Australia's biggest retailers are nearly invisible to AI search
A passive check of 8 well-known AU retail homepages on 23 July 2026: 0 of 8 served an llms.txt, 0 of 8 declared an AI-crawler policy, and most serve no structured data in the HTML an AI crawler reads.
Frequently asked questions
Which retailers did you check, and when?
Eight well-known Australian retail homepages on 23 July 2026: Bunnings, JB Hi-Fi, Chemist Warehouse, Myer, Kmart, THE ICONIC, Kogan and Harvey Norman. Every finding is a point-in-time check of the homepage on that date - a site could add an llms.txt or change its robots.txt tomorrow, which is why the date matters.
Does this mean these brands are invisible in ChatGPT right now?
Not necessarily. I measured the readiness signals AI engines use (llms.txt, AI-crawler policy, structured data), not live citations. A brand as large as these may still be named by an AI engine on the strength of sheer authority and third-party coverage. The point is narrower and fair: they have built no AI-search foundation of their own, so any visibility they have is on loan, not earned.
What is an llms.txt file and why does it matter?
llms.txt is an emerging plain-text file at the site root that tells AI models what a site is, which pages to read, and what they are permitted to use - the AI-era companion to robots.txt. Sites that serve one are easier for AI engines to understand and cite. None of the eight retailers served one.
How did you check this without a login or a crawl of the whole site?
Passive, public checks only: a request to each homepage, to /llms.txt, and to /robots.txt, plus a check of whether structured data appears in the page. These are the same publicly observable signals AuditHQ’s GEO and AI-readiness suites read - no authenticated access, no active probing.