What GEO is, and Why It is Not Just SEO for AI

GEO is a useful phrase with a messy job. People use it for at least three related things: being cited in generated answers, appearing in AI summaries and making web content easier for assistant‑style discovery systems to use. Those are not identical outcomes, even if they often get bundled together.

That is why I am cautious with the term. GEO can help a team talk about AI‑mediated discovery without pretending nothing has changed. Used lazily, it becomes a new label for old SEO work or, worse, a reason to sell vague AI visibility fixes that nobody can verify cleanly.

My view is simple: GEO is worth taking seriously, but only when it pushes us towards better evidence, better structure and clearer judgement. It should not become a parallel mythology where normal crawlability, rendered HTML, authorship, internal links and source quality somehow stop mattering.

GEO is Useful Shorthand, but It is Imprecise

The phrase generative engine optimisation normally points at content being found, interpreted and reused by systems that generate answers rather than simply listing pages. That might mean Google AI features, a Perplexity answer with sources, a ChatGPT browsing response, a Copilot summary or a future search interface that combines links and synthesis in a different way.

Those systems do not all work the same way. Some rely heavily on a search index. Some retrieve live sources. Some summarise a small set of documents. Some mix model memory, retrieval, product‑specific ranking systems and user context. A page that is useful to one product is not automatically visible in another.

So the term needs humility. GEO describes a pressure on web content, not a guaranteed distribution channel. The practical question is not "how do we make the model like this page?" It is "can a system discover this page, understand what job it does, extract a useful passage and connect that passage to enough evidence to trust it?"

GEO is Not a Separate Channel

Most GEO work still depends on ordinary web fundamentals. If the page cannot be crawled, is canonicalised somewhere odd, relies on JavaScript to reveal the only useful text or says the same thing as five nearby pages, there is no special AI layer that fixes that.

The same applies to trust. A generated answer may quote a passage, but it still needs a source worth quoting. Pages with clear authorship, visible experience, sensible internal links, accurate structured data and useful supporting material have a better chance of surviving that selection process than pages padded with generic definitions.

Google's own documentation on AI features in Search is a useful corrective here. It does not describe a secret markup layer for AI visibility. The same broad principles behind how Search works still matter: discovery, crawling, indexing, ranking systems and quality signals.

That does not make GEO meaningless. It means the useful part of GEO sits on top of solid SEO, not instead of it.

SEO, AEO, GEO and Retrieval Overlap

The vocabulary can get noisy, so I separate the jobs like this.

• SEO is the wider discipline: discovery, crawlability, indexation, ranking, technical health, information architecture, content quality and search visibility.
• AEO is answer‑shaped work: making direct answers easy to identify without turning every page into thin FAQ copy.
• GEO is about making content easier for AI‑mediated systems to retrieve, understand, summarise, cite and connect to supporting evidence.
• Retrieval is the mechanism: a system finding passages, pages or sources that might help answer the user's question.

Those lines overlap. A well‑structured answer helps AEO and GEO. A crawlable, indexable page helps SEO and retrieval. Clear internal links help search engines, users and AI‑mediated systems understand relationships between topics. GEO vs. SEO: Where They Overlap, and Where They Don't goes deeper on that boundary, and What AEO Is, and How It Fits with SEO and GEO covers the direct‑answer side.

The danger is treating the acronyms as separate departments. In real website work they meet in the rendered page. A heading, paragraph, canonical, link, schema node and author signal all contribute to whether a useful answer can be found and trusted.

What I Have Changed on My Own Site

The GEO work on johnkavanagh.co.uk has been deliberately unglamorous. I have not added hidden prompt instructions or magic metadata. I have focused on making the site easier to inspect, crawl and reason about.

That includes keeping a public URL inventory at `urllist.txt`, publishing `llms.txt` and `agents.txt`, maintaining sitemap and canonical hygiene, and making sure important service, resource, article and case‑study pages link to each other in ways that match the actual subject matter.

More recently, the service estate needed editorial work rather than another technical trick. Several pages were too close in shape and language. A generic service page might be acceptable to a human who already knows me, but it is weak evidence for search, retrieval and AI summaries. The fix was to make each page own a clearer job: what has gone wrong, what I would check first, what I would not assume too early and what kind of decision the buyer needs to make.

The same principle applies to resources. A risk register, checklist or comparison worksheet is more useful when it is connected to the service page, article and case‑study context around it. Otherwise it is just another isolated asset.

