AI SEO vs GEO vs AEO vs LLMO: what's the difference?

GEO vs SEO comes down to where the result appears and what counts as a win. SEO (search engine optimisation) is the work of being found and chosen in a list of search results, while GEO (generative engine optimisation) is the work of being included and cited in the answers that AI tools write. AEO (answer engine optimisation) and LLMO (large language model optimisation) describe the same shift from slightly different angles, and AI SEO is the umbrella term that covers all of it. The labels overlap far more than they differ: Google and Microsoft both say the same foundations sit under classic results and AI answers. This guide defines each term, explains what is genuinely new, and sets out what a small business should do first.

SEO, GEO, AEO, LLMO and AI SEO in one minute

Here is the short version of each term: what it stands for, where the result shows up and what winning looks like.

• SEO, search engine optimisation. Making pages easy for a search engine to crawl, index and rank, and worth choosing once they appear. The result is a link with a snippet in Google or Bing. Winning looks like a higher position, more clicks and more enquiries from those clicks.
• GEO, generative engine optimisation. Making your pages and your brand the material an AI system draws on when it writes an answer. The result is a citation, a mention or a recommendation inside Google AI Overviews and AI Mode, ChatGPT search, Perplexity, Gemini, Copilot or Claude. Winning looks like being named in the answers to the questions your buyers ask, with a link where the tool offers one.
• AEO, answer engine optimisation. The same goal seen through the lens of the question: being the page that supplies the direct answer. The idea is familiar from Google's featured snippets, which already answer a question at the top of the results, and Google says its systems decide which page becomes one. Winning looks like being quoted for a defined set of questions.
• LLMO, large language model optimisation. A label for being described accurately when a chatbot talks about your business from what it has read across the web, whether or not it ran a live search. Winning looks like the model getting your services, location and customers right.
• AI SEO. The umbrella term. It is used to mean optimising for AI search, which is everything above, and also to mean using AI tools inside SEO work, such as clustering keywords or drafting outlines. When a supplier says they do AI SEO, ask which of the two they mean. Our guide to AI SEO covers the umbrella in full.

Microsoft Advertising put it plainly in October 2025: "Whether you call it GEO, AIO, or SEO, one thing hasn't changed: visibility is everything." AIO is yet another label for the same work, so do not be surprised when a sixth acronym turns up.

These are mostly new names for new surfaces and new ways of measuring, built on one set of foundations. Nobody has to choose between SEO and GEO; the question is how much of the newer work to layer on top, and that depends on how your buyers search.

Where the term GEO came from

GEO is unusual among marketing acronyms in having a traceable origin. The term was formalised in a research paper titled "GEO: Generative Engine Optimization" by Pranjal Aggarwal, Vishvak Murahari, Tanmay Rajpurohit, Ashwin Kalyan, Karthik Narasimhan and Ameet Deshpande, from Princeton University, the Indian Institute of Technology Delhi and two independent researchers. It was first posted to the arXiv preprint server in November 2023 and presented at the KDD 2024 data mining conference in Barcelona in August 2024.

The paper defines a generative engine as a system that retrieves relevant documents and uses a large language model to write a response grounded on those sources, with citations. The authors argued that this disadvantages website owners, who lose the visit when the answer is given directly and have little control over how their content is used.

Their experiment is what gave GEO its reputation. They built a benchmark of 10,000 queries, fetched the top five Google results for each, had a language model write an answer from those pages, and measured how much of the answer each source accounted for. Then they rewrote one source at a time using nine methods and measured the change.

• Adding citations to credible sources, quotations and statistics were the strongest methods, lifting a source's share of the answer by roughly 30% to 40% on the main metric.
• Making the text more fluent and easier to understand also helped, by around 15% to 30%.
• Keyword stuffing gave little to no improvement and was classed as non-performing. A more persuasive, authoritative tone made no significant difference either.
• Overall the authors reported visibility gains of up to 40%, and up to 37% when they tested on Perplexity.ai, a live product. Which method worked best varied by subject area.

Two caveats before you act on this. First, it is one lab study, run with GPT-3.5 answering from five pages and with the subjective part of the scoring also done by GPT-3.5, so treat it as evidence of a direction rather than a ranking rulebook for Google, ChatGPT or anyone else. Second, the effect was strongest for pages that ranked lower in the classic results: when every source was optimised at once, citing sources lifted the fifth-ranked page's visibility by 115% while the top-ranked page lost about 30% on average. That is the clearest hint in the research that AI answers can reshuffle who gets seen.

How classic search and AI answers work

Classic search has four steps. A crawler fetches your pages, an index stores them, a ranking system orders them for a query, and the results page shows a list of links with short snippets. You compete for a position, and the searcher does the reading and the choosing.

