GEO vs SEO vs AEO: what changes, and what to do first.

GEO vs SEO, with AEO somewhere in between, is now a budget question for most B2B marketing teams. SEO, search engine optimization, is the familiar one: earning a place in Google’s list of results. AEO, answer engine optimization, and GEO, generative engine optimization, are the newer two, and they aim at something else: getting your company named, and ideally linked, inside the answer an AI tool gives when a buyer asks a question.

We run SEO, AEO and GEO as one program, so weigh what follows with that in mind. It is also why this guide is plain about what the acronyms do not change, what nobody can promise, and when the money is better spent somewhere else.

The three terms in one minute

• SEO, search engine optimization. Making a site easy for search engines to crawl, understand and rank, so its pages appear in the results for what buyers search. Success is a position on the page and a click. It is now often called traditional SEO, to tell it apart from the other two.
• AEO, answer engine optimization. Shaping pages so a search engine or assistant can lift a direct answer from them: featured snippets, voice answers, and now Google’s AI Overviews and AI Mode. Success is being the answer, or the source quoted in it.
• GEO, generative engine optimization. Earning a mention or a citation in answers written by large language models such as ChatGPT, Gemini, Perplexity, Claude and Copilot, which assemble a response from many sources instead of ranking any one of them. Success is being named, described accurately and recommended.

You will also meet LLMO (large language model optimization), AI SEO, AIO and AI search optimization. If you came here asking what SEO for AI is called, or how AI SEO differs from traditional SEO, that is the answer: several names, no standard yet, and the same job underneath.

GEO vs AEO: is there a real difference?

AEO and GEO differ mainly in where they started. AEO targets the short, direct answers search engines display, such as featured snippets and Google’s AI Overviews. GEO targets citations inside answers that AI models write, in tools such as ChatGPT and Perplexity. In practice, the work is almost the same.

AEO is the older term. It grew up around featured snippets and voice assistants, when the goal was to be the one answer read aloud or boxed at the top of Google. GEO arrived in late 2023, named in a paper by researchers at Princeton and IIT Delhi, just as large language models began answering questions in full paragraphs.

The line between them has dissolved. Google’s AI Overviews are a search result and a generated answer at once, and what wins in one wins in the other: clear answers, specific facts, a company the engines can identify, and other sites that vouch for it. Even the vendors disagree on the label. HubSpot now uses AEO as the umbrella for both, while Semrush and many of the newer AI visibility tools say GEO.

The distinction worth making is not AEO against GEO. It is being ranked against being named. The rest of this guide uses AEO and GEO together for the second job.

AEO and GEO vs SEO, side by side

Most AEO vs SEO comparisons stop at definitions. This is what changes in practice: one website, two jobs.

What has actually changed in search

The scale is no longer in question. Google says its AI Overviews reach more than 2.5 billion people a month, and that AI Mode, its conversational search, passed a billion monthly users in July 2026. OpenAI counts about 1.2 billion weekly users. In Conductor’s sample of almost 22 million searches tracked in late 2025, an AI Overview appeared on about a quarter of them.

What changed most is the click. Pew Research Center tracked nearly 69,000 real Google searches made by 900 US adults in March 2025, and the gap is stark.

Ahrefs, comparing December 2025 with December 2023 across 300,000 informational keywords, found that an AI Overview now comes with a 58% lower average click-through rate for the page ranked first.

Two findings stop this from being a eulogy for SEO. First, search has not shrunk. Gartner forecast in 2024 that traditional search volume would fall 25% by 2026; instead, Google reported in July 2026 that AI Mode was adding to the total number of searches. Second, being inside the answer pays. Seer Interactive, tracking 53 brands and more than five million queries, found that pages cited in an AI Overview earned 120% more organic clicks per impression than pages that were not, though still fewer than when no Overview appeared at all.

So the shift is not from search to AI. It is from a click on a list to a decision shaped by an answer, with fewer visits afterwards and, as the measurement section shows, better ones.

Why it matters more in B2B

A consumer asking for a recipe loses little if the answer skips a website. A B2B buyer asking which vendors to consider is building a shortlist, and shortlists decide deals. In 6sense’s 2025 survey of nearly 4,000 B2B buyers, the vendor that won was already on the shortlist on day one 95% of the time, and buyers first contacted a seller about 61% of the way through their journey. Most of the deciding happens before anyone fills in your form.

AI tools now sit inside that early stretch. In G2’s March 2026 survey of about 1,000 B2B software buyers, 51% said they now start their research with an AI chatbot more often than with Google, up from 29% a year earlier, and 69% said chatbot guidance had led them to a different vendor from the one they planned to choose. Estimates of how many buyers use AI at all run from 63% in a TrustRadius survey to 94% in Forrester’s and in 6sense’s, because each asks a different question, but none of the recent surveys found buyers ignoring it.

