Galactia · galactia.co/resources/ai-search-readiness-report
AI search readiness of Australian local business websites
October 2026 edition. We checked 1112 local business websites across 34 Australian locations for the things search engines and AI answer engines need: access, structured data and a clear summary of each page.
Key findings
- Only 29% of sites have LocalBusiness structured data, the markup that says what kind of business a site belongs to and where. 73% have structured data of some kind, usually added by a theme or plugin.
- 25% of home pages have no meta description, so Google writes the search result summary itself.
- Blocking AI search crawlers is rare: 2% of sites block OAI-SearchBot, PerplexityBot or Claude-SearchBot. Access is not the main problem; being understood is.
- 23% of sites have an llms.txt file, and 53% of those were generated automatically by a site builder or SEO plugin.
- Real estate has the widest structured data gap: 20% of the 74 real estate sites we checked have LocalBusiness markup.
- 29%
have LocalBusiness structured data
- 25%
have no meta description on the home page
- 2%
block an AI search crawler in robots.txt
- 23%
have an llms.txt file, mostly auto-generated
Sample: 1112 business websites in 34 Australian locations, checked 20 October 2026.
Why these checks matter
AI answers from ChatGPT, Perplexity, Gemini and Google's AI Overviews are built from web pages that crawlers can reach and search indexes can understand. Google says a page must be indexed and eligible to show with a snippet to appear in its AI features (Google Search Central), and OpenAI says sites that block OAI-SearchBot will not be shown in ChatGPT search answers (OpenAI). Our checks measure the basics that decide whether a local business can be found, understood and quoted.
1. Structured data: the widest gap
Structured data is code on a page that states facts in a fixed format: this is a dentist, here is the address, these are the opening hours. Most sites have some, because themes and plugins add general types such as WebSite and Organization. Far fewer say what the business actually is. Across our sample, 73% of sites carried structured data, but only 29% used LocalBusiness or one of its subtypes. Our LocalBusiness guide explains how to add it.
By industry
| Industry | Sites | LocalBusiness | Any structured data | No meta description |
|---|---|---|---|---|
| Real estate | 74 | 20% | 62% | 30% |
| Accommodation and food | 330 | 24% | 64% | 31% |
| Personal and other services | 191 | 27% | 75% | 25% |
| Health care | 219 | 30% | 81% | 20% |
| Professional services | 125 | 36% | 80% | 19% |
| Construction and trades | 35 | 37% | 83% | 17% |
Industries with at least five sites checked in a location, combined across locations.
2. Meta descriptions: often left to Google
A meta description is the one-sentence summary a site gives for a page. When it is missing, Google picks text from the page, often a menu item or a cookie notice. 25% of the home pages we checked had none. It is the quickest fix in this report: one sentence per page, naming the service and the area.
3. AI crawler access: rarely blocked
AI companies run separate crawlers for search and for training. Blocking a search crawler (OAI-SearchBot, PerplexityBot, Claude-SearchBot) removes a site from that engine's answers. Blocking a training crawler (GPTBot, ClaudeBot, Google-Extended and others) does not. Only 2% of sites blocked an AI search crawler, and a further 2% blocked training crawlers only. For almost every local business, access is not what keeps it out of AI answers.
4. llms.txt: present, but mostly by default
llms.txt is a proposed file that summarises a website for AI tools. 23% of sites had one, but 53% of those files were written automatically by Wix, Shopify or an SEO plugin. Google says sites do not need AI text files to appear in its AI features. Our llms.txt guide covers when one is worth adding.
5. Site builders
WordPress 47%, Other or custom 29%, Squarespace 8%, Wix 6%. The platform matters because it decides how easy the fixes are: structured data, titles and descriptions are simple settings on some builders and need custom code on others.
Results by location
| Location | Sites | LocalBusiness | No meta description | Block AI search | llms.txt |
|---|---|---|---|---|---|
| Sydney | 62 | 31% | 27% | 2% | 34% |
| Western Sydney | 39 | 26% | 23% | 2% | 13% |
| Parramatta | 30 | 43% | 20% | 0% | 30% |
| Melbourne | 54 | 33% | 19% | 2% | 30% |
| Frankston | 22 | 18% | 18% | 4% | 32% |
| Brisbane | 63 | 27% | 29% | 2% | 21% |
| Gold Coast | 56 | 29% | 30% | 2% | 14% |
| Broadbeach | 49 | 24% | 18% | 2% | 20% |
| Southport | 27 | 19% | 33% | 0% | 19% |
| Perth | 46 | 39% | 20% | 2% | 28% |
| Adelaide | 51 | 27% | 20% | 2% | 20% |
| Newcastle | 39 | 36% | 23% | 5% | 26% |
| Darwin | 26 | 23% | 27% | 7% | 8% |
| Canberra | 50 | 34% | 38% | 0% | 14% |
| Hobart | 30 | 27% | 40% | 8% | 23% |
| Central Coast | 31 | 26% | 10% | 0% | 26% |
| Wollongong | 17 | 47% | 18% | 5% | 18% |
| Coffs Harbour | 18 | 11% | 28% | 0% | 22% |
| Port Macquarie | 19 | 47% | 21% | 0% | 32% |
| Wagga Wagga | 18 | 22% | 22% | 5% | 22% |
| Albury | 20 | 30% | 20% | 5% | 25% |
| Tamworth | 17 | 18% | 18% | 0% | 12% |
| Orange | 19 | 26% | 32% | 0% | 37% |
| Bathurst | 19 | 16% | 26% | 0% | 32% |
| Geelong | 61 | 30% | 21% | 2% | 18% |
| Ballarat | 40 | 22% | 20% | 2% | 18% |
| Bendigo | 34 | 24% | 32% | 8% | 12% |
| Sunshine Coast | 23 | 35% | 39% | 4% | 22% |
| Toowoomba | 24 | 12% | 21% | 0% | 29% |
| Townsville | 28 | 18% | 18% | 0% | 32% |
| Cairns | 23 | 22% | 35% | 8% | 13% |
| Rockhampton | 21 | 48% | 33% | 4% | 33% |
| Launceston | 21 | 33% | 24% | 0% | 38% |
| Bunbury | 15 | 47% | 7% | 0% | 13% |
Each location page has the full breakdown, with the ABS business mix for the area.
Method
We took businesses listed in OpenStreetMap in six industries, picked up to 12 per industry per location that list a website, and fetched each site's home page, robots.txt and llms.txt. Our crawler identifies itself and obeys robots.txt. Samples are small, tens of sites per location, so read the figures as a pointer to common gaps, not a census. The full method, sample sizes and limits are on our local data page.
How to cite this report
Galactia, AI search readiness of Australian local business websites, October 2026 edition, https://galactia.co/resources/ai-search-readiness-report
Frequently asked questions
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Can we quote figures from this report?
Yes. Quote any figure with a link to this page and the edition date (October 2026). The CSV has the figures for each location if you need more detail than the summary.
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How often is the report updated?
Each edition is a snapshot from one round of website checks. We publish a new edition when we rerun the checks, and the edition date is on every page of the PDF.
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Can you check my own website the same way?
Yes. Our first check of a client's site covers the same points across the whole site, not just the home page, plus Search Console and what AI engines say about your business. Talk to us.
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