What GEO Work Actually Changes

Good GEO work often looks like stronger editing rather than a new technical feature. The opening needs to say the useful thing earlier. Headings need to describe the content below them. Passages need to carry enough context that they can be extracted without losing the point.

The page should also make its evidence visible. If a claim comes from first‑hand work, say what kind of work. If the page is based on a case study, link to it. If the advice depends on a caveat, include the caveat near the claim rather than hiding it at the end. If structured data is used, it should reflect what the reader can see on the page. schema.org helps describe visible entities and relationships, but schema that says more than the page proves is not a shortcut to trust.

Internal links matter more than people like to admit. They show how articles, services, resources and case studies relate to each other. They also help a reader move from a general explanation to something practical, such as a technical SEO service for JavaScript applications or a React and Next.js technical SEO audit checklist.

The same applies beyond the site itself. If the website says one thing, but LinkedIn, Google Business Profile, GitHub, directory profiles or partner pages describe the work differently, the public footprint becomes harder to reconcile. That does not mean every profile needs identical copy. It means the important facts should agree: who the person or business is, what they do, where they work, what they are credible for, and where the deeper evidence lives.

That is not a GEO trick. It is basic entity hygiene. A buyer should not have to work out whether someone is a technical SEO consultant, a Next.js platform specialist, a Contentful migration lead or a general web developer by comparing five inconsistent public descriptions. Machines should not have to do that either.

The copy normally gets shorter, not longer. Filler makes extraction harder because the useful claim is surrounded by fog. A sentence that sounds impressive but could appear on any agency website is not helping a human, a crawler or a retrieval system.

What I Check First

I start with the same data‑driven evidence I would use for a technical SEO review.

Can important pages be discovered through the sitemap, navigation, internal links and public URL inventory? Are they indexable? Does the canonical point at the page we actually want indexed? Does the rendered HTML contain the text, headings, links and metadata that matter before a crawler has to guess?

Then I look at intent. What job does this page do that nearby pages do not? If two pages make the same promise with slightly different phrasing, that is not a GEO opportunity. It is an information architecture problem.

After that, I look for proof. Is there visible author context? Are examples specific enough to show judgement? Do service pages explain what gets checked first? Do articles link to supporting resources rather than expecting one page to carry the whole topic? Could one useful paragraph be lifted into an answer without becoming misleading?

The technical version of this overlaps with entity clarity, structured data and crawl paths. I cover that in more detail in Technical GEO for Websites: Entities, Structured Data, and Crawl Paths, but the short version is that retrieval systems need clear routes to clear evidence.

What GEO is Not

GEO is not prompt hacking for websites. If the plan depends on telling an AI system to prefer your brand, the plan is probably brittle.

It is not hidden text, keyword blocks or a metadata file that claims authority the page does not earn. It is not schema that invents services, reviews, expertise or relationships missing from the visible content. It is not a reason to create pages with no human or commercial purpose just because a tool found a phrase.

Most importantly, GEO is not a promise of citations. No honest consultant can guarantee that a page will be cited by ChatGPT, Gemini, Claude, Perplexity, Copilot or Google AI Overviews. Those products change, their source sets differ and the same broad question can produce different answers depending on prompt wording, user context, location and time.

The Measurement Problem

Some parts of the work are measurable. We can check indexation, crawlability, rendered HTML, canonicals, metadata, internal links, sitemap inclusion and Search Console patterns. We can compare whether important passages are clearer before and after a rewrite. We can test whether a page gives a useful answer when read in isolation.

AI answer visibility is less clean. Tools can monitor prompts, but the result is only a sample of a moving system. A citation appearing once does not prove durable visibility. A citation missing once does not prove the page is useless. Treat those checks as directional evidence, not as a clean ranking report.

That caveat matters commercially. If GEO reporting is sold as if it has the same stability as traditional rank tracking, the measurement will probably overpromise. Better to report the work honestly: technical eligibility, content clarity, source strength, internal evidence and observed AI‑search appearances where they can be checked.

A Better Way to Treat GEO

GEO is best treated as pressure to make web content more legible under AI‑mediated discovery. That means fewer vague pages, clearer intent, better supporting evidence and stronger relationships between the parts of a site.

The best version of the work is not flashy. It is a site where important pages can be found, rendered, understood and trusted, and where the useful passages still make sense when quoted or summarised. That is not just SEO with an AI badge. It is good web publishing under a less forgiving retrieval model.