Ask ChatGPT to recommend an accountancy firm in Leeds and you will not receive ten blue links. You get a short paragraph naming three or four firms, with numbered citations sitting beside the text. Ask Google the same question and an AI Overview may appear above the organic results, summarising the answer and linking to a handful of pages.
In both cases, something has changed about how visibility works. You are either one of the named sources or you are absent from the answer entirely.
Generative engine optimization, usually shortened to GEO, is the work of improving the odds that your business is one of those sources. It sits alongside search engine optimisation rather than replacing it, and it is far less mysterious than much of the advice circulating online suggests.
What Generative Engine Optimization Actually Means
GEO is the practice of making your content easier for AI systems to retrieve, understand, trust and cite when they generate answers. The term was popularised by an academic paper published in 2023 that examined how content characteristics affected inclusion in generative search responses, and it has since been adopted, somewhat loosely, by the marketing industry.
You will also see the term AEO, or answer engine optimisation. In practice the two describe the same activity. Google’s own position, published in its official guidance for website owners, is that optimising for generative AI features in Search is simply optimising for Search, and therefore still SEO. That is a useful anchor. Anyone selling GEO as an entirely separate discipline with its own secret mechanics is overstating the case.
What GEO does usefully describe is a shift in the unit of competition. Traditional SEO competes for a position on a results page. GEO competes for inclusion in a synthesised answer where only a few sources are named, and where the reader may never scroll further.
Why GEO Emerged
Three developments pushed this into commercial relevance.
First, AI answers moved from experiment to default. Google’s AI Overviews and AI Mode now appear across a large share of queries, and ChatGPT, Perplexity, Copilot and Gemini have all become places where people begin research rather than places they visit for novelty.
Second, the behaviour around those answers is different. Someone reading a synthesised answer that already resolves their question has less reason to click through. Publishers have reported reduced click-through rates on queries where AI answers appear, though the effect varies enormously by query type and industry. Informational queries are affected far more than transactional ones.
Third, the traditional measurement layer stopped telling the whole story. A page can be referenced repeatedly inside AI answers while its organic click data looks flat. Businesses noticed the gap and wanted a way to manage it.
How GEO Differs From Traditional SEO
The overlap is substantial. Both depend on being crawlable, indexable and genuinely useful. The differences are worth stating precisely, and we cover them in more depth in our comparison of GEO and SEO.
Traditional SEO optimises a page to rank for a query. GEO optimises content so that specific passages within it can be extracted, verified and attributed. A page can rank tenth and still be quoted, or rank second and be ignored, because the model is selecting claims rather than pages.
Traditional SEO is measured in positions, clicks and impressions. GEO is measured in mentions, citations and share of answers, which is a messier and less mature discipline.
Traditional SEO is largely on-site work supported by links. GEO leans more heavily on what exists about you elsewhere: review platforms, industry directories, forum discussions, trade press and comparison sites. AI systems frequently draw on third-party sources when forming an opinion about a brand.
How AI Search Engines Retrieve and Synthesise Information
Understanding the pipeline removes most of the mystique. The technical detail is covered fully in our explanation of how AI citations work, but the essentials matter here.
Retrieval Comes First
Most AI search features do not answer from memory. They retrieve current web documents and generate an answer grounded in what they find. Google describes this as retrieval-augmented generation, or grounding, and states plainly that it relies on core Search ranking systems to retrieve pages from the Search index. In other words, if you are not indexed and eligible to appear with a snippet in Google Search, you are not eligible for its AI features either.
ChatGPT operates differently. It draws on external search providers alongside its own crawler, OAI-SearchBot. OpenAI’s publisher guidance is direct about the prerequisite: any public website can appear in ChatGPT search, but you must not be blocking OAI-SearchBot in your robots.txt file. That crawler is separate from GPTBot, which relates to model training, so a business can allow search visibility while declining training use.
Perplexity runs real-time searches and returns numbered footnotes linking to sources. Each platform has its own retrieval layer, and this is why the same question produces different citations on different services.
Queries Get Expanded
Google documents a technique called query fan-out, where the system issues several concurrent related searches rather than one. Its own example: a query about fixing a weed-filled lawn might fan out into searches about herbicides, chemical-free weed removal and weed prevention.
The practical consequence is that you are rarely competing for one phrase. You are competing across a cluster of sub-questions, some of which you may never have considered as keywords.
