AI search

Generative Engine Optimization: getting cited by AI search

AI Overviews and assistants answer first and link second. Here's what actually earns a citation — and what Google says is a waste of time.

SeoraUpdated June 22, 20262 min read

Generative Engine Optimization (GEO) is the practice of structuring content so AI systems — Google's AI Overviews, ChatGPT, Perplexity, Gemini — select and cite it when they answer a question. The good news from Google is blunt: there is no separate playbook. Its AI features are "rooted in our core Search ranking and quality systems," so the helpful, well-structured content that already ranks is the content AI quotes. The work is making your best answers easy for a machine to lift.

What actually earns a citation

Independent research on generative engines (Aggarwal et al.) found that the biggest gains came not from keyword tricks but from credibility signals: adding citations to sources, including relevant statistics, and quoting authoritative voices raised a page's visibility in AI answers by roughly 30–40%. AI retrieval also weighs the opening of a page heavily, so your first 150–200 words should answer the primary question outright — not build up to it.

Lead with the answer. State the conclusion plainly, then support it; assistants often lift the first self-contained paragraph that resolves the query.

Back claims with sources and numbers. Cited statistics and named references are quotable and verifiable — exactly what a model prefers to attribute.

Offer something only you have. Original data, a benchmark, a framework from real experience — Google calls this a "unique point of view," and it's the surest reason to be cited over a dozen lookalikes.

Structure for skimming. Clear headings, short sections and lists let a model find the relevant chunk without guessing.

What Google says is a waste of time

Just as useful is what to skip. Google has explicitly debunked several emerging GEO myths, and chasing them costs effort for nothing:

Don't create an llms.txt file or special "AI markup" — Google Search doesn't use them.

Don't artificially chop content into tiny chunks for AI; there's no requirement to do so.

Don't rewrite pages keyword-by-keyword for machines — systems understand synonyms and meaning.

Don't mass-produce a page per query variation; that trips spam policies and fails long-term.

Structured data isn't required for AI features, but it still earns rich results and helps every system parse your page with less ambiguity.

The technical floor: be reachable

None of this matters if a model can't fetch your page. Make sure important content is server-side rendered rather than hidden behind client JavaScript, that it isn't locked behind a login or paywall, and that your robots rules and CDN don't block legitimate AI crawlers. Add clear schema.org markup (Article, FAQ, Product) where it fits — it's the difference between a model inferring your meaning and reading it.

Where Seora fits

Seora scores each page for AI-overview readiness — answer-first structure, citation density, schema coverage, crawlability — and tells you the specific edit that would make it quotable. Try it on your own pages with a free audit, or see how it works.

GEO isn't a new discipline bolted onto SEO; it's classic quality content made machine-liftable. Answer first, cite your sources, publish something only you could, and keep the page reachable. Pair that with fast, stable pages and you're optimised for the searcher and the model at once.