An AI answer changes the last step. The system still retrieves pages, but a model then writes a single response and attaches supporting links. Google says AI Overviews and AI Mode may use a technique it calls query fan-out, issuing multiple related searches across subtopics and data sources to build the response, and that its models identify more supporting pages while the response is being written, so the set of links can be wider than on a classic results page. The two features may use different models and techniques, so their answers and links vary.

Google is also candid that AI Overviews do not appear everywhere: it says they show only when its systems judge that an overview adds something to the classic results, so on many searches they do not appear at all. For many of the searches that matter to a trade or professional services business, the classic list is still what a buyer sees.

Microsoft describes the mechanics on its side in similar terms. Assistants like Copilot break a page into smaller structured pieces, a process it calls parsing, evaluate each piece for authority and relevance, and assemble an answer from several sources at once. Ranking still happens, but to pieces of content rather than whole pages. Microsoft also says Copilot is powered by Bing's search index, which is the plain reason classic indexability still matters for AI answers.

ChatGPT is the other big surface. OpenAI introduced ChatGPT search on 31 October 2024 for Plus and Team subscribers and its SearchGPT waitlist, opened it to all logged-in users on 16 December 2024, and made it available to everyone with no sign-up from 5 February 2025. OpenAI says ChatGPT decides for itself when a question needs the web, that its search uses third-party search providers as well as content supplied directly by publisher partners, and that any website can choose to appear in its results, which are shown as links to sources alongside the answer.

What stays the same: the SEO foundations AI answers rely on

Google's guidance on its AI features undercuts most of the hype. It says you can apply the same foundational SEO best practices to AI Overviews and AI Mode as to Google Search overall, that specific optimisation for these features is not required, and that there are no additional technical requirements. To be eligible as a supporting link, a page needs to be indexed and eligible to show in Google Search with a snippet. Google's 2026 guide to optimising for its generative AI features adds one condition: the site must not be excluded through Search Console's Search generative AI control, which includes sites by default.

Google's list of fundamentals that continue to be worthwhile reads like any good SEO checklist:

• Crawling allowed in robots.txt, and by any CDN or hosting layer in front of the site.
• Content made easy to find through internal links.
• A good page experience for visitors.
• Important content available as text, supported by quality images and video where relevant.
• Structured data that matches the visible text on the page.
• Up-to-date Merchant Center and Business Profile information.

In May 2025 Google's John Mueller set out the technical floor: Googlebot is not blocked, the page returns an HTTP 200 status code, and the page has indexable content. Meeting those requirements, he wrote, covers you for search generally, including AI formats.

The same post pointed back to Google's long-standing content advice: its systems look for signals of experience, expertise, authoritativeness and trustworthiness, known as E-E-A-T, with trust the most important of the four, and it strongly encourages accurate bylines. Google also says it has no preferred word count, a useful corrective to the GEO advice that circulates about ideal chunk sizes and answer lengths.

Microsoft says the same from the Bing side: crawlability, metadata, internal linking and backlinks remain essential for being discovered, and are the starting point rather than the whole job.

What is genuinely different about GEO and AEO

With the foundations agreed, here is what actually changes, sourced to Google, Microsoft and the Pew Research Center, with nothing from a vendor's correlation study.

The result is an answer, so the scoreboard changes

In classic search your page is the result. In an AI answer your page is one of several ingredients, and success means being cited, mentioned or recommended inside the text. A page can rank well and be left out of the answer, or sit lower and still be quoted for the one passage that fits.

Fewer clicks when an answer appears

The Pew Research Center analysed the browsing data of 900 US adults for March 2025 and published the results on 22 July 2025. When a Google results page carried an AI summary, users clicked a traditional result in 8% of visits, against 15% when there was no summary. They clicked a link inside the summary itself in just 1% of visits, and they were more likely to end their browsing session entirely on pages with a summary, 26% against 16%.

Two details stop that being a panic story. Only 18% of the searches in Pew's dataset produced an AI summary at all, and Google says clicks from results pages with AI Overviews are higher quality, with visitors more likely to spend longer on the site, so it advises measuring sales, sign-ups and engagement rather than clicks alone. Both can be true at once: a page can get fewer visits from a query, and better ones.

Questions get longer and more conversational

Pew found that AI summaries appeared on 8% of one- or two-word searches, rising to 53% of searches with ten or more words and 60% of searches that began with a question word such as who, what, when or why. Google says people using its AI experiences ask longer and more specific questions, then follow up to dig deeper. The unit of work becomes the question a buyer actually asks, with its follow-ups, rather than a two-word keyword.