Then the Answer Is Assembled
The model reads the retrieved material, selects the passages that best support an answer, writes the response and attaches links to the sources that informed it. Citation is a byproduct of the material being used, which is why the goal is not to be liked by an AI but to be the clearest available evidence for a specific claim.
Why Businesses Want to Appear in AI Answers
The commercial argument is about consideration sets. When an AI answer names three suppliers, it has quietly performed the shortlisting that a buyer used to do across several tabs. Being named is qualitatively different from ranking seventh.
There is also traffic, though it needs measuring rather than assuming. OpenAI’s publisher documentation notes that ChatGPT referrals can be tracked in analytics platforms, and referrals typically arrive with an identifiable source parameter. Many businesses find these visitors small in number but unusually well qualified, since they have already read a synthesised explanation before clicking.
The third reason is defensive. If your competitors are being cited on the questions that matter in your category and you are not, the answer being formed about your market is one you have no part in.
What Appears to Influence AI Visibility
This is where careful language matters. No technique guarantees a citation, and any tool or agency claiming otherwise is guessing. It helps to separate what is documented from what is widely observed.
Documented Requirements
Google states that a page must be indexed and eligible to appear with a snippet to be eligible for generative AI features. OpenAI states that OAI-SearchBot must not be blocked. These are prerequisites, not advantages. They are also the first thing to check, because a surprising number of sites fail them without knowing.
Google also emphasises unique, non-commodity content, using a memorable contrast: a generic list of homebuying tips is commodity content that anyone could have written, whereas a specific account of a decision you made and what it cost is not. Its guidance says this will likely influence long-term presence in generative AI search more than anything else in the document.
Content Structure and Factual Clarity
Content that answers a question directly, in plain language, near the point where the question is raised, is easier to extract and attribute than content that circles the subject for four paragraphs first.
Be careful here. Google explicitly says there is no requirement to break content into tiny pieces for AI to understand it, and no ideal page length. Clarity helps because it helps readers. Mechanical chunking for its own sake does not.
Factual specificity does appear to matter. A sentence such as “our onboarding usually takes four to six weeks for a fifty-person team” is a citable claim. “We onboard clients quickly” is not, because there is nothing in it a model can attribute.
Authority, Entities and Third-Party Mentions
AI systems form a picture of your organisation from many sources, not only your website. Consistent business details, clear author identification, and a presence on the review sites, directories and communities where your category is discussed all contribute to that picture.
One warning worth taking seriously. Google’s guidance names the pursuit of inauthentic mentions as a tactic to ignore, noting that its ranking systems focus on quality content while other systems block spam. Buying mentions is not a strategy. Earning them is.
Freshness and Accuracy
Where a topic changes, currency matters. Where it does not, changing the date without changing the substance is not an update. Pages that carry outdated pricing, superseded regulations or dead references are risky material for a system that is trying to produce a reliable answer.
Building a GEO Content Strategy
A workable approach has five parts.
Build a prompt inventory. List the questions a buyer would actually ask an AI assistant in your category, phrased conversationally rather than as keywords. “Which brand agencies in Manchester work with challenger drinks brands” is a prompt. “brand agency manchester” is a keyword. You need both, but only one of them tells you what an AI answer will be assembled from.
Cover the sub-questions. Because of query fan-out, depth on the surrounding questions supports visibility on the main one. This is the argument for topic clusters rather than isolated posts, and it is why this article sits within a connected set rather than standing alone.
Publish something only you can publish. Original data, client outcomes with real numbers, methodology you have tested, first-hand accounts of what failed. Our article on how interior design businesses get cited by AI search engines works through this in a single sector, and the pattern holds across most service industries.
Fix your off-site footprint. Audit how your business is described on Companies House, LinkedIn, Google Business Profile, Trustpilot, industry directories and any trade publications that cover you. Inconsistencies here weaken the entity picture.
Get the fundamentals right. Crawlable, fast, indexed, no accidental blocking of AI search crawlers, clean internal linking. Unglamorous and non-negotiable.
How to Optimise Existing Content
Most businesses have more to gain from improving published pages than from adding new ones.
Start with pages that already rank on the first page but attract few clicks, since these often sit underneath an AI answer. Read each one and ask whether the central question is answered clearly within the first two hundred words. If it is not, restructure so it is.
