Generative engine optimization (GEO, also called answer engine optimization or AI SEO) means getting your company mentioned, recommended and accurately described in the answers AI tools give, with your pages cited where possible. For Google, it’s still SEO, and Google now says so by name. Its May 2026 guide for site owners puts it plainly: “From Google Search’s perspective, optimizing for generative AI search is optimizing for the search experience, and thus still SEO.”
That doesn’t mean nothing has changed. Being cited in an AI answer is a different result from ranking a page, the AI tools don’t all draw on the same sources, and a lot of what decides whether you’re mentioned happens off your website. The way I’d put it: there are things that help both, and there are things to do very specifically for AI visibility.
Where the term came from
“Generative engine optimization” comes from a 2023 research paper by a team from Princeton and IIT Delhi, published at the KDD conference in 2024. The researchers built an experimental generative search system using GPT-3.5 and tested nine ways of changing source content to see whether that content became more visible in the generated answer.
Adding quotations, statistics and citations to reliable sources performed especially well, although results varied by topic. Keyword stuffing did worst. The paper reported visibility gains of up to 40%, and pages that ranked lower in the search results gained the most.
It’s a real, useful study, and its strongest tactics look a lot like good writing: quote real people, use real numbers, show your sources. But it was a lab experiment on a 2023 model, and it measured how prominently a page’s content showed up in the answer, not traffic, leads or sales. Treat anyone who turns it into “Princeton proved GEO gets you 40% more traffic” with caution.
GEO vs SEO at a glance
| Traditional SEO | Shared by both | Specific to AI visibility |
|---|---|---|
| Ranking pages for searches | Useful, original content | Testing your buyers’ questions across the assistants |
| Technical crawling and indexing | Clear statements of what you do and for whom | Tracking mentions and citations, not just rankings |
| Links and authority | Strong factual support and proof | Analyzing which sources the assistants repeatedly cite |
| Keyword and search demand research | A reputation across trusted sites | Checking access for AI search crawlers and Bing indexing |
What’s genuinely different from SEO
Five things change when the result you want is a mention in an AI answer rather than a ranked page.
Being cited isn’t the same as ranking
A page doesn’t have to rank in Google’s top ten for the exact question to be cited in an AI answer. Ahrefs found that in March 2026, about 38% of the pages cited in Google’s AI Overviews ranked in the top ten for the search, down from about 76% in its study the previous July. Ahrefs also improved how it detects citations between the two studies, so treat that as a rough comparison rather than a clean before-and-after. In a separate 2025 study, across 15,000 prompts, only about 12% of the pages cited by ChatGPT, Gemini and Copilot ranked in Google’s top ten for the original question.
That doesn’t mean rankings stopped mattering. Google says its AI features draw from its own search index through its regular ranking systems. It means the page that gets cited is often not the page that ranks first for the exact question someone typed.
One question becomes many searches
Part of the reason is what Google calls query fan-out: the AI turns one question into several related searches and pulls from the results of all of them. Google’s own example is a question about fixing a lawn full of weeds fanning out into searches for herbicides, removing weeds without chemicals and preventing weeds.
I said it this way in a video about why AI isn’t recommending some companies: “When you ask one of these tools a question, it performs a bunch of searches or fan out queries to find all the pages on the internet that relate to the query at hand.”
The tempting response is to create a page for every variation. Google warns against exactly that: doing it “primarily to manipulate rankings or generative AI responses” violates its spam policy on scaled content.
A lot of it happens off your website
What credible sites say about you can shape how AI tools describe and recommend you. Google’s guide notes that its AI features can show “what’s being said about products and services across the web, including in blogs, videos, and forum discussions.” In practice, that means industry publications, review sites, directories, forums, LinkedIn articles and YouTube can influence whether and how you’re represented, alongside your own site.
It also means you can’t fake it. Google’s guide says that “seeking inauthentic ‘mentions’ across the web isn’t as helpful as it might seem.” The work is earning real mentions next to the problems you solve: getting quoted, publishing where your buyers read, showing up in the lists and comparisons they trust.
Different assistants use different sources
There isn’t one AI search engine. Google’s AI features rely on Google’s search index. ChatGPT uses its own search crawler along with third-party search providers. Microsoft Copilot is tied closely to Bing. Perplexity runs its own crawler and index, and the other assistants have their own search arrangements. The practical point is that being visible in Google doesn’t guarantee you’ll show up everywhere. Your site also needs to be reachable by the crawlers and search systems those products use, which is why Bing indexing and crawler access matter more than many companies realize.
