SEO, AEO and GEO: What business leaders need to know about the new search landscape

For most of the last two decades, being visible in search meant something fairly stable and well understood. You published pages, search engines found them, and if your content was relevant and trusted enough, it appeared in a ranked list of blue links. Success was measured in positions, clicks, impressions and backlinks, and an entire discipline, search engine optimisation, grew up around influencing those signals. Those fundamentals have not disappeared. But the surface people actually see when they search has changed more in the past two years than in the previous ten, and that change is now significant enough that business leaders, not just marketing teams, need to understand what is happening.

The shift is simple to describe and profound in its consequences. Increasingly, search engines and AI assistants answer the question themselves. Rather than handing you ten links and leaving you to do the reading, Google’s AI Overviews and AI Mode, Microsoft Copilot, Perplexity, ChatGPT and others read across many sources on your behalf and compose a single written answer, usually with a handful of citations pointing back to the pages they drew from. Google has been candid that these AI features are built on the same underlying search systems it has always used, the same crawling and indexing, so there is no separate technical door to walk through. If your content is eligible for Google Search, it is eligible to be used in an AI answer. What has changed is not the plumbing but the destination: your content is now competing to be the answer, not merely to appear beneath it.

That reframing has brought two newer terms into everyday marketing conversations: AEO and GEO. Both are close relatives of SEO, and there is a fair amount of hype and loose definition around them. What follows sets out what each one actually means, how the underlying technology works, where they genuinely differ, and what a sensible organisation should do about all three.

What is SEO, and how search actually works

It helps to start with the foundation, because the newer disciplines only make sense once you understand what they are built on. Search engine optimisation is the practice of making a website discoverable and competitive in a search engine’s results. To appreciate what that involves, it is worth being precise about the three mechanical steps every search engine performs before it can show anything to anyone.

The first is crawling. Search engines run automated programs, often called crawlers, spiders or bots , that move from link to link across the web, requesting pages and reading their code much as a browser would. If a page cannot be reached, is deliberately blocked, or depends on scripts the crawler cannot execute, it may never be seen at all. The second step is indexing. Once a page has been crawled, the search engine analyses it, the words, the structure, the images, and the relationships between pages, and stores a processed version in an enormous database known as the index. Being indexed is the price of entry: a page that is not in the index cannot appear in results, in a featured snippet, or in an AI-generated answer. The third step is ranking. When someone searches, the engine consults its index and orders the eligible pages according to hundreds of signals: relevance to the query, the apparent quality and depth of the content, the authority of the site, page speed, mobile usability, and the trust conveyed by links from other reputable sites, among many others.

Good SEO works on all three stages at once. It keeps a site technically healthy so it can be crawled and indexed cleanly; it produces genuinely useful content that deserves to rank; and it earns the authority signals, chiefly credible backlinks, that persuade a search engine your pages can be trusted. Woven through all of this is the idea of search intent: the recognition that behind every query is a person trying to accomplish something, to learn, to compare, to buy, or simply to get somewhere, and that the best result is the one that satisfies that underlying goal rather than merely matching the words on the page.

None of this becomes less important in an AI-driven world. Quite the opposite. Every AI answer is assembled from content that has first been crawled, indexed and judged trustworthy. If a search engine cannot reach your page, cannot make sense of it, or does not trust it, that page will not feature in an ordinary ranking, and it certainly will not be selected as a source in a generated answer. SEO is the ground floor of the whole building; AEO and GEO are additions to the upper storeys, and they cannot stand without it.

What is AEO?

Answer engine optimisation, usually shortened to AEO, is the practice of shaping content so that it can be used directly as an answer rather than only as a link a user has to click and read. The name reflects a real change in behaviour: for a growing share of questions, the search engine now tries to resolve the query on the results page itself.

This is not entirely new. For years Google has surfaced featured snippets , the boxed answer that appears at the very top of some results, lifted from a single page , and “People also ask” panels that expand into short answers to related questions. AEO began as the craft of earning those placements. What AI Overviews and AI Mode have done is widen and deepen the same principle. Where a featured snippet quoted one passage from one page, an AI Overview reads across several pages and writes a short synthesis. Where the old panels answered a handful of adjacent questions, AI Mode can hold an entire conversation, carrying your context from one question to the next so that a follow-up builds on what came before.

The practical craft of AEO follows directly from how these systems consume content. They do not read a page the way a person reads an article, from top to bottom. They extract: they look for a clear, self-contained passage that answers a specific question, and they lift or paraphrase it. Content written to be extractable therefore has a genuine advantage. In practice that means answering the core question early and plainly rather than burying it beneath several hundred words of preamble; using descriptive, logical headings so a machine can locate the relevant section; defining terms in plain language; and, where it truly helps the reader, adding well-formed question-and-answer sections. A page targeting the question “What is AEO?” should offer a clear definition near the top and then expand into examples, nuance and practical guidance , not because a machine demands it, but because that is also the structure a busy human reader appreciates. It is worth stressing this point, because the same discipline that helps an answer engine extract a passage is the discipline that makes content genuinely readable. There is no real tension between writing for people and writing for answer engines; the second is largely a stricter version of the first.