The same research carries a warning for anyone who hears this as the end of the website. In TrustRadius’ January 2026 survey of more than 1,800 buyers, nearly all of those who used AI checked its answers at least some of the time, and demos, trials, past experience and peer reviews still outweighed AI at the final choice. The answer gets you onto the list. Your site, your reviews and your people still have to win from there.

Ranking and being cited are different jobs

This is the finding that turns AEO and GEO from a rebrand into real work. If AI tools simply quoted whatever ranked first, SEO would cover everything. They do not.

• The fall for AI Overviews is the striking part. In Ahrefs’ early 2026 data, roughly 31% of cited pages ranked between 11 and 100 for the search, and another 31% ranked lower still.
• For the assistants, more than 80% of the citations came from pages that did not rank for the question at all. Perplexity, which leans hardest on live search, overlaps with Google the most.

Why the gap? AI tools break a question into several narrower searches, a technique called query fan-out, and cite whichever pages answer those best; Ahrefs puts much of the AI Overview change down to it. The tools also lean on sources a results page underweights: review sites, comparison articles, documentation, forums and trade publications. And they favour a passage that answers cleanly over a page that ranks well but buries the answer halfway down.

Rankings still matter. AI tools search the web before they answer, and a page that no index can read gets cited by nobody. But a strong ranking is no longer proof that you are in the answer. That has to be checked on its own.

What actually moves AI visibility

Most of it is ordinary good practice, done more deliberately. It falls into four areas.

The page itself

• Answer first. Open each section with the direct answer in a sentence or two, then the detail. An engine lifting a passage takes the one that stands on its own.
• One question per section, with the question, or something close to it, as the heading.
• Specific, checkable facts: numbers, named methods, dates and short quotes from people who know. In the experiments behind the paper that named GEO, adding statistics, quotations and references raised a page’s visibility in generated answers by up to 40%, while stuffing in keywords did worse than changing nothing.
• Tables and lists where the content really is a comparison or a sequence. They are easy to lift whole.

The gains in those experiments were largest for pages that ranked lower in search, which is good news for smaller companies. They ran on a simulated engine, though, so treat the numbers as a direction rather than a promise.

A rewrite, before and after

Here is the difference on a typical B2B page. The question is one buyers really ask; the company and its numbers are placeholders.

The second version answers in its first sentence, names the factors a buyer can check against their own situation, and still makes sense if an engine lifts it off the page. It also tells the buyer something. The first would read the same on any company’s site, which is exactly why no engine quotes it.

Your company as an entity

• Say what you are the same way everywhere. An AI tool has to know what your company does, for whom and where before it can recommend you. Your site, your LinkedIn page, your Google Business Profile and every directory listing should tell the same story.
• Mark it up. Organization, Service, Article and FAQ schema make those facts machine-readable. It helps engines understand you, though nobody has shown that it wins citations on its own.
• Keep names consistent: one name for each product, service, person and category, used everywhere.

What other sites say about you

This is the part SEO underweights and AI tools weigh heavily. In G2’s March 2026 survey, 43% of software buyers said review sites shaped their shortlist, more than the 36% who said vendors’ own websites did, and those reviews are public pages that AI tools can read. Get reviewed where your buyers look: G2, Capterra or TrustRadius for software, Clutch for services. Get into the comparison articles and industry roundups in your category, write for the trade publications your buyers read, go on their podcasts, and answer questions where they talk, Reddit and LinkedIn included.

Access for the machines

• Let the AI search crawlers in. Check that your robots.txt does not block them, OAI-SearchBot for ChatGPT and PerplexityBot among them. Blocking the crawlers that collect training data is a separate decision.
• Put the content in the HTML. Many AI crawlers do not run JavaScript, so text that only appears after a script runs may be invisible to them.
• Keep the basics sound: fast pages, indexed in both Google and Bing.

What we did on our own site

We built katama.io the same way, so you can inspect it. Our robots.txt names each AI crawler and lets every one of them in. Every service page carries a short, direct answer near the top. Each page has structured data describing the company, the service and the questions it answers. The words are in the HTML itself, not loaded by scripts. And a plain summary for language models sits at /llms.txt, which some AI tools read and others ignore. It is too early to report what this has done for us, and we will not guess.