Passages matter as much as pages

Because assistants lift pieces, Microsoft's advice is about the shape of a page: a title, meta description and H1 that align; headings that work like chapter titles instead of vague labels such as "Learn more"; direct question and answer pairs, which it says assistants can often lift word for word; and lists and tables that break details into reusable segments. It warns against long walls of text, answers hidden in tabs or expandable menus because AI systems may not render hidden content, core information only in PDFs, and key facts only in images.

Off-site presence counts for more

Pew found that Wikipedia, YouTube and Reddit were the most frequently cited sources in both AI summaries and standard results, and that government websites were more common in AI summaries (6% of sources) than in standard results (2%). An answer about your category can be assembled from Reddit, YouTube and a government page before it reaches your site, so reviews, profiles, consistent business details and mentions on the sites that get cited are part of GEO in a way they were only loosely part of SEO.

Separate crawlers with separate rules

Each AI company runs its own bots, with its own split between search and training. That is the most practical difference of all, so it gets its own section.

AI crawlers: the technical difference most sites miss

A page cannot be cited by a tool whose crawler never saw it. Google's AI features ride on Googlebot, but ChatGPT, Perplexity and Claude each use their own crawlers, and a bot filter, a CDN security rule or a copied robots.txt template can turn those crawlers away without anyone noticing. Here is who is who, as each company documents it at the time of writing.

• OpenAI. OAI-SearchBot surfaces websites in ChatGPT search, and OpenAI says sites opted out of it will not be shown in ChatGPT search answers. GPTBot crawls content that may be used to train OpenAI's foundation models, and disallowing it signals that your content should not be used for training. The two settings are independent, so you can allow search and refuse training, and a robots.txt change takes about 24 hours to reach OpenAI's search systems. ChatGPT-User fetches a page when a person asks ChatGPT about it, and because a user triggered the visit, robots.txt rules may not apply.
• Perplexity. PerplexityBot surfaces and links websites in Perplexity results and is not used to collect content for foundation models. Perplexity recommends allowing it in robots.txt along with its published IP ranges, and it publishes step-by-step allow rules for Cloudflare and AWS web application firewalls because those products can block it. Perplexity-User handles user-requested fetches and generally ignores robots.txt.
• Anthropic (Claude). ClaudeBot collects content that may contribute to model training. Claude-SearchBot analyses content to improve the relevance and accuracy of Claude's search results, and Claude-User fetches pages when a person asks Claude a question. Anthropic says disabling either of the last two may reduce your site's visibility in its search results.
• Google. Robots.txt rules for Googlebot control crawling for Search, including AI Overviews and AI Mode. Google-Extended is a separate robots.txt token with no user agent of its own; it governs whether crawled content may be used to train future Gemini models and for grounding in Gemini apps and Vertex AI, and Google says it does not affect a site's inclusion in Google Search and is not a ranking signal. To limit what Google shows from a page, including in AI features, use nosnippet, data-nosnippet, max-snippet or noindex; more restrictive settings limit how your content is featured in its AI experiences. Since 31 August 2026, Search Console also has a Search generative AI setting that includes a site in AI Overviews and AI Mode by default and can exclude the whole site from them without affecting classic results.

Two technical footnotes. The Robots Exclusion Protocol, published by the IETF as RFC 9309 in September 2022, states that its rules "are not a form of access authorization", which is why user-triggered fetchers can ignore it. The same standard says a crawler must assume a whole site is disallowed while its robots.txt is unreachable because of a server error, so a broken robots.txt can lock every well-behaved bot out at once.

An AI crawler is often blocked by accident, and nothing flags it: Google traffic looks normal while the site never turns up in ChatGPT or Perplexity answers. Check what the server actually does, as well as what the file says.

Is GEO just SEO with a new name?

Mostly, yes, and the parts that are new are real. Here is the balanced verdict from the sources above.

Google's position is that no special optimisation is required for its AI features and that existing SEO fundamentals continue to be worthwhile. Microsoft's is that the fundamentals still matter but selection now happens at the level of content pieces, so structure and clarity carry more weight. The GEO researchers argued that classic SEO is not directly applicable to generative engines, yet their strongest finding was that adding evidence helps while keyword stuffing does not, which reads less as a rejection of SEO than as a rejection of its worst habits.

Put together, the work breaks down roughly like this.

• Same as SEO: crawlable, indexable, fast pages; internal links; original content written by someone who knows the subject; structured data that matches the page; accurate business listings; links and mentions from other sites.
• Different emphasis: a direct answer near the top of each page and each section; evidence a model can lift, meaning numbers, named sources and short quotes; question-shaped headings; the same facts about the brand everywhere; explicit access for the AI search crawlers; and measurement by citations and mentions as well as rankings.

