If you have typed "what's the AI version of SEO" into a search box, you have asked the right question in a shape that does not quite have an answer. There is no single "AI SEO" that quietly replaced the old one while you were not looking.
What actually happened is narrower and more manageable. Search split into more than one surface, and two of those surfaces are new enough to have earned their own names: answer-engine optimisation (AEO) and generative-engine optimisation (GEO). Both sit on exactly the same foundation as traditional SEO — structured content, entity authority, and technical health — and both are simply measured differently.
So the accurate reframing is this: the AI version of SEO is not a replacement discipline you have to learn from scratch. It is two additional measurement surfaces on the discipline you already run. This is a category point of view, not a pitch. NETEVO's principal is a registered Trans-Tasman patent attorney and systems architect, and the Law-to-Code Methodology treats visibility as an engineering problem rather than a marketing trick.
The short answer: not one AI version, but two — on one foundation #
Traditional SEO measures whether you rank in Google's classic results. The two newer surfaces measure something adjacent. AEO measures whether you own the answer block above those results — the featured snippet, the People Also Ask expansion, and since 2024 the Google AI Overview. GEO measures whether you are cited inside a conversational assistant — what ChatGPT, Claude, Perplexity, or Gemini says when a buyer asks it a question directly.
Three surfaces, one substrate. None of them replaces Google search, which in Australia still handles roughly 94% of all queries according to StatCounter. The AI surfaces sit on top of that demand, not in place of it.
Why the question keeps changing shape #
The reason the plain-English question feels slippery is that the vocabulary is still multiplying. SEO is decades old. AEO named the shift to snippets and AI Overviews. GEO named the shift to being quoted inside an assistant, a category formally described in the Aggarwal et al. KDD 2024 paper. And a fourth label — AIO, for AI optimisation or AI-Overview optimisation — began appearing in live Australian search queries through 2026, before the field has even settled what it means.
This is what a category looks like while it is forming. People do not reach for an acronym they are unsure of; they type the plain-English question precisely because four competing initialisms is three too many. If that is you, you are not behind. You are watching a naming contest, not a technology you have missed.
What actually changes when search becomes AI-mediated #
Underneath the vocabulary, one concrete thing changes. Classic search returns a list of links and asks the person to choose. An answer engine or a generative engine returns an answer and cites a handful of sources. The unit of visibility moves from a ranking position to a citation. You are no longer only trying to rank in a list; you are trying to be the source the model quotes.
The levers that decide whether you are quoted are not new or exotic. They are the same three foundations that have always decided SEO, now read more strictly by a machine that is synthesising rather than listing:
- Structured content — schema markup that states, in machine-readable form, what each page is about, so a model can extract and attribute it confidently.
- Entity authority — a clean, connected identity (a dense
sameAsgraph, named-author bylines, a pattern of being referenced by sources the model already trusts), so the model treats you as credible. Google's E-E-A-T signals and the signals an LLM weighs turn out to be nearly the same judgement. - Technical health — pages that AI crawlers can actually reach and render, because a crawler that cannot see your content cannot cite it.
Get those right and you become quotable across all three surfaces at once. NETEVO measures the result as Share of Model — the rate at which the AI answers to your buyers' questions cite you rather than a competitor — the same way traditional SEO measures rank.
The Australian-market version of the question #
Most of what ranks for "the AI version of SEO" was written for United States B2C marketers and is silent on what a listed or pre-IPO Australian company actually needs. For an ASX-listed entity, the surface that matters is not a product-review query — it is what an analyst, journalist, or retail investor sees when they ask an AI assistant to describe your company. That first-pass description is now assembled by a model from your investor-relations pages, your annual report, and whatever else is publicly legible about you. If that substrate is unstructured, the gap is filled with competitor framing or stale coverage. The engineering that fixes it is the same substrate work above, applied to the pages that carry your reputation rather than only the pages that carry your marketing.
What to do about it — and what not to #
The trap in a forming category is to buy one of everything: an "AEO tool", a "GEO agency", and an "AI SEO" retainer, each selling a measurement surface as if it were a separate discipline. That is three procurement decisions to fix one underlying problem. Build the substrate once — structured content, entity authority, technical health — then instrument the three surfaces against it.
If you want the acronym-by-acronym comparison — what each one optimises for, where it measures success, and what shifts it first — that is set out in full in the AEO vs GEO vs SEO pillar. If the question you actually need answered is "how would this be delivered for us", that is the remit of AI Search Visibility. Either way, the answer to "what is the AI version of SEO" is the reassuring one: it is not a new thing to start from scratch. It is the thing you already have, observed through two new lenses, with one discipline underneath all of them.
Where to read next
The path runs from this plain-English overview into the full comparison and then into delivery. If the category is new to your team, start with the pillar.
AEO vs GEO vs SEO: Three Acronyms, One Strategy
The full comparison this overview points to — what each surface optimises for, where it measures success, and the single substrate that wins all three.
Read the pillarAI Search Visibility
The delivery side — Schema Engineering for AI, Entity Optimisation, Content Architecture for RAG, and Share of Model tracking.
View solutionSEO Visibility
The traditional-search measurement and revenue-attribution practice the AI surfaces build on top of.
View solutionGenerative Engine Optimisation: The Evidence Base
The deeper research paper, including the Aggarwal et al. methodology and the AU market context.
Read the evidence baseQuestions
Frequently asked questions
Plain-English framing questions. The acronym-by-acronym comparison (AEO vs GEO vs SEO, what each measures) is answered on the AEO vs GEO vs SEO pillar; how the work is delivered is answered on AI Search Visibility.
What is the AI version of SEO?
There is no single AI version. AI search adds two measurement surfaces on top of SEO: answer-engine optimisation (owning snippets and AI Overviews) and generative-engine optimisation (being cited inside ChatGPT, Claude, Perplexity, and Gemini). All three run on the same substrate — structured content, entity authority, and technical health.
Is SEO dead, or has AI replaced it?
Neither. Google still handles roughly 94% of Australian search, and the same foundations that win SEO also win the AI surfaces. The discipline is consolidating into one visibility practice with three measurement lenses, not being replaced. The vocabulary changed faster than the underlying work did.
What does AIO mean?
AIO is an emerging label for AI optimisation or AI-Overview optimisation. It began appearing in live search queries in 2026 and does not yet have a settled definition. Treat it as the newest name in a still-forming category rather than a distinct discipline you need a separate budget for.
Do I need a different tool or agency for AI search?
Usually not. A vendor pitching AEO, GEO, or 'AI SEO' as a separate retainer is selling a measurement surface as if it were a discipline. The team that builds your schema, entity graph, and technical foundation is the team that wins all three surfaces. How that is scoped and delivered is covered on the AI Search Visibility solution page.