a model.
Choose the evidence object relevant to the question: a service page, cited passage, social post, video description or verified transcript. The existence of a URL is not a complete content inspection.
Compare with the right scope
Use models, interfaces and retrieval modes before comparing systems. Use comparability and change before interpreting a time series. Use measurement and uncertainty before relying on a score or percentage.
A short reading path for a non-specialist is: identify the entity, read its assigned role, follow the source, then examine the denominator and conditions. A specialist can begin with the uncertainty or change reference when evaluating a delivered study.
The decision guides apply these explanations to a practical choice. The governance pages describe claim, publication and correction standards. Public knowledge can help frame a private investigation without substituting for its specific evidence.
When using a dated Observatory reading as market context, inspect the publisher’s method and the reading’s actual capture scope. A publisher’s editorial explanation and a private AAI diagnosis have different purposes and permissions.
Common questions
- Which reference helps interpret a visibility score?
- Read the guide to AI visibility measurements, then check which organization was identified and what role it had in the answer.
- Where can I understand website versus external-source evidence?
- Read the website evidence and source interpretation guides. They distinguish your own claims, external accounts and the actual cited page.
05 Where this leads
Once identity, role, source and observation conditions are clear, the remaining question is whether they support the study’s conclusion. The study-evaluation guide follows that connection through a material finding. For a discrepancy about your own organization, the representation investigation example shows how to connect the retained wording to verified facts and a relevant business decision.