The AIARF global AI visibility baseline.
A public, repeatable framework for observing whether a brand appears in AI-generated answers—and for tracing the sources and claims surrounding that appearance.
AIARF is a new independent practice. This protocol establishes an honest starting point: claims should be tied to observations, observations should be dated, and methods should be clear enough to repeat.
It does not claim to reverse-engineer proprietary models. It measures outputs visible to a researcher and uses those outputs to form testable hypotheses about entity clarity, content coverage and source authority.
Baseline protocol
01
Define
Create a fixed set of category, comparison, recommendation and entity prompts in English.
02
Capture
Record answers for each platform with date, mode, visible citations and relevant interface context.
03
Classify
Mark mentions, recommendation context, narrative accuracy, competitors and cited sources.
04
Repeat
Re-run the same prompt set at documented intervals and compare directional changes.
Publication rules
- Label samples and demonstrations as illustrative.
- Do not present model variability as a deterministic ranking.
- Separate observed citations from inferred influence.
- Record corrections and material method changes.
Apply the protocol