AEO vs GEO vs SEO (and AIO): Four Names for Work That Mostly Overlaps

AEO vs GEO vs SEO: what is the difference?

Google's guide for site owners on AI features and your website contains a sentence worth reading before any explainer on this topic: "There are no additional requirements to appear in AI Overviews or AI Mode, nor other special optimizations necessary." It settles most of the argument. SEO, search engine optimization, is the work of getting pages crawled, indexed and ranked. AEO (answer engine optimization), GEO (generative engine optimization) and AIO (AI Overviews optimization, or simply AI optimization, depending on who says it) are names for the step after that: getting a page that already qualifies chosen as a source inside an answer.

The popular slogan says SEO gets you found, AEO gets you answered and GEO gets you cited, as if these were three separate ladders. The evidence describes one. Google says a page must be indexed and "eligible to be shown in Google Search with a snippet" before it can appear as a supporting link in AI Overviews or AI Mode. The research paper that named GEO built its test engine on the top five Google results for each query. Being found comes first, and most of being cited follows from it.

Where the terms do differ is narrower, and more useful to know. The thing being judged is a passage or a claim more than a whole page, and the result has to be measured differently, because a citation in an AI answer often produces no click at all. The argument of this piece is that a team should run one plan under one name and split only the measurement.

How do AEO, GEO, AIO and SEO compare?

The four side by side; the evidence behind each row follows.

You will also meet LLMO (large language model optimization) and "AI SEO". They cover the same ground, and neither arrives with a method the others lack.

Where did AEO, GEO and AIO come from?

AEO: built for the answer box and the smart speaker

AEO predates generative AI search by several years. It grew out of the featured snippet, the box at the top of Google's results that puts a page's answer before its link. In a January 2018 post, A reintroduction to Google's featured snippets, Danny Sullivan, then Google's public liaison for search, noted that "with the growth in voice-activated digital assistants, more people are doing voice queries", and that a spoken featured snippet cites its source page and links to it in the Google Home app.

A smart speaker reads one answer aloud, and being that answer is a different goal from ranking third. Kalicube, the SEO consultant Jason Barnard's company, credits him with coining the term in 2017. The tactics from that period still define AEO: put the answer in the first sentence or two under a heading phrased like the question, and use a list or a table when the answer is one. Note what was never on the list: Google's featured snippets documentation says its systems choose snippets automatically, and site owners cannot mark a page as one.

GEO: named by a research paper in 2023

GEO has an exact birth date. On 16 November 2023, six researchers posted "GEO: Generative Engine Optimization" to arXiv; the first version lists Princeton University, Georgia Tech, the Allen Institute for AI and IIT Delhi, and the paper was later accepted at KDD 2024, a major data mining conference. Their test engine worked the way AI search engines of the time did: fetch sources for a query, then have a language model write an answer from them. They rewrote source pages nine ways and scored how much of each answer drew on each source, weighted by how early it appeared, a metric they called Position-Adjusted Word Count.

Three rewrites did best. Adding quotations, adding statistics and citing sources each raised visibility by roughly 30 to 40% on that metric; the abstract's headline figure is "up to 40%". Making the prose more fluent helped too. Rewriting pages in a more persuasive, authoritative tone made no significant difference, and keyword stuffing, the oldest trick in SEO, scored below the unedited baseline. The gains also went mostly to sources further down the list. Applied to the source in fifth place, citing sources raised its visibility by 115.1%. Applied to the source in first place, the same edit lowered it by 30.3%.

Read the setup before the numbers, though. The paper says that "only the top 5 sources are fetched from the Google search engine for every query", and the answers were written by a 2023 OpenAI model. Every page in the experiment had already ranked in Google's top five. GEO, as its inventors defined it, is a way to win more of an answer you are already eligible for. A repeat test on a commercial AI search engine pointed the same way.

AIO: one acronym, two meanings

AIO is the youngest of the three and the most ambiguous. Google began rolling AI Overviews out to everyone in the US on 14 May 2024, after testing them in Search Labs, and SEOs soon shortened the feature to AIO. In that usage, AIO optimization means getting cited in Google's summary box, and lately in AI Mode as well. Others use AIO for AI optimization in the broad sense: every AI answer, on every platform.

The company that publishes this blog is called AIO Copilot and uses the broad sense; our complete guide to AIO covers the page-level checklist. When a client asks for AIO, ask which meaning they have in mind, because only the narrow one comes with its own report in Search Console.

