Which brands do AI engines actually cite?
When Australians ask AI engines who to use, a handful of brands get named. The Australian AI Search Report will measure which ones — category by category, engine by engine.
Every buying decision now has an AI answer. Almost nobody measures who is in it.
When an Australian asks an AI engine who to use — which lender, which firm, which retailer, which trade — the engine replies with a short, synthesised answer naming a handful of brands. Those names are not ranked pages. They are the shortlist. And in most categories, no one can say with evidence which brands the engines are naming, how consistently, or drawn from what sources. Opinion fills the gap.
The Australian AI Search Report exists to replace that opinion with measurement. The first edition is in preparation: systematic testing of commercially meaningful Australian queries across Google AI Overviews, ChatGPT and Perplexity, recording which brands each engine cites for each category. The result will be a league table of AI citation share — measured, not guessed, and open to challenge because the method will be published with it.
The report comes out of an AI search practice that runs on measurement rather than commentary. The same discipline already operates at brand level as the AI search visibility audit — one organisation, its queries, its competitors, its gaps. The report applies that discipline at category level, across the market, as a public baseline.
It is written for marketing leaders who owe a board an answer on AI exposure. Directors have started asking whether the brand appears when customers ask AI engines who to use — and today most executive teams can only answer with anecdote. Once the report exists, the question has a reference point.
What the first edition will do.
Measure citation share
Commercially meaningful Australian queries — the questions buyers put to an engine before they spend — tested systematically across Google AI Overviews, ChatGPT and Perplexity, with every brand citation recorded and attributed to its engine.
Publish a league table
Findings presented as a league table of brand citation share, category by category. No sponsored placements and no pay-for-position — a brand appears in the table because an engine named it, and for no other reason.
Show the working
The methodology published alongside the findings: how queries were constructed, which engines were tested, how citations were collected and counted, and where the limits of the data sit. A baseline is only useful if it can be scrutinised and retested.
Be part of the baseline.
Category coverage for the first edition is being scoped now. Organisations that want their sector measured — and a clear read on where they stand when the results land — can enquire.
sam@sampark.com.au