What is AEO and GEO, and how do they differ from SEO?

Last updated October 14, 2026. Written by the Third Coast AI team.

AEO (answer engine optimization) is the work of getting your company named, described accurately and cited when an AI engine such as ChatGPT, Google AI Overviews and AI Mode, Gemini, Perplexity or Copilot answers a buyer's question. GEO (generative engine optimization) is the same discipline described from the engine's side: making your pages the ones the model retrieves and quotes when it writes that answer. In practice the two terms are used interchangeably, and both differ from SEO in one way that matters: SEO earns a position on a list of links, while AEO and GEO earn a mention inside a written answer that most people never click past.

This page gives the definitions, a side-by-side table, a short account of how the engines choose sources based on the published research, and a candid list of what the field does and does not know yet. It is written for an owner or marketing director who needs to understand the thing before buying it, and it is the page we point clients to before an audit.

Is there a real difference between AEO and GEO?

We use both terms because clients and the engines do. If you want a rule of thumb, AEO describes the business goal (be the answer) and GEO describes the page-level craft (be the source). Neither replaces SEO, and the most useful way to see the three is side by side.

How do SEO, AEO and GEO compare?

Why can a page rank first in Google and still be ignored by the engines?

Because the engines are building a different list. Ahrefs tracked the overlap between Google's top ten and the pages cited in AI Overviews and watched it fall from 76% in July 2025 to 38% in March 2026. Tom Capper at Moz measured 88% of AI Mode citations as pages that did not appear in the organic results for the same query, and Kirsten and colleagues (Ruhr University and MPI-SWS, 2025) found 53% of the domains cited in AI Overviews were not in Google's organic top ten for the same query, and 40% were outside the top 100. Rank still helps, and Cyrus Shepard's May 2026 synthesis of 54 studies scores search rank at 9.4 out of 10, second only to URL accessibility at 9.5, but the correlation is weakening every quarter.

The mechanism behind this is the set of searches the engine runs behind one question. When you ask AI Mode or AI Overviews a question, the system issues many related searches on your behalf, retrieves candidates for each, and writes one answer from the set. Google has described this publicly, and our own captures show 10 to 20 sub-queries behind a typical buyer question. A page that ranks first for the exact phrase you typed may rank nowhere for the sub-queries, which is why a competitor on page three with a more thorough page can be the one quoted.

Which signals decide whether a page gets cited?

The cleanest model in the current research is the two-stage one proposed by Zhang and Yao in 2026 and consistent with Shepard's factor analysis. In the first stage, selection, the engine decides whether to retrieve and consider your page at all, and that is predicted by crawler access, index presence, brand priors (how often you are mentioned elsewhere and whether the model recognizes you as an entity) and how much of the topic cluster you cover. In the second stage, absorption, the engine decides how much of your page to use, and that is predicted by where the answer sits, how dense the statistics are, whether there are quotations and cited sources, and how the page is structured.

• Accessibility. GPTBot, OAI-SearchBot, ClaudeBot, PerplexityBot and Bingbot have to reach the raw HTML; ChatGPT's retrieval does not execute JavaScript. Shepard scores this 9.5 out of 10, the highest of 23 factors.
• Third-party mentions. Ahrefs' 75,000-brand study found unlinked web mentions correlated with AI citations three times as strongly as backlinks, and the 5W citation index attributed about 85% of 680 million AI citations to earned media.
• Answer near the top. 55% of AI Overview citations and 44% of ChatGPT citations come from the first 30% of a page.
• Statistics, quotations and sources. The Princeton paper's three strongest tactics, replicated on Perplexity at smaller but positive effects.
• Structure. Zhang and Yao: top-quartile heading count cited at 12.5 times the bottom quartile; list density 8.94 times.
• Topical coverage. BrightEdge measured pillar-and-cluster architectures lifting AI Overview citation on pillar queries from about 12% to 41% (Q1 2026).
• Freshness, when the query is time-sensitive. Half of Perplexity's citations are to content under 13 weeks old; 29% of ChatGPT's are from 2022 or earlier, so authority still outweighs recency for evergreen topics.

Does schema markup or an llms.txt file get you cited?

Not on the evidence, and we would rather say so than sell it. Ahrefs ran a difference-in-differences test on 1,885 pages and found FAQ and HowTo schema made no measurable difference on AI Mode or ChatGPT and a small negative difference on AI Overviews, while Microsoft has said Copilot does use structured data for grounding, so schema is hygiene everywhere and a real lever on Bing. The llms.txt file scores 2.0 out of 10 in Shepard's analysis and measured bot traffic to it is around 0.1%; Anthropic has confirmed it is read by developer tools such as Claude Code and Cursor, which is a reason to publish one for documentation and a weak reason otherwise. We publish one on this site because it costs nothing and describes the company accurately, not because we expect it to move citations.

Where do the experts still disagree?

Several places, and an honest vendor will tell you which. Google's own spokespeople, Glenn Gabe, Cyrus Shepard and Marie Haynes hold that good SEO is good GEO, while Mike King, Eli Schwartz and Andrew Holland argue the mechanics are different enough to be a separate skill; our position is that SEO is the foundation and GEO has its own levers on the brand, earned-media and passage layers. Content length is contested (ChatGPT's median cited page is about 941 words, AI Overviews cite 100 to 300 word passages, and a Semrush study of LinkedIn found 50 to 299 word posts cited most). Whether blocking AI crawlers protects anything is contested too: BuzzStream found 82% to 88% of blocking publishers were still cited through cached training data and third-party mentions. And nobody outside the labs knows how much weight the pre-training corpus carries against live retrieval, which is the largest open question in the field.

Should a mid-sized company care yet?

It depends on the category, and the honest way to answer is to measure. BrightEdge's tracking now puts AI Overviews on nearly half of Google queries, and Semrush measured a 71% rise on commercial searches between November 2025 and April 2026, and Pew measured click-through falling from 15% to 8% when a summary is present. AI search still sends under 1% of visits to most sites in Glenn Gabe's panel, so if your only measure is traffic you may not feel it yet. If your measure is which companies get recommended when a buyer asks, you are already in the race whether or not you have entered. The audit is how we find out where you stand, and the step-by-step guide is what to do about it.

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