Is AEO different from SEO?

On Google, mostly not, and Google says so in several places. Its documentation states that "the best practices for SEO remain relevant for AI features in Google Search" and lists the usual fundamentals, from crawl access to structured data that matches the visible page. It also says site owners do not need new machine-readable files, AI text files or special structured data to appear.

The ranking machinery is shared too. Google's May 2025 explainer, AI Overviews and AI Mode in Search, says the company integrated its "core web ranking systems" into AI Overviews, which are "built to surface information that is backed up by top web results". Of AI Mode it says the feature is "rooted in our core Search ranking and safety systems". Pages that do well in ordinary results are the pool the AI features draw from.

Even the controls overlap. The same nosnippet, data-nosnippet and max-snippet rules that keep text out of featured snippets also limit what Google shows from a page in AI features. The lever an AEO practitioner pulls for featured snippets and the one an AIO practitioner pulls for AI Overviews are the same line of code. Since 31 August 2026 Google has also offered a switch that applies only to AI features: every site now has a Search generative AI control in Search Console that can exclude its links and content from AI Overviews, AI Mode and Discover's AI features. Inclusion is the default, and Google says the setting "isn't used as a ranking or inclusion signal affecting other parts of Search."

Outside Google, wherever an answer is grounded in a live search, the pattern holds. The AI Performance report in Bing Webmaster Tools lists "grounding queries", which Microsoft describes as the key phrases the AI used when retrieving content it went on to cite. The assistant searched before it answered, and a page that cannot be found for those searches cannot be cited.

Where AEO and GEO really differ from SEO

The unit is the passage, and the query may not be yours

Classic SEO ranks a page against a query; AI features work in smaller pieces. Google's documentation says AI Overviews and AI Mode may use a "query fan-out" technique, issuing multiple related searches across subtopics and data sources to build one response, and that the two features can use different models, so their links differ for the same query. A page can be pulled into an answer for a sub-question it was never written to rank for, and a page that ranks first for the main query can be passed over if it never answers the sub-question cleanly.

Take a sample client, Harbour & Finch LLP, a Toronto law firm that exists only as demo data. Someone asks what a commercial lease review costs in Toronto, and a fan-out search might look separately for typical fees and for what a review covers. If the firm's fees page buries the first and ignores the second, its ranking for "commercial lease lawyer Toronto" does little for it inside the answer. The fix is ordinary editing: answer each likely follow-up question in a short passage that still makes sense quoted alone. Our free AIO readiness checker gives a quick structural read of one page's headings, answer patterns and structured data; treat it as a checklist, not a forecast, since Google says no special markup is required.

Inside the answer, evidence beats emphasis

The GEO results above are the best published guide to what wins once a page is in the candidate set, with the caveat that they come from one study on a 2023 test engine. The rewrites that worked added material a model can check and quote, while a more persuasive tone did little and keyword stuffing hurt. That favours pages written the way a careful reporter writes, with claims tied to a source and numbers that carry a date.

A win may not bring a visit

The largest difference is the scoreboard. In SEO, a ranking that earns no clicks is a failure. In AI answers, being cited without a click is common, and may still be worth something. Pew Research Center tracked the browsing of 900 US adults in March 2025 and found that people who saw an AI summary clicked a traditional result in 8% of visits, against 15% for people who did not see one. They clicked a link inside the summary itself in 1% of visits.

Google's documentation offers the other side: it says clicks from results pages that carry AI Overviews are "higher quality", with visitors more likely to spend time on the site. Both can be true at once. Neither tells you whether your page was the one cited, which is why measurement is where AEO and GEO genuinely need their own methods.

What changed in AI Overviews and AI Mode on 15 October 2026

A week ago Google published More ways to connect with the web from Search, by Hema Budaraju, a vice president of product management at Google. The post describes "continued and substantial increases to the presence of inline links" in AI Mode and AI Overviews, and changes to show those links higher in responses more often. Google is also testing a section at the top of some AI responses that links to official websites, with context on why each link is useful. News carousels are reaching more locations and languages.

For the argument here, the update cuts two ways. Links inside AI answers are becoming more prominent, so being the cited source is worth more than it was a month ago. But the reporting has not caught up. In a statement to Search Engine Roundtable, which had pressed it for click data on launch day, Google said it would "introduce additional metrics over time". For now, you can see that your links were shown in AI features. You cannot see whether anyone clicked them there.

