SEO vs AEO vs GEO (and AISO, LLMO, AIO): The Plain Guide for 2026

If you've been running an established business for a few years and you're paying attention to how people find things online, you've probably encountered a few terms recently: SEO, AEO, GEO, and now AISO, LLMO, and AIO. Maybe all of them in the same week, from different people telling you different things.

The queries "GEO vs SEO" and "AEO vs GEO" are searched 2,900 and 1,300–2,400 times a month respectively—evidence that real confusion exists about what each discipline actually covers and whether they're genuinely different. Some describe exactly the same work. And for a founder of an established small business in 2026, the question isn't which one to choose; it's understanding what each one does, and which labels refer to different disciplines, so you can make a sensible decision about where to invest.

Here's the plain version.

SEO, AEO, GEO, and the rest—defined clearly

SEO (Search Engine Optimisation, also written Search Engine Optimization) is the practice of optimising a website to rank in traditional search engine results, primarily Google. The currency is position; page one, ideally top three. The signals are backlinks, keyword relevance, domain authority, and technical health. SEO has been the dominant discoverability discipline for two decades and remains relevant. But in 2026, it's no longer sufficient on its own.

AEO (Answer Engine Optimisation, also written Answer Engine Optimization) is the practice of optimising a website to be cited by AI-powered answer engines like ChatGPT, Perplexity, Claude, and Google's AI Overviews. The currency is citation, being the source an AI engine selects when synthesising a response. The signals are schema markup, entity confidence, answer-first content structure, and crawlability for AI crawlers. AEO is moving fast in 2026: search interest in the term has grown many-fold over the past year, but adoption hasn't kept up—only 22% of sites pass a clean schema audit, the baseline signal AI engines need to cite a source with confidence.

GEO (Generative Engine Optimisation, also written Generative Engine Optimization) is the practice of optimising content to appear in AI-generated outputs more broadly. Not just answer engines but generative AI tools, summarisers, and AI-assisted research tools. GEO overlaps significantly with AEO in its technical requirements. For most practical purposes, AEO and GEO describe the same underlying discipline and the terms are often used interchangeably. The query "AEO vs GEO" now attracts 1,300–2,400 searches per month, evidence that confusion between the two is real and growing.

AISO, LLMO, AIO, ASO, SXO: the acronym problem

The AI search space has a terminology proliferation problem. AISO (AI Search Optimisation, also written AI Search Optimization), LLMO (Large Language Model Optimisation), AIO (AI Optimisation), ASO, and SXO are all terms in active use in 2026. Job postings, agency pitches, and trade publications use them inconsistently, and one analysis of AI-search job postings found AISO listings alone outpacing SEO, AEO, GEO, and LLMO combined.

The honest read on all of them: they describe the same underlying technical discipline as AEO and GEO. The work includes schema markup, entity signals, AI crawler access, answer-first content structure, and does not change depending on which label is applied. Google's own position is that none of these are new disciplines: it's still SEO. What has changed is the set of surfaces that SEO now needs to target.

Chasing the latest acronym is a distraction. Understanding the infrastructure is the work.

The comparison

AISO, LLMO, and AIO require the same technical implementation as AEO/GEO—they are different labels for the same work.

Why AEO vs SEO isn't the right question

Every piece of content that positions AEO against SEO as competing choices is missing the point. They're not alternatives. They're layers.

A site that does SEO and ignores AEO is visible on Google and invisible to AI engines, which is an increasingly significant gap as AI-powered discovery grows. A site that does AEO on top of broken SEO fundamentals is optimised for citation on a foundation that doesn't rank. Neither is useful on its own.

The right frame: SEO is the floor. AEO is the layer above it. A well-built site in 2026 needs both, implemented in the right order. Whether you call the upper layer AEO, GEO, AI search optimization, or AISO is a labelling question, not a strategic one.

What established founders actually need

If you're running an established business that's been operating for some years, with real clients, real authority in your field, and a site that should be performing better than it is, the sequence is usually this:

Start with an infrastructure audit. Before adding content or pursuing backlinks, find out what's wrong with the technical foundation. Most established business sites have infrastructure gaps that no amount of SEO or AEO work will overcome: missing schema, AI crawlers accidentally blocked, JavaScript-dependent content invisible to the engines that matter, entity signals that are inconsistent or absent. The audit tells you where the real problems are.

Fix the technical foundation. This means schema markup, entity signals, crawler access, and content architecture—in that order. This is the AEO infrastructure layer, and it's the prerequisite for everything else. Without it, SEO improvements underperform, and AEO efforts produce nothing.

Build the content layer. With the technical foundation correct, content that's written answer-first, marked up with FAQPage schema, and structured for extraction will compound. It will rank on Google and get cited by AI engines, because the infrastructure underneath it allows both.

The goal isn't chasing acronyms—it's AI visibility optimization, and the infrastructure that makes it possible. Whether the emerging term is generative engine optimization, AISO, LLMO, or something coined next month, if the AEO infrastructure is correct, the underlying work is handled. The signals that make a site citable by ChatGPT are the same signals that make it citable by Perplexity, Claude, and any generative AI tool drawing from the web. Build the infrastructure once.

The specific AEO gap for established businesses

Founders of established businesses have a particular advantage that most content about SEO vs AEO fails to mention: they already have domain authority, real expertise, and a body of work. AI engines weigh these things. A site with genuine entity recognition, where the business has a clear, consistent identity across schema, content, and external references, gets cited more reliably than newer sites with technically better content.

The problem is that most established business sites have schema that's incomplete or broken—only 22% of sites pass a clean schema audit—so AI engines can't recognise and confidently cite them. The expertise is real. The infrastructure that signals it to AI engines is absent.

That's the gap AEO fixes. