Start a conversationChatGPT Search, Google AI Overviews, Perplexity and Copilot answer the question instead of listing ten links. This is the work of being retrievable, quotable and consistently described across all of them — the hub for generative engine optimization and answer engine optimization both.
Overview
AI SEO is the practice of making a site’s content retrievable, quotable and accurately represented by systems that generate answers rather than return links (e.g., ChatGPT Search, Google AI Overviews, Perplexity, Claude and Microsoft Copilot). These systems work by retrieval-augmented generation: a query triggers a search against an index or a live crawl, a handful of sources are retrieved, and a language model synthesizes an answer from them, usually with citations. Visibility therefore depends on two separate things: being retrieved at all, and being written in a way that survives summarization.
Two named sub-disciplines sit underneath it and overlap heavily without being identical. Generative engine optimization (GEO) concerns presence and framing inside a synthesized response (whether your brand is part of the answer at all, and how it is characterized). Answer engine optimization (AEO) concerns being the source quoted for a specific question, and descends directly from featured snippet and People Also Ask work. The discipline is young, the measurement is unstable, but the fundamentals are still recognizably SEO.
Who it's for
Before anything else, the crawler has to get the content. GPTBot, ClaudeBot, PerplexityBot and their peers largely do not execute JavaScript, so a client-side rendered application can be invisible to them while ranking normally in Google. robots.txt directives, blanket bot-blocking at the CDN or WAF, and paywalls all decide this before a word of content matters.
Retrieved content still has to be easy to lift. Explicit claims, stated numbers with units and dates, self-contained paragraphs, clear headings and Schema.org markup all make a passage quotable without the surrounding page. Copy that depends on three earlier paragraphs for its meaning tends to be paraphrased badly, or dropped in favour of a competitor who simply said the thing.
A model assembles its understanding of your company from many sources at once: your site, Wikipedia, Crunchbase, G2, LinkedIn, review platforms, news coverage. Where those disagree about what you sell, who you serve or what you are called, the answer it generates hedges or gets it wrong. Consistent naming, Organization schema, sameAs references and corroborating third-party sources resolve the ambiguity.
There is no rank one. The usable metrics are share of voice across a fixed set of prompts, citation frequency by engine, sentiment and accuracy of how you are described, and referral sessions from assistant domains. Answers vary between runs and between users, so the unit is a sampled prompt set tracked over time, not a position.
In this area
Presence and framing inside a synthesized answer: content that survives summarization, and an entity footprint models can resolve.
Being the source quoted for a specific question. Question-shaped pages, direct answers, and markup where it is genuinely warranted.
What's included
A fixed set of buying-intent prompts run across ChatGPT, Perplexity, AI Overviews and Copilot, so you know where you stand before anything changes.
What GPTBot, ClaudeBot and PerplexityBot actually receive from your servers — robots.txt, CDN rules, rendering and status codes, checked against real requests.
Organization, Product and FAQPage markup, sameAs references and consistent naming across the third-party sources these models read alongside your site.
Rewrites and structural edits on the pages that matter most, so a passage can be lifted and quoted without losing its meaning.
Not sure which of these you actually need?
Request a discovery callProcess
1
A fixed prompt set run across the major engines, scored for presence, accuracy and sentiment.
2
Crawler logs, robots.txt, CDN rules and rendered output checked against what each bot actually receives.
3
Entity, schema and content work shipped in priority order, with tickets your developers can build.
4
The same prompt set rerun, movement attributed to specific changes, and the roadmap updated.
FAQ
Largely yes on fundamentals: crawlability, clear content, structured data and genuine authority still decide it. It differs meaningfully in two places: content has to be structured to survive being summarized, and measurement moves from ranked positions to share of voice across a prompt set. Anyone claiming it is entirely new is selling something.
They overlap. GEO is about presence and framing inside a synthesized response (whether you are mentioned and how you are described). AEO is about being the source quoted for a specific question. GEO is closer to brand and entity work; AEO is closer to snippet and schema work.
No, and I would be wary of anyone who does. These systems are non-deterministic, the same prompt returns different answers to different users, and no vendor has an index-level lever. What I can do is remove the reasons you are currently excluded and measure the change honestly.
Usually technical SEO, because the two share a foundation. If Googlebot cannot render your pages, neither can GPTBot. If the crawling and indexing side is already sound, this is the right next piece of work rather than a replacement for it.
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