How do you measure AEO and GEO?

Google: impressions, and clicks you cannot separate

Search Console counts AI features inside its ordinary numbers, under the Web search type of the Performance report. Since 3 June 2026 it has also had a separate view: Google's Generative AI performance reports, which reached all sites worldwide on 31 August, while the same data stays in the overall report. The help page for the Search version lists what it holds: impressions in AI Overviews and AI Mode, counted when links to your site were shown, grouped by page, country, device or date.

What it leaves out matters as much: no clicks, no queries, and no split between AI Overviews and AI Mode. The most useful thing to do with it today is set it beside the main report: a page whose AI impressions climb while its clicks fall over the same dates is probably being shown in answers more often without being visited more. Do not add the two reports together, because the AI impressions are already inside the Web totals.

Bing: the closest thing to a GEO metric

Microsoft went further, earlier. Its AI Performance report, a public preview since 10 February 2026, counts how often your pages are cited in Microsoft Copilot, AI-generated summaries in Bing and some partner integrations. It shows total citations, citations by URL and the grounding queries behind them, which Microsoft says are a sample. That is close to what the GEO paper set out to measure, and Google's report has no queries at all.

Everywhere else: sample, and show the margin

For assistants that publish nothing, such as Claude or the Gemini app, the only method is to ask them, repeatedly, because answers vary from run to run by design. A January 2026 study by SparkToro and Gumshoe ran 12 prompts 60 to 100 times each through three assistants, including Claude and Google's AI features. For two of the three, the chance of getting the same list of brands twice in 100 runs was under 1 in 100. The authors concluded that a visibility percentage across many prompts and runs is a reasonable measure and a "ranking position" in an AI answer is not. The GEO researchers sampled five responses per query for the same reason.

Back to the sample client. Say you write 40 prompts a prospective client of Harbour & Finch might type, and run each five times in one assistant: 200 answers. The firm is named in 62 of them, a share of 31%. At 200 answers, the 95% margin of error on that share is about 6.4 percentage points either way, so the honest report is "roughly 25% to 37%". Next month the firm is named in 74 of 200 answers, or 37%. That looks like a six-point gain, but the margin on the difference between two samples of this size is about 9.3 points, so the change sits inside the noise. Detecting a six-point move with the same confidence would take about 480 answers in each period.

Treat that margin as a floor. Five runs of one prompt are not five independent draws, and 40 prompts are themselves a guess at what people ask, so the real uncertainty is wider than the formula says. Our guide to measuring share of model in AI answers covers building the prompt set, and the comparison of AEO tools checks how the trackers on the market count. AIO Copilot's AI search view samples how often assistants name a client against its rivals, shows the margin of error beside the number, and keeps those estimates apart from what it measures directly in Search Console and Bing Webmaster Tools.

Is AEO the same as GEO, and which term should you use?

For AI answers, AEO and GEO now describe the same output, and the market treats them that way. HubSpot sells its tracker as HubSpot AEO, under the heading "Answer Engine Optimization Software", and its own FAQ treats generative engine optimization as another name for it. The two terms have different histories and the same job.

Our recommendation is to use AEO as the internal name for anything that happens inside an answer, and to keep that work inside the SEO plan. AEO names an outcome, being the answer, where GEO and LLMO name a technology. The technology behind answers has already changed once since the term appeared, from snippets read aloud by speakers to summaries written by models, and the name still fits. GEO already means geographic targeting to anyone who runs Google Ads, and AIO is split between a Google feature and AI in general.

The name matters less than the structure behind it. A separate AEO team with its own audit is likely to spend its first weeks rediscovering the crawl problems and thin pages the SEO team already has on its list, because Google's AI features rest on the same index and ranking systems. Run one audit and one backlog. Add the two things that are genuinely new: passages written to answer the sub-questions a fan-out search will ask, with evidence a model can quote, and separate measurement lines for AI impressions in Search Console, citations in Bing and sampled share in the assistants that publish nothing.

Nobody outside the companies that run these systems can watch the step where a model picks its sources. The best evidence on what wins at that step is one paper, tested on a 2023 model. The reporting is months old and still missing clicks. Next year will bring another acronym, probably with a slogan attached. Whatever it is called, ask the two questions that sorted these four: what has to be true before a page can be chosen, and how would you know that it was. For AEO, GEO and AIO, the answer to the first is still SEO. The second is where the new work is.

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