So treat GEO and AEO as an extension of SEO rather than a replacement for it, and be wary of anyone selling them as a separate silo. A site with weak SEO foundations struggles in AI answers for the same reasons it struggles in classic results. That is how Mojo Dojo runs its AI SEO services in Australia: the SEO base first, then the AI-specific layer of crawler access, answer-first pages and entity consistency on top, measured side by side.

Common mistakes and myths

Most of the damage comes from a short list of errors, several of them sold as techniques.

• Myth: you need a separate GEO tech stack or special markup. Google says there are no additional technical requirements for AI Overviews or AI Mode beyond being indexed and eligible for a snippet. Spend the budget on the pages instead.
• Mistake: keyword stuffing under a new name. It gave little to no improvement in the GEO study, and Google's spam policies, which cover attempts to manipulate generative AI responses as well as rankings, list it as a violation.
• Mistake: mass-producing AI-written pages. Google's scaled content abuse policy gives "using generative AI tools or other similar tools to generate many pages without adding value for users" as an example of spam, and its quality guidance treats bulk AI-generated text that nobody has reviewed or edited as content made with little to no effort.
• Mistake: blocking every AI bot by default, or letting a firewall do it for you. Sites that opt out of OAI-SearchBot will not be shown in ChatGPT search answers, and Anthropic and Perplexity say blocking their search bots can reduce or prevent your visibility in their results. The mirror-image mistake is assuming that blocking GPTBot or Google-Extended removes you from ChatGPT search or AI Overviews; both companies document that those controls are separate.
• Mistake: structured data that does not match the visible page. Google's guideline is that all the content in your markup must also be visible on the page; markup that says more than the page does undermines trust.
• Mistake: hiding the answer. Key facts only in an image, a PDF or a collapsed tab, or buried under a long introduction, give an assistant nothing clean to lift. Microsoft lists walls of text, tabs, PDFs and image-only information as common mistakes that hurt AI search visibility. Google itself counts tabbed content as part of a page's main content and does not treat it as spam, so this is about what an assistant can lift, and nothing to do with penalties.
• Mistake: judging the whole thing on clicks. Pew's data shows fewer clicks when an answer appears, and Google's data says the clicks that remain are more engaged. Count only sessions and you will cut the pages that are quietly earning the citations.
• Myth: a special trick guarantees a citation. Google says you cannot mark a page as a featured snippet, its systems decide, and nothing in Google's documentation offers a way to request a citation in AI Overviews or AI Mode; Microsoft says there is no secret strategy for being selected. Anyone promising a guaranteed citation is promising something no engine offers.

How to measure SEO and GEO side by side

SEO has a mature scoreboard: rankings, impressions, clicks and the enquiries or sales that follow. GEO's official scoreboard is thin: Google reports AI impressions in Search Console, but no engine reports AI clicks separately, and the other assistants report nothing, so be clear about which numbers come from the engines and which come from your own tests.

What Google reports

Google counts traffic from AI Overviews and AI Mode in the Performance report under the Web search type, and since 31 August 2026 Search Console also has a separate Generative AI performance report showing how often your pages appeared in those features, by page, country and device. That report covers impressions only. In October 2026 Google moved inline links higher in AI Mode and AI Overviews, but Search Console still does not show which clicks come from AI results, so a change in clicks has to be read next to rankings and impressions before you credit or blame the AI features.

Google also recommends looking past clicks to the value of a visit, tracking conversions and time on site in a tool such as Google Analytics, because it sees clicks from results pages with AI Overviews as higher quality.

What you can measure yourself

• A fixed question set. Write down 20 to 30 questions buyers ask before they choose a supplier. Each month, ask them in Google, ChatGPT and Perplexity, and record whether an AI answer appears, which pages it cites, whether your brand is named and what it says about you. Over a few months that gives you citation counts and a share of voice against named competitors.
• AI referral traffic. Segment visits from referrers such as chatgpt.com and perplexity.ai in your analytics so enquiries from AI tools can be counted. In our audit of B2B companies, 42% could see AI traffic in analytics but could not separate it. Check your tagging before you react to a dip: a ChatGPT referral drop in GA4 between 8 and 16 October 2026 appears to have been mostly a tracking gap, with visits landing in Direct after ChatGPT's inline links lost their tracking tag.
• Crawler logs. Watch for OAI-SearchBot, PerplexityBot and Claude-SearchBot in your server logs, and for the user-triggered fetchers ChatGPT-User, Perplexity-User and Claude-User, which show a real person asked about your page. On mojodojo.io, 35% of 240,060 bot visits over 30 days came from AI crawlers, level with search engines.
• Answer accuracy. Note every time an assistant gets a fact about your business wrong, find the page it learned it from and fix the source. This is the LLMO part of the job, and the easiest to show a result on.

