"Ranking" in AI search is a slightly misleading phrase: there are no positions one to ten in a ChatGPT answer. There's an answer, a few businesses named in it, and everyone else.
But the work of becoming one of those names is concrete, repeatable and mostly unglamorous, and in 2026 it rewards businesses willing to do it properly.
This is the playbook we run for Australian businesses, in the order we run it.
None of it requires tricks. All of it requires actually doing the work.
Start from conversational, long-tail questions
People don't talk to AI the way they type into Google. Nobody asks a chatbot "plumber Brisbane"; they ask "who's a reliable plumber in Brisbane's inner north who does emergency call-outs and won't charge a fortune?"
Those long, specific, conversational questions are your new keyword research. List the questions your customers actually ask (by suburb, budget, situation and objection) and make sure your site contains a genuine, direct answer to each one.
Specificity is the advantage here: an engine answering a specific question strongly prefers a source that addresses it specifically.
State the facts buyers decide on, explicitly
Language models can only quote what's written down. If your pricing is "contact us", your service area is implied, and your point of difference lives in a founder's head, the engine has nothing to work with and will name a competitor who spelt it out.
Put decision-relevant facts in plain text on the page: prices or honest price ranges, specifications, service areas, turnaround times, guarantees, and when the information was last updated. Freshness matters: engines discount pages that look abandoned, and a visible "last reviewed" date is a cheap credibility signal.
Structure pages so machines can lift the answer
Structure is how you make your content easy to extract. Use question-shaped headings with direct answers in the first sentence beneath them.
Add FAQ blocks to core pages; they map one-to-one onto how AI questions arrive. Implement schema markup (Organization, LocalBusiness, Product, FAQPage as relevant) so the facts on the page are also machine-readable.
And keep the answer near the top: an engine skimming your page should hit the substance in seconds, not after four paragraphs of throat-clearing.
Win the Australian surfaces engines actually read
AI engines cross-check businesses against third-party surfaces, and in Australia that means a specific set. Your Google Business Profile should be complete, category-accurate and actively collecting reviews: it's frequently the single most-consulted record about a local business.
Product and service businesses should take ProductReview.com.au seriously; it's a distinctly Australian trust signal engines can retrieve. Then come the industry directories and professional bodies relevant to your field: the boring listings you set up once and forget are exactly the corroboration an engine looks for before naming you.
Consistency across all of them, down to the exact business name and phone number, is the multiplier.
Publish original data: become the citation
The strongest position in AI search is being the source, not just being mentioned. Engines need numbers, and most industries produce very few original ones.
A modest dataset you actually own (median days-on-market across the suburbs you service, a survey of 200 customers, benchmark pricing you've collected) gives engines something they can only get from you, and citations compound. One genuinely original number outworks ten generic blog posts.
Measure with holdouts, not vibes
Finally, the step most programmes skip: proof. Track a fixed set of target questions across engines over time so you can see share-of-answer moving.
Then go further and hold something out (a region, a product line, a set of pages left untouched) so you can compare treated against untreated and see incremental effect rather than market tide. The best available research is candid about why this matters: outcomes vary widely by category.
0–16.3%
sales lift measured in randomised GenAI retail experiments: a range, not a promise
That spread, from nothing to a substantial lift in randomised retail experiments, is exactly why holdouts belong in the playbook. Some categories move a lot, some barely move, and only measurement tells you which one you're in.
This full sequence is what our 90-day pilot runs from start to finish, and if you want a snapshot of where you'd be starting from, check your AI visibility.
The foundations overlap, deliberately, since retrieval still runs on technical SEO. The additions are answer-ready structure, entity consistency, third-party authority surfaces, original data, and AI-answer tracking with holdouts. If your agency covers all that, you're in good hands.
Both, in sequence. Your site supplies the facts an engine can quote; third-party surfaces supply the corroboration that makes it comfortable naming you. A strong site with no independent proof, or glowing reviews around a thin site, both underperform the combination.
It helps and it's cheap, so yes, but it's a supporting actor. Schema makes facts machine-readable; it can't compensate for pages that don't state the facts in the first place. Content first, markup second.
Structural fixes and profile clean-ups can shift answers within weeks; authority and original data compound over months. Insist on tracked target questions from day one so you're watching real movement, not waiting on faith.