Fewer clicks, so you measure differently
People are less likely to click when an AI answer appears. In Pew Research’s analysis of U.S. browsing behavior from March 2025, people clicked a traditional result on 8% of Google visits that included an AI summary, against 15% when no summary appeared. They clicked a source inside the AI summary itself only about 1% of the time. That shifts measurement from traffic alone toward visibility: whether you’re mentioned, recommended or cited, and how you’re described.
What’s hype, in Google’s own words
Google’s May 2026 guide includes a list of things site owners can ignore for its AI features. Paraphrased, with Google’s wording where it matters:
- llms.txt and other “AI files.” “You don’t need to create new machine readable files, AI text files, markup, or Markdown” to appear in Google’s AI features, because Google Search doesn’t use them.
- Chunking your content. “There’s no requirement to break your content into tiny pieces for AI to better understand it.”
- Writing for AI. “You don’t need to write in a specific way just for generative AI search.”
- Special schema. “Structured data isn’t required for generative AI search, and there’s no special schema.org markup you need to add.” It’s still worth using for regular search.
- Tools claiming insider access. “No third-party tool has access to our internal ranking or AI systems.”
One caveat: that guide covers Google only. It says nothing about how ChatGPT, Perplexity or Claude choose sources, and nobody outside those companies knows exactly how they do.
What stays the same
Most of what makes a company visible in AI answers is what made it visible in search, done properly:
- Pages search engines can find and read, with your important content in the page itself.
- Original content with real experience behind it. Google says content that’s “unique, compelling, and useful” will likely influence your presence in AI search “more than any of the other suggestions” in its guide.
- Clear statements of who you serve and what you do, so a machine can describe you accurately.
- Real proof: results, named clients where you can, specifics.
- A reputation that shows up elsewhere, consistently, across trusted sites.
That’s why, when owners ask me whether answer engine optimization is different from SEO, my answer is that it overlaps a lot. Much of the underlying work is shared. If you already have a solid SEO program, AI visibility work should extend it.
What’s worth paying for
If someone is pitching you GEO, the question is whether it’s new work or your existing SEO with a new invoice. Real AI visibility work usually includes:
- Research across the assistants. Running the questions your buyers actually ask in ChatGPT, Gemini, Perplexity and the others, more than once, and recording whether you’re mentioned, recommended or cited, and which sources get cited instead.
- A plan for off-site sources, based on what that research shows: the publications, directories, forums and comparison pages the assistants actually draw on in your category.
- Fixes to what blocks you, like crawler access, Bing indexing or pages that don’t say clearly what you do.
- Measurement that admits its limits. You still can’t cleanly attribute every AI mention to revenue. But “AI visibility can’t be measured” is now outdated. Google added reports to Search Console in June 2026, available to every site since August, that show impressions from its AI features, and Bing Webmaster Tools now reports citations in Microsoft’s AI experiences. Both measure appearances and citations, not recommendations or sales. A provider should be able to show you whether visibility is moving, even if the path from citation to sale is imperfect.
Before you buy, ask what you’ll actually receive. I’d expect a baseline of where you appear today, the questions or topics being tracked, the sources competitors are being cited from, the specific changes the provider plans to make, and a repeatable report showing what changed. If a proposal can’t show you the starting point or explain how success will be measured, you’re being asked to buy a label. Agree up front on a review point where you decide whether to continue, change the scope or stop.
Be wary of anyone who leads with llms.txt, special schema or rewriting your whole site “for AI,” or who guarantees you’ll be recommended. Nobody can promise that. And apply a simple test to any tactic: if it would embarrass you in front of a buyer, it isn’t worth whatever visibility it buys.
What’s the difference between AEO, GEO and AI SEO?
Today the three overlap heavily, but they didn’t start in the same place. AEO has long been used for direct-answer results like featured snippets and voice search. GEO was coined specifically for generative AI engines. AI SEO is the broadest marketing label. In practice, providers now use all three for much the same work. What matters is whether the work starts from the questions your buyers actually ask.
What to ask anyone selling you GEO
If somebody sells you GEO, don’t ask whether GEO is real. Ask what they’re doing that your SEO program isn’t already doing. If the answer is research across the assistants, citation analysis, crawler access, off-site source work and AI-specific measurement, there’s real work there, as long as it fills a real gap. If you already pay for SEO, ask the provider to mark which activities your current agreement already covers, which are genuinely new, and what each costs. If the answer is llms.txt, special schema and a new acronym on the invoice, I’d keep my money.
Sorting out which GEO work fills a real gap in your program is the kind of review I do in AI SEO consulting. Here’s how to reach me.