Report the two scoreboards together. Rankings and clicks tell you whether the SEO base is healthy; citations, mentions and AI referrals tell you whether the AI layer on top is working.

Frequently asked questions

Is GEO replacing SEO?

No. Google says the same foundational SEO practices apply to its AI features, and Microsoft says crawlability, metadata, internal links and backlinks remain essential. AI answers are built from crawlable, indexed pages, so SEO is the base that GEO sits on.

Is AEO the same as GEO?

They overlap almost completely. AEO emphasises being the direct answer to a question, which is also what a featured snippet does, while GEO emphasises generative engines that write a full response from several sources. The terms are used interchangeably in practice, including on our own service pages. Our guide to answer engine optimisation and our guide to generative engine optimisation cover each in depth.

What does LLMO add?

Mostly a reminder that a model can describe your business from what it has read even when it is not citing a live page, so the facts about you across the web need to agree. There is no separate technique behind it.

Can I keep my content out of AI training but stay in AI search?

Yes, with the three companies that document the split. OpenAI separates GPTBot (training) from OAI-SearchBot (search), Anthropic separates ClaudeBot from Claude-SearchBot, and Google says Google-Extended controls Gemini training and grounding without affecting inclusion in Google Search, while the separate Search generative AI setting in Search Console governs whether your site appears in AI Overviews and AI Mode. Remember that user-triggered fetchers may not follow robots.txt at all.

Can I make Google feature my page in an AI answer?

No. Google says you cannot mark a page as a featured snippet because its systems decide, and nothing in Google's documentation offers a way to request a citation in AI Overviews or AI Mode. What you can do is remove the reasons you would be left out.

How long does it take to see results?

No engine publishes a timeline. Google says recrawling after a change can take anywhere from several days to several months, and OpenAI says a robots.txt change takes about 24 hours to reach ChatGPT search. Measure monthly and expect gradual movement rather than a switch flipping.

How to get started: a practical order of work

For a small business the order matters more than the volume. Do these in sequence, because each step makes the next one measurable.

1. Fix the SEO base. Verify the site in Search Console, and check that the Search generative AI setting there has not been switched to exclude the site (it includes sites by default). Make sure the pages that matter return HTTP 200, are indexable and are not blocked for Googlebot in robots.txt or by your host or CDN. Google says meeting its technical requirements covers you for AI formats as well as classic results, and nothing AI-specific will compensate for a broken base.
2. Check AI crawler access. Read your robots.txt and your firewall or CDN rules for OAI-SearchBot, PerplexityBot and Claude-SearchBot, and allow them if you want to appear in those tools. Make a separate, deliberate decision about the training bots GPTBot, ClaudeBot and Google-Extended; blocking them does not remove you from search answers, and allowing them is a business choice rather than an SEO one.
3. Rewrite the pages that answer buyer questions. Pick the ten pages that should answer the questions people ask before they buy. Align the title, H1 and meta description. Put a plain two-sentence answer at the top of the page and under each heading, with headings phrased the way a buyer would ask. Use lists for steps and comparisons, and keep every key fact in HTML text instead of only in an image, a PDF or a tab.
4. Add evidence and authorship. Replace vague claims with specific numbers, name your sources and quote them briefly where a quote adds weight; those were the strongest methods in the GEO study. Put a real byline on the page with a link to an author profile. Google strongly encourages accurate authorship and treats fabricated author profiles as deception.
5. Add structured data that matches the page. Organisation or LocalBusiness, Service or Product, and author markup are the usual starting set, and every fact in the markup must be visible on the page. Microsoft says schema helps its systems interpret content with confidence, and Google says it makes pages eligible for certain search features. Neither says it gets you into an answer on its own.
6. Build presence beyond your site. Keep Business Profile, Merchant Center, directories and social profiles consistent on name, address, services and claims, and earn reviews and mentions on the sites that already get cited in your category, because the answer is often assembled from several of them before it reaches you.

The work spans technical, content and authority, which is why we deliver AI SEO for US businesses inside the same programme as classic SEO rather than as a separate product, and why the two scoreboards above are reported together.

For the detailed version of this list, with the AI-readiness audit worksheet and a chapter of quick wins for the next 30 days, our 14-page AEO Playbook is the next step. It is free, was updated in September 2026 and takes about 11 minutes to read.