What is GEO?

Generative engine optimisation, or GEO, is the newest of the three and the one most prone to confusion, so it is worth explaining carefully. A generative engine is any system that uses a large language model to compose an original answer to a question, such as Google’s AI Mode, Microsoft Copilot, Perplexity, ChatGPT and the rest. GEO is the practice of improving the likelihood that these systems reference, cite or draw on your content when they compose those answers. The term itself comes from academic research first published in 2023, and it has since travelled into everyday industry use as generative answers have become mainstream.

To understand GEO, you need a working picture of how a modern generative answer is actually produced, because it is quite different from ranking a list. Take Google’s AI Mode as the clearest example. When you ask it something, it does not simply match your words against an index. It performs what Google calls query fan-out: it breaks your question into several narrower sub-questions, runs searches for each of them, gathers passages from across many sources, and then passes that collected material to its language model, which reasons over the evidence and writes a single coherent answer. The technique underneath this is retrieval-augmented generation. The model is not answering from memory alone but from fresh material retrieved for the occasion and then “grounded” in those sources so the response can be attributed. This is why these systems can cite where their claims came from, and it is also why the queries the machine runs internally are not the words you typed. Microsoft has made this visible in Bing: what it calls 'grounding queries' are the AI’s own reformulations of a user’s question, the phrases it generates in order to go and find supporting evidence. Someone might ask Copilot how to make their marketing team more productive, and behind the scenes the system searches for tighter, more specific phrasings in order to retrieve the right material.

Once you see the mechanism, the goal of GEO becomes obvious. In classic SEO the prize is a ranking position. In GEO the prize is to be one of the sources the model chooses to ground its answer in , to be quoted, cited or paraphrased inside the response itself. That requires more than keywords. Generative systems tend to favour content that is well structured, factually precise, specific rather than vague, and supported by evidence they can lean on. Original data, genuine expertise, clearly identified authorship, transparent sourcing and information that is kept up to date all raise the odds of being treated as a reliable reference. A page thick with concrete facts, figures and clearly stated claims gives a model something to hold on to; a page of generic, hedged, interchangeable prose gives it nothing to cite.

Until recently, whether any of this was working was largely a matter of guesswork. That has begun to change. In February 2026 Microsoft launched an AI performance report inside Bing Webmaster Tools , the first time a major search provider offered site owners a direct view of how often their content is cited across Microsoft Copilot, Bing’s AI summaries and partner experiences, together with the grounding queries that triggered those citations. Google’s Search Console, by contrast, still exposes very little about AI Overview citations, which leaves an awkward asymmetry: the platform sending the most AI traffic tells you the least about it. That gap is, in itself, part of the strategic picture.

How SEO, AEO and GEO differ

The cleanest way to hold the three apart is by what each is ultimately trying to win. SEO is trying to win a position, to have a page rank well and attract organic visitors from the results page. AEO is trying to win the answer, to provide the clear, extractable passage that a search feature uses to respond directly. GEO is trying to win a citation to have a brand treated as a trusted source that a generative system draws on when it composes an answer, an answer that may never send a click at all.

Because the objectives differ, so do the measurements, and this is where many organisations are still poorly equipped. SEO has a mature set of metrics: rankings, impressions, clicks, sessions and conversions. AEO is measured more by presence than by traffic, whether you hold featured snippets, appear in answer boxes, and surface in AI summaries for the questions that matter to you. GEO demands metrics that barely existed a couple of years ago: how often you are cited in generative answers, how your share of those citations compares with competitors, how much referral traffic arrives from AI platforms, and, importantly, how valuable that traffic turns out to be. The uncomfortable truth is that some of the most important activity now happens where you cannot yet measure it cleanly, which places a real premium on the first-party reporting that is only beginning to appear.

For all that, these are overlapping disciplines rather than separate ones, and it would be a mistake to build three competing teams around them. Strong SEO underpins both of the others: a page that cannot be crawled, indexed or trusted is invisible to answer engines and generative systems alike. Clear, AEO-style answers make a page more useful to a human reader and easier for a machine to extract in the same stroke. And GEO leans heavily on exactly the credibility, clarity and authority that good SEO has always tried to build. In practice you are optimising one body of content for several audiences at once, not running three unrelated programmes.

Do AEO and GEO replace SEO?

It is tempting to read the arrival of AEO and GEO as a signal that SEO is on the way out. That would be a misreading. The newer disciplines extend SEO; they do not replace it. Traditional optimisation still supplies the technical foundation and the authority that every search and AI system depends upon. AEO adapts your content for direct-answer formats, and GEO prepares it for AI-driven discovery. Google’s own guidance is consistent on this point: the established fundamentals of good SEO continue to apply to its generative features, including AI Overviews and AI Mode. There is no secret alternative rulebook waiting to be discovered.

