Generative Engine Optimisation (GEO) for Australian Businesses: A 2026 Playbook

Generative Engine Optimisation (GEO) is the practice of making a website legible, quotable, and trustworthy to the AI systems that now sit in front of Google Search, Bing, and millions of daily enterprise queries — ChatGPT, Perplexity, Google AI Overviews, Google Gemini, Microsoft Copilot, and Anthropic Claude.

For Australian businesses competing locally or nationally, GEO is no longer optional. According to Google’s own May 2024 announcement, AI Overviews are rolled out to more than a billion users, and Similarweb’s 2025 analysis shows ChatGPT referral traffic to publisher sites grew more than 300% year on year. The rules of being found online have shifted from “rank in the blue links” to “be quoted in the AI answer.”

Why GEO is different from SEO

SEO optimises for a ranked list of ten page results. GEO optimises for being cited inside the answer itself. The underlying mechanics overlap (both require crawlable pages, clean markup, and authoritative backlinks) but the ranking signals diverge in three important ways.

First, AI engines resolve entities. They need to know what your business is, where it operates, and who runs it. This means structured data — specifically schema.org — is no longer a nice-to-have. It is the primary currency.

Second, AI engines reward concise, factual, question-shaped passages. A 40 to 60 word answer under a clear H2 question will outperform a 400-word marketing monologue every time.

Third, AI engines prefer sources they can verify. Citations with dates, author bylines, and linked references are picked up at a higher rate than anonymous editorial content. Google’s own Helpful Content guidance effectively codifies this preference for human expertise over templated AI output.

The seven fixes we apply to every website we optimise for GEO

1. Serve a real /llms.txt file. The llms.txt specification published by Answer.AI gives AI systems a single markdown file listing the most important pages and content policies for a site. Without it, AI crawlers must guess at what to cite.
2. Wire up IndexNow. IndexNow is the Microsoft-backed protocol that pushes new content directly to Bing, Copilot, Yandex, and Naver within seconds of publish. It is free and takes under 10 minutes to set up on WordPress via RankMath or Yoast.
3. Consolidate Organization and LocalBusiness JSON-LD to a single canonical block with a stable @id. We frequently find three or four Organization schema blocks on a single page — one from the SEO plugin, one from the page builder, and one hand-rolled. Conflicting sameAs lists confuse AI entity resolvers.
4. Publish FAQPage schema with genuinely useful Q&A. AI Overviews and ChatGPT web search disproportionately cite FAQPage content because it is pre-formatted for answer retrieval. Six to ten questions per service page is the sweet spot.
5. Attribute every blog post to a named author with Person schema. A post bylined “by Admin” or “by Company Name” produces zero Experience, Expertise, Authoritativeness, and Trust (E-E-A-T) signal. A post bylined by a real person with a LinkedIn sameAs link, a job title, and a knowsAbout field lifts the entire page’s citation odds.
6. Render visible “Last updated” dates. Perplexity, ChatGPT web search, and Google AI Overviews strongly favour content with verifiable freshness. The dateModified in schema is important, but a visible on-page date is what AI crawlers train against.
7. Submit a Wikidata item. A Wikidata Q-ID is the single most powerful entity anchor a business can claim. AI systems use Wikidata as a ground-truth reference for the relationships between entities — owner, founder, headquarters, industry. Even a minimal Wikidata item lifts brand-recognition accuracy in AI answers.

What this looks like in practice

When we audit a new prospect site, we score it on two frameworks: CORE-EEAT (80 items) and CITE (39 items, our AI-citation readiness scorecard). A typical Australian SME site scores around 40 to 50 on CORE-EEAT and 15 to 20 on CITE. The top 10% of sites we measure score above 68 and 30 respectively. The gap is almost always structural — missing schema, conflicting entity nodes, ghost-author blog posts, and no llms.txt — not content quality.

Closing that gap is a six to eight week project for a mid-market WordPress site, and it typically precedes (rather than replaces) a traditional SEO campaign. Getting found in AI search is a foundation move; getting found in Google search is a layer on top.

Further reading

• Answer.AI — Proposal for an llms.txt standard
• Google Search Central — Structured data general guidelines
• Microsoft IndexNow — IndexNow protocol overview
• OpenAI — GPTBot and OAI-SearchBot documentation
• Wikidata — Introduction to Wikidata

This post is part of Dezign Digital’s ongoing research into how AI search surfaces cite Australian businesses. If you would like a free CITE-score audit of your own site, get in touch.

Want your business named in ChatGPT, Gemini and Google AI Overviews? See our AEO and GEO service, or read about GEO in Perth.