GEO vs SEO: what actually changes

"GEO vs SEO" reads like a rivalry. The evidence says otherwise. Google's own stated position, reported directly on Wikipedia's page for the term, is that optimising for generative AI search is optimising for the search experience, and is therefore still SEO. The genuine differences are real but narrower than most guides suggest, and they sit in what a page is being read by, not in a separate set of tactics.

Why this distinction matters now and did not two years ago

The scale is the actual reason to care. Google's own investor materials put AI Overviews at over 2.5 billion monthly users and AI Mode past 1 billion, with the Gemini app at 950 million monthly active users, as of its mid-2026 reporting. OpenAI has confirmed 900 million weekly active users for ChatGPT, disclosed alongside its funding announcement in February 2026. A meaningful share of the people who would previously have scanned a list of blue links are now reading a synthesised answer instead, in some cases without visiting any of the pages it drew on. A business whose entire visibility strategy assumes the click-through-to-a-ranked-page model is measuring less of its actual audience than it was two years ago, whether or not it has done anything differently.

What actually stays the same

The prerequisite is identical. Google states it plainly in its own AI-optimisation guide: the way Search finds and processes a page is the core of how its AI systems access data at all. A page has to be crawlable, indexed and eligible to appear in an ordinary result before any generative feature can draw on it. There is no separate AI front door, no alternative submission process, no way to be visible in an AI-generated answer while invisible to normal search.

What earns that visibility is also unchanged in substance. Google's guidance rewards the same things it has asked for since long before AI Overviews existed: original information rather than summarised repetition, genuine expertise, and content a reader can verify against a named author. None of this is new advice repackaged for AI. It is the same advice, now with a more literal reason to follow it, a system deciding what to cite runs something close to the same test a careful reader would.

What "optimising for GEO" cannot mean

Because the term is new and undefined, it gets used to sell things Google's own documentation directly rules out. Adding an llms.txt file. Rewriting existing pages into an "AI-friendly" chunked format. Adding schema markup specifically because a vendor called it a GEO requirement. Chasing citations from a fixed list of "high-authority domains per quarter", a figure that appears in at least one vendor's published framework with no traceable source behind it. None of these are optimising for anything measurable. They are activity, sold as strategy, in a market where the buyer has no easy way to check the claim against a primary source, because until now nobody has bothered to look.

What is genuinely different

The mechanism. Traditional search returns a ranked list of links a person scans and clicks through. A generative answer engine retrieves passages from several indexed pages and synthesises a response, citing sources as it goes. A page can be cited in an AI-generated answer without being the top-ranked traditional result for that query, because the system is assembling an answer from multiple sources rather than picking one winner.

What "visibility" measures. A ranking is a position. A citation is an appearance inside someone else's synthesised text, sometimes with a link, sometimes without a click ever happening. This is why "AI visibility" and organic ranking are related but not the same measurement, and why a page can be doing well on one without moving on the other.

The reporting. This is the part that has not caught up. Google's generative AI performance report inside Search Console, fully rolled out worldwide at the end of August 2026, shows impressions, how often a page was shown as a source in AI Overviews or AI Mode, broken down by page, country, device and date, but still has no click, query or conversion data. Bing's AI Performance report is built around citations rather than clicks too, and gained extra breakdowns (intent categories, topic grouping, citation share) in June 2026 without changing that underlying model. Neither platform currently answers "did this citation lead to a visit", which is the question a business actually wants answered.

What does not work, according to the platforms themselves

The gap between what vendors sell as GEO tactics and what Google's own documentation says is wide enough to matter. Google states directly that llms.txt files are ignored by Search, adopting one neither helps nor harms visibility. It states that no special schema.org markup is required for generative AI features, standard structured data still helps with ordinary rich results, but is not a citation hack. It names content chunking, artificial mentions and long-tail keyword stuffing as unnecessary, and warns that near-duplicate pages built to chase query variants can trigger its scaled-content spam policy rather than help. A guide that leads with any of these as the differentiator is repeating a claim the platform itself has already ruled out.

What got more important, not less

Two things that were already SEO fundamentals carry more weight now precisely because they are prerequisites for the newer mechanism, not because anything about them changed. Crawl access is the first: Google states directly that the way it finds and processes pages is the core of how its AI systems access data at all, so a page blocked from crawling, deliberately or by accident, is invisible to both the ranking algorithm and anything built on top of it. The second is page experience, Google's guide names "ensuring your site displays well across all devices, reducing latency" as current, active guidance, sitting alongside the content-quality checklist rather than replacing it. Neither of these is a new GEO requirement. They are the same technical foundation SEO has asked for, now serving two purposes instead of one.

The term itself is younger, and less settled, than the marketing implies

Generative Engine Optimization traces to a specific, checkable source: a paper posted to arXiv in November 2023 by researchers at IIT Delhi, Princeton and independent researchers, presented at the KDD 2024 conference. It is not an industry standard with an agreed definition. Wikipedia's summary of the term states there is no consensus distinguishing GEO from the older term AEO (answer engine optimization), or from AI optimization and LLM optimization, and most practitioners use these terms interchangeably. HubSpot's own comparison of the two terms reaches the same conclusion from a different angle: the practical difference is mostly terminological, and it describes GEO simply as making content visible in AI-generated responses, functionally the same job AEO already named. Anyone presenting a clean, confident line between GEO and SEO as settled fact is asserting more certainty than the platforms, or the research, currently support.

There is a reason that confident line gets drawn anyway. A search for "GEO agency UK" returns almost nothing except agencies' own service pages and other agencies' "best GEO agency" round-ups, with no independent journalism, government or consumer body anywhere in the results. A newer, less-defined term is easier to sell as a distinct discipline than a mature one with settled pricing expectations, and a market that has not agreed on a definition yet is a market where a confident-sounding vendor definition travels further than a cautious one.

Side by side

The practical difference that is worth acting on

Given all of that, the one change worth making deliberately is sourcing discipline. A generative system assembling an answer from several pages is more likely to pull from the one that states a fact plainly, attributes it to a checkable source, and is written by someone a reader could verify, because that is also what a careful human editor would prefer. Write for that standard and both traditional ranking and generative citation follow from the same work, rather than treating GEO as a second content programme layered on top of SEO.

Different platforms retrieve content differently, and the mechanics are covered in more depth in our guide to LLM SEO, but the principle holds across all of them: a system built to retrieve and cite reliable sources rewards the same qualities a human editor would, checkable claims, clear attribution, content that adds something rather than repeating the page above it in the search results.

That is the actual work behind MSD's SEO and GEO service: checking whether a site's existing content meets that bar, and fixing the technical and sourcing gaps that stop it, not selling a separate GEO tactics list alongside the SEO one. If you want an honest read on where your own content sits against this, talk to us.

Written by

Michael Szalaty Technical director

Delivery, development and infrastructure. Runs a staffing agency.