Common GEO and AEO mistakes

• Running GEO as a separate project. A second agency editing the pages your SEO team already works on means two teams undoing each other’s changes. Run one program with two scorecards.
• Blocking the crawlers by accident. Some CDN and security services now block AI crawlers by default, or with a single switch, and robots.txt rules copied from a template can shut out the search crawlers along with the training ones. Check what actually gets through.
• Hiding the answers. Text that loads only after a script runs, appears only when someone clicks, or sits inside an image may never reach an AI crawler.
• Judging by one screenshot. A single ChatGPT answer proves nothing either way. Answers change from run to run, so measure across many questions and many runs.
• Writing for the engine instead of the buyer. Keyword stuffing did worse than doing nothing in the experiments behind GEO, and mass-produced pages give an engine nothing worth quoting. Hidden instructions aimed at AI crawlers are worse still.
• Ignoring what the AI already says about you. Old pricing, a retired product or the wrong category, repeated to every buyer who asks. Correct it at the source: your site, your profiles and the directories that list you.
• Paying for a guaranteed citation. Nobody controls what the engines say, and they change without notice.

Which to fund first

Not by acronym. The work happens on the same pages, so splitting a budget into an SEO line and a GEO line usually means two teams editing one website. Decide by which gap is costing you more.

Most companies find themselves in two or three of these rows. The order still holds: the foundation first, because it is cheap and everything depends on it; then the pages that should be doing the answering; then the authority that takes longest to build. Changes to a page’s structure can alter which passages get quoted within weeks. Authority builds over quarters, and anyone who promises otherwise is guessing.

How to measure it without fooling yourself

In SEO, rankings explain movement. AI answers need a baseline of their own, and most companies have never taken one.

Build a question set

• Write down 20 to 50 questions your buyers really ask before they buy: “best [category] for [type of company]”, “[competitor] alternatives”, “how do I fix [the problem you solve]”, “what does [your service] cost”. Take them from sales calls, not only from keyword tools.
• Run each one in ChatGPT, Google’s AI Overviews and AI Mode, Perplexity and Gemini. Record whether you are named, where in the answer, who is named instead, which pages are cited, and whether what is said about you is accurate.
• Run every question more than once. Answers change between runs, so a single check proves little. Track your share of mentions across the whole set, the same way, every month.

That baseline tells you which rows of the table above you are in, and it is the number every later month gets compared with.

Read the traffic carefully

AI referrals are still small. In Conductor’s 2025 study of almost 14,000 websites, visits from AI tools made up about 1% of all traffic, nearly nine in ten of them from ChatGPT. In IT, the highest sector, the share was 2.8%. Those visitors tend to convert well: Ahrefs found that AI search brought 0.5% of the visitors to its own site but 12.1% of its signups. That is one site, so treat it as a signal rather than a benchmark.

Most of the influence never shows up as a referral. A buyer reads an answer, then types your name into Google or goes straight to your site. So watch branded search and direct visits alongside AI referrals.

Track AI referrals in your analytics

Most analytics setups file AI visits under Referral, mixed in with everything else. In Google Analytics 4, give them a channel of their own.

• Under Admin, Data display, Channel groups, create a new group from the default one and add a channel called AI assistants.
• Set its condition to source matches regex, with the expression below, then reorder the channels so AI assistants sits above Referral. Channels are checked in order, so below Referral it would never be reached.

.*(chatgpt|openai|perplexity|gemini\.google|copilot\.microsoft|claude\.ai|meta\.ai|deepseek).*

• ChatGPT adds utm_source=chatgpt.com to many of the links it shows, so those visits usually arrive already labelled.
• Clicks from Google’s AI Overviews and AI Mode arrive as ordinary Google organic traffic. No setting separates them, which is one more reason to watch branded search.

Then carry the answer into your CRM. Add ChatGPT and the other AI tools to the “how did you hear about us” question on your forms, store the answer on the contact record, and ask it again on every first call. That is what lets a pipeline report show the deals that started with an AI answer.

Then judge it the way you judge everything else: on pipeline. Visibility that never turns into a qualified conversation is a vanity metric with a new name. Connecting the two is revenue operations work: tracking which searches and AI referrals became opportunities.

Where to start

Start with the question set. Run it this week, before you buy anything or rename a single page. If AI tools already name you accurately, keep doing what works and protect it. If they name competitors instead, look at what those competitors have that you do not: clearer answers, more reviews, more mentions in the places the engines read. That list is your plan.

If the question set is hard to write, the problem sits upstream, in knowing exactly who you sell to and what they ask. That is ideal customer profile and target account work, and it decides what every page should answer.

And if you would rather have someone run the baseline and the work, that is what our AI search and digital visibility service does, judged on pipeline rather than rankings.