SEO for AI goes by three names: GEO (Generative Engine Optimization), AEO (Answer Engine Optimization), and LLMO (Large Language Model Optimization).Different labels, one discipline: making your site the source that AI systems — ChatGPT, Gemini, Perplexity, Google’s AI Overviews — retrieve, trust, and cite when they answer questions your customers used to type into a search box.
“what is seo for ai called” — 210 searches/mo (Google, US)Why a new name at all?
Because the surface changed. Classic SEO competes for a ranked list of links; the searcher clicks, you get the visit. Generative engines skip the list: they synthesise an answer from a handful of sources and show it directly, with citations if you are lucky. The competition moved from “rank #1” to “be one of the three sources the answer is built from”— and the levers that win that competition are related to classic SEO but not identical.
Average monthly US search volume. Source: Google autocomplete demand via AnswerThePublic, 2026.
How AI assistants choose their sources
Under every generative answer is a retrieval pipeline, and each stage is a place you either survive or vanish:
- Crawl— AI crawlers (GPTBot, Google-Extended, PerplexityBot, and friends) fetch your pages. If your robots rules, CDN, or firewall block them, nothing downstream can happen. This is also where you exercise choice: allow retrieval bots that put you in answers, and decide separately about training-only bots.
- Index or train— your content enters a retrieval index (fresh answers) or training data (background knowledge).
- Retrieve— for a live question, the engine pulls candidate passages. Pages that state answers plainly, close to the top, in extractable form, win retrieval.
- Synthesise— the model composes the answer from those passages. Ambiguous, meandering pages get paraphrased out; precise ones get quoted.
- Cite— the visible payoff: your brand named, your link shown. Entity clarity (schema, consistent naming, an authoritative About) makes attribution easy.
GEO vs classic SEO: what actually changes
Classic SEO
- Win a ranked position on a results page
- Optimise titles and snippets for the click
- Success metric: rankings, clicks, traffic
- Keywords and links carry most weight
GEO / AEO
- Be a cited source inside the answer itself
- Optimise passages a model can lift verbatim
- Success metric: citations, mentions, AI referrals
- Entity clarity and structure carry most weight
The overlap is the good news: everything that makes a site technically healthy for Googlebot — crawlability, speed, clean structure — also feeds the AI pipeline. GEO is not a second job; it is the same job with three additions: answer-shaped content, entity-level structured data, and deliberate crawler policy.
How to do AI SEO: six concrete moves
- Answer the question in the first two sentencesof any page targeting a question — then elaborate. Models retrieve passages, not pages.
- Use question-led headings that match how people actually ask (the H2s in this post are lifted verbatim from real query data).
- Ship structured data beyond the basics— Organization, Article, FAQ, Product — so machines get facts as data rather than prose to interpret.
- Set a deliberate per-bot crawler policy.Retrieval bots in, training bots your call — and never let a blanket firewall rule silently block them all.
- Publish an
llms.txt— an emerging convention that hands AI systems a curated map of your most citable content. - Measure AI-crawler traffic in your logs.It is the only direct signal of whether any of this is being read — no AI platform offers a search-console equivalent.
The honest caveats
- Nobody outside these companies knows the exact source-selection criteria. What is written above reflects observable behaviour and the published mechanics of retrieval systems — treat vendors claiming guaranteed AI placement the way you treat guaranteed rankings.
- Citation traffic is smaller than click traffic, for now. The reason to move early is positional: sources that assistants learn to trust compound, and the measurement habit takes months to build either way.
Start where every layer of that pipeline starts: a technically clean site. Run the free audit to confirm crawlers — human-era and AI alike — can actually read what you publish.
Frequently asked questions
- Will AI replace SEO?
- It is replacing a slice of it — the simple informational queries that an assistant can answer in a sentence. What it cannot replace is the supply side: AI answers are grounded in crawled web content, so someone still has to be the source. The work shifts from "rank a blue link" to "be the page the answer cites", which is why GEO is best understood as SEO’s next chapter rather than its replacement.
- Can AI do SEO for me?
- AI is genuinely good at parts of the job: drafting metadata, summarising content gaps, generating schema, triaging audit findings. It does not replace the strategic layer — knowing which pages matter to your business — or the technical layer of making a site fast, crawlable, and structured. The strongest results come from AI-assisted workflows sitting on healthy technical foundations.
- What is the difference between GEO and AEO?
- They overlap heavily. AEO (Answer Engine Optimization) predates the LLM era and focused on featured snippets and voice assistants — being the single extracted answer. GEO (Generative Engine Optimization) targets generative systems like ChatGPT, Gemini, and AI Overviews, where the answer is synthesised from several sources and the win is being cited among them. In practice the tactics converge: clear answers, strong structure, machine-readable pages.
- How do I appear in Google AI Overviews?
- There is no submission process — AI Overviews draw on Google’s regular index. The observable pattern favours pages that answer the question directly near the top, carry relevant structured data, come from sites with topical authority, and remain crawlable. In other words: the same fundamentals, executed cleanly, plus content written so a machine can lift the answer without guessing.
- Should I block AI crawlers from my site?
- It is a genuine trade-off, and it should be a per-bot decision, not a blanket one. Blocking training-only crawlers protects your content from model training; blocking retrieval crawlers can remove you from AI answers your buyers actually read. Decide per bot and measure — which is exactly why per-crawler controls and AI-crawler analytics matter.