AEO: what it is and how to apply it

SEO optimizes for appearing in a list of search results. AEO and GEO largely describe the same set of techniques aimed at getting an AI system to mention or cite a brand within an already-drafted answer, with different shades of emphasis.

AEO puts the emphasis on answering a person's specific questions; GEO, on the generative system's ability to build that answer from multiple sources. Neither replaces SEO: they complement it. You can see the full contrast in our AEO vs GEO comparison.

No, and anyone who promises that isn't being honest. A field study published in 2026 analyzed hundreds of thousands of pages on a single domain before and after applying AEO interventions, comparing them against an unchanged control group.

The platform's own organic growth explained a large share of the increase in referred traffic; the effect directly attributable to the AEO interventions was more modest than expected, and the authors themselves called it suggestive, not conclusive. The practical takeaway is that many industry success stories likely overstate the real causal impact when platform growth isn't isolated.

It helps, but it doesn't guarantee anything on its own. Structured data makes it easier for a system to identify entities, services, or FAQs, and it must always match the content visible on the page.

Google has explicitly stated there are no additional technical requirements for appearing in AI Overviews or AI Mode beyond being indexed and eligible to show a snippet in traditional search. Structured markup adds to that foundation, it doesn't replace it.

An analysis of over 21,000 citations gathered from ChatGPT, Google AI Overviews/Gemini, and Perplexity across 602 questions found that the pages with the most real influence on the answer (not just passing mentions) share several traits: sufficient length to cover the topic, structured formatting, clear semantic relevance, and easily extractable elements like definitions, concrete data, and step-by-step procedures.

The same study distinguishes between how many sources a platform cites (breadth) and how much each one actually influences the final text (depth): Perplexity and Google tend to cite more sources, while ChatGPT concentrates more influence per citation.

Some commercial industry tools talk about visible results in two to six weeks, but that timeframe should be treated as a vendor's rough estimate, not a promise.

The academic evidence available so far suggests that isolating the real effect of an AEO intervention from a platform's or domain's organic growth requires weeks of before-and-after control data, so an honest timeframe can only be given after measuring, not before.

Asking ChatGPT a question once and saving a favorable screenshot isn't enough: that's an anecdote, not a measurement. A reasonable starting point is defining 10 to 15 questions relevant to the business and running them in incognito mode across several platforms (ChatGPT, Gemini, Perplexity, AI Overviews), documenting which answers the brand appears in.

From there, specific metrics get logged: AI visibility, share of voice against competitors, citation rate, prominence, and accuracy of what's said about the brand, repeating the measurement over time instead of relying on a single query. That's exactly what we do in our mention monitoring service.

Before any advanced tactics, it's worth starting with an AI visibility audit: fixing crawling, indexing, and architecture errors; clearly defining the business's entities (what it is, what it offers, to whom); and creating content chunks that are genuinely useful for the questions its audience asks.

On top of that foundation is where it makes sense to add structured data, work on legitimate external mentions, and set up a repeatable measurement system across several AI platforms.