# What is AI SEO, exactly? > AI SEO and GEO are real — but they are not a replacement for traditional SEO. Here's what's actually happening under the hood, and why your Google ranking still determines everything. **Published:** Jun 2026 · 7 min read · AI SEO --- Every few years, a new term enters the SEO industry and people declare that everything has changed. AI SEO — or GEO, Generative Engine Optimization — is the latest. And like most of those moments, the truth is more boring than the hype suggests. AI SEO is real. It matters. But it is not a separate discipline, and it is not replacing traditional SEO. It is an extension of it. If you understand how AI search actually works under the hood, this becomes obvious. ## How AI search actually retrieves information When someone asks ChatGPT a question about your industry, most people imagine the model reaching into its training data and pulling out an answer. That is partially true for general knowledge questions. But for current, specific, or commercial queries — the kind B2B buyers ask — it does not work that way. ChatGPT, Perplexity, Google AI Overviews, and most AI search tools use a technique called Retrieval Augmented Generation (RAG). Instead of relying purely on training data, the model calls a search API in real time, retrieves a set of current web pages, reads them, and synthesises an answer. Here is the part that most "AI SEO" content glosses over: **those search APIs belong to Google and Bing.** - **ChatGPT** with web browsing uses Bing's search API — not coincidentally, Microsoft is OpenAI's largest investor. - **Perplexity** queries a combination of Bing and Google search results. - **Google AI Overviews** draws directly from Google's own search index. - **Claude, Gemini, Copilot** — all the major AI assistants with web access are pulling from the same search infrastructure that has existed for decades. The AI generates the answer. But the source material it reads comes from pages that are already ranking in search. ## The implication is straightforward If your company does not rank on Google or Bing, your company will not show up in AI-generated answers. The AI cannot cite a source it cannot find. And it finds sources the same way it always has — through search indices built by crawling the web. > If you don't rank on Google, you won't show up on ChatGPT. That is not a metaphor. It is literally how the retrieval works. This is not a knock on AI SEO as a concept. It is just an accurate description of the dependency chain. Traditional SEO is not dying — it is the foundation that AI citation is built on top of. ## So what is GEO actually adding? GEO is not a myth. But the things people typically list as "GEO tactics" — schema markup, entity clarity, structured data — are mostly noise. LLMs do not parse HTML or interpret schema. They process embedded tokens — compressed numerical representations of your page's actual text content. When a search API returns your page to an LLM, the model receives tokenized text, not raw markup. The structured metadata sitting in your `` is invisible to it. Based on my own research, I believe ChatGPT adds another layer on top of this: a system that takes the raw search API results, strips the HTML down to clean text, and re-ranks or filters which pages actually get passed through to the model. If that is accurate — and the behaviour I have observed is consistent with it — then what matters is not your markup but how well your page's plain text survives that extraction and whether it surfaces after the re-ranking step. Which is, again, a function of your content quality and your search ranking. Schema does not help you here. The one thing that genuinely differs between traditional SEO and GEO is how queries are formed. Human searchers type short, compressed queries. "B2B SEO agency Indonesia." "Best AI SEO tool." The intent is implicit. Traditional SEO is built around targeting these compressed query forms. LLMs do something different. When a user asks ChatGPT a broad question — "how do I improve my B2B company's visibility on AI search?" — the model does not search that phrase verbatim. It breaks the question down into multiple sub-queries and searches each one independently. This is called query fan-out. It might search: "what is GEO generative engine optimization", then "how do LLMs retrieve web content", then "B2B content strategy for AI search", then "does schema markup help with AI citations". Each sub-query retrieves a different set of pages. The model reads them all and synthesises an answer. **The GEO opportunity is in those sub-queries.** Most companies write broad, category-level content that targets the obvious head terms. Almost nobody writes the niche, specific pieces that cover the exact sub-questions an LLM would fan out to when decomposing a broader topic. A B2B company that has ten niche articles covering the specific sub-questions an LLM generates — not the head terms a human would search — has a meaningful advantage in AI citation over a company with one generic overview article that ranks well for the head term. This is harder than it sounds. You need to think like an LLM decomposing a question, not like a human typing into a search bar. The query forms are different, the specificity is higher, and the content required to answer them well is genuinely niche. But that is exactly why most competitors have not done it. ## What the myths get wrong The most common misconception is that GEO is a shortcut — that you can optimise for AI citation without doing the underlying SEO work. Some vendors are selling this idea. It is not accurate. A second misconception is that AI SEO is primarily about your content style — using certain phrases, formatting answers in a certain way, or structuring content to "sound like" what AI tools prefer. Style adjustments at the margin do not overcome a fundamental lack of search authority and indexation. A third misconception is that the rules have completely changed. They have not. The core of what makes a web page authoritative — genuine expertise, clear structure, legitimate links from relevant sources, technical health — has not changed because ChatGPT exists. ## The practical conclusion If you are a B2B company wondering whether to invest in "AI SEO" as a separate initiative, here is the answer: invest in SEO. Good SEO — technical health, topical authority, quality content, link acquisition — is the same work that produces both Google rankings and AI citations. The companies that will dominate AI search over the next five years are the ones that build genuine authority in their category through traditional SEO discipline. The companies that chase AI-specific shortcuts, without doing the underlying work, will have neither Google rankings nor AI citations to show for it. GEO matters. But it sits on top of SEO — not next to it, and not instead of it.