Then look for vague claims that could be made specific. Replace ranges you have never verified with figures you can stand behind. Add the date of your most recent substantive review where currency matters. Name the author and explain, briefly, why they are qualified to write it.
Finally, remove content that exists only to occupy a keyword. Thin pages dilute the picture of what your site is actually authoritative about.
How to Measure AI Search Visibility
Measurement is the least developed part of GEO, and honesty about that is more useful than a dashboard full of invented certainty. Our guide to measuring AI search visibility covers this properly, but the current landscape looks roughly like this.
Google provides a generative AI performance report in Search Console, which shows how content is performing in its generative AI features. Bing Webmaster Tools added an AI performance report covering citations in Microsoft Copilot and Bing’s AI summaries, reporting total citations and the grounding queries used to retrieve cited content. OpenAI does not offer equivalent reporting for most publishers, so ChatGPT visibility is usually assessed through referral traffic and manual or tool-assisted prompt testing.
Google also advises caution about third-party tools that claim access to internal ranking or AI systems, since none have it. Use the tools if they help your workflow, but treat their numbers as directional estimates rather than facts.
Common GEO Mistakes
- Treating llms.txt as a strategy. Google states it does not use these files, and that creating one will neither help nor harm visibility in Google Search. Other systems may use them, so it is not harmful, but it is not the work.
- Chunking content mechanically. Explicitly named as unnecessary in Google’s guidance.
- Rewriting everything in a stilted question-and-answer format. AI systems understand synonyms and meaning. Writing badly for a machine tends to produce content that people bounce off.
- Publishing volume. A high quantity of pages does not make a site more relevant, and creating pages for every query variation risks falling foul of scaled content abuse policies.
- Ignoring off-site presence. Many businesses obsess over their own pages while their category is being discussed on Reddit, Trustpilot and trade forums without them.
- Assuming one platform behaves like another. Optimising for Google’s index does nothing for ChatGPT if you are blocking OAI-SearchBot.
Where GEO Goes Next
Two developments are worth watching. The first is agentic browsing, where AI agents visit sites to complete tasks such as comparing specifications or making bookings. Google now points site owners towards agent-friendly practices and emerging protocols for commerce interactions, which suggests that how easily a machine can navigate your site will matter more over time.
The second is measurement. Platform-level reporting has improved noticeably in the past year and will keep improving. Businesses that build a measurement habit now will be in a better position than those waiting for a complete solution.
What seems unlikely to change is the underlying requirement. Systems that generate answers need reliable material to generate them from. Being that material remains the job.
The Practical Takeaway
Generative engine optimization is best understood as search visibility extended into a new interface, not as a replacement for the work you already do. The prerequisites are technical and dull. The differentiator is content that contains something specific, verifiable and unavailable elsewhere. The tactics being marketed most aggressively are mostly the ones the platforms have said they do not use.
If you do only one thing after reading this, audit whether your most important pages are indexed, crawlable by AI search bots, and capable of answering their central question in a single clear paragraph. That covers more ground than any file you could add to your root directory.
Frequently Asked Questions
Is GEO different from SEO, or just a rebrand?
Google’s position is that for its own generative features, optimising for AI search is still SEO. The distinction has more practical value across other platforms, where retrieval works differently and where off-site presence carries more weight. Treat GEO as an extension of search visibility rather than a separate budget line.
Do I need to add an llms.txt file to my website?
Not for Google, which states it ignores these files. Some other services use them, so maintaining one is harmless, but it will not produce visibility on its own and should not be prioritised over content and technical fundamentals.
How long does it take to see results from GEO work?
There is no reliable published benchmark, and anyone quoting a precise timeframe is estimating. Realistically it depends on how often the relevant pages are recrawled, how competitive the topic is, and whether the change was substantive. Plan in quarters rather than weeks.
Can a small business compete with large publishers in AI answers?
On broad questions, rarely. On specific ones, often. A ten-person firm with genuine first-hand detail about a niche process is frequently better source material than a large site restating common knowledge, and Google’s guidance points in exactly that direction.
Should I block AI crawlers to protect my content?
That is a strategic choice with a real trade-off. Blocking OpenAI’s search crawler removes you from ChatGPT search results. Blocking training crawlers is a separate decision controlled independently. Decide deliberately rather than by accident, and check what your robots.txt currently says.
Published by BrandingX UK.