What has genuinely changed is that content now has to work harder and satisfy more audiences at once: a human reader, a search crawler, and an AI system that will summarise, compare and cite it. And there is a subtler shift underneath that, one worth naming plainly because it reframes how the work should be approached. Ranking well and being cited are beginning to come apart. A page can rank respectably in the traditional results and still be passed over when the AI composes its answer; conversely, a page that ranks only modestly for a keyword can be the source a generative system chooses to ground a related answer in. Analyses through 2025 and into 2026 have repeatedly found that the pages cited in AI answers are no longer simply the top-ranked pages; the overlap between ranking and citation has loosened considerably. The practical implication is that the unit you are optimising is quietly moving from the page to the passage and the claim. It is increasingly a specific, well-evidenced statement within your content, a clear definition, a concrete figure, or a defensible assertion , that gets retrieved and cited, rather than the page as a whole earning a position. Organisations that internalise this and write in clear, citable units will adapt more smoothly than those still thinking purely in terms of page rankings.

There is a commercial edge to this as well. The evidence emerging from AI-driven results points towards a concentration effect: when an AI answer does show its sources, those cited few tend to capture a disproportionate share of the attention and clicks that remain, while everyone who is merely ranked but not cited is squeezed out. The pool of clicks on many informational queries is shrinking, but within that smaller pool, being the cited source is worth more than it used to be. It is a winner-take-most dynamic, and it rewards the organisations that earn citations rather than settling for rankings alone.

How businesses can optimise for all three

The reassuring part of all this is that the actions which serve all three disciplines overlap heavily, and none of them is exotic. They begin with something unglamorous: producing content that is genuinely worth citing. Thin articles, vague claims and generic, mass-produced copy, including undifferentiated AI-written text, are precisely what generative systems have least reason to reference, because they add nothing that a hundred other pages do not already say. The organisations that win are the ones that write from real expertise, real experience or proprietary data and that are willing to be specific where their competitors are generic.

Structure carries more weight than it once did, because it directly affects whether a machine can locate and lift the relevant part of your content. Descriptive headings, reasonably short paragraphs, clear definitions and question-led sections all make a page easier to scan for a human and easier to parse for an AI. One caution is often missed here: structure should serve the reader, not be bolted on mechanically. Padding a page with forced FAQs and artificial headings in the hope of gaming an answer engine tends to backfire, because quality systems are increasingly alert to that kind of manipulation. The aim is genuine clarity, not the appearance of it.

Authority remains decisive, and if anything it matters more now than before. Content that names real experts, cites reliable sources, avoids claims it cannot support, and is reviewed and refreshed on a sensible cadence is exactly what both search rankings and generative citations reward. In fast-moving fields, letting content go stale is a quiet way of forfeiting trust , and because AI systems prize current information, out-of-date pages are increasingly passed over in favour of fresher ones.

Measurement, finally, has to grow up. Rankings and organic traffic still deserve attention, but they no longer capture the whole of your visibility. Sensible teams are beginning to watch how often they appear in AI summaries, how much referral traffic arrives from AI platforms and how well it converts, how frequently the brand is mentioned or cited in generated answers, and how that citation share moves over time. The tooling for this is young; Microsoft’s Bing report is an early and welcome example, and more will follow, but the direction is clear enough that leaders should be asking for these numbers now rather than waiting for them to become standard.

One further consideration belongs on the leadership agenda rather than the marketing checklist: control and governance. As AI answers have grown, so has the question of whether, and how, a business wants its content used in them. In the UK in particular, regulators have started to force the issue; a 2026 order from the Competition and Markets Authority required Google to give publishers a genuine way to opt out of having their content used in AI Overviews and AI Mode while remaining fully indexed in ordinary search results. For most businesses the sensible default is to stay visible on these fast-growing surfaces, but the fact that the choice now exists and is beginning to be governed by regulation means it deserves a deliberate decision rather than a default one.

The strategic takeaway

The through-line in all of this is that search visibility is no longer a single game played on a single board. SEO is not becoming obsolete; it is becoming broader. The organisations that will do well are not the ones chasing whichever three-letter acronym is currently in fashion, but the ones that quietly get the fundamentals right across the board: a technically sound website, content built on real expertise, clear and extractable answers, credible sourcing, and the willingness to measure visibility wherever their customers now look for information, whether that is a traditional results page, an AI Overview, or a conversational assistant.

For business leaders, the most useful way to think about it is less about tactics and more about a single question of readiness. Is your organisation’s knowledge clear enough, trustworthy enough and accessible enough to be chosen by a search engine, by an AI system and by the customer reading the answer as the source worth relying on? Almost everything technical follows from that. The businesses that can answer yes are the ones that will stay visible as the landscape keeps shifting and the ones best placed to turn that visibility into genuine commercial advantage.

About the author:

This article was developed in collaboration with Joaquin Morales, Search Director at New Horizon Marketing and Advertising

Article by David Reeder. LinkedIn Profile: https://www.linkedin.com/in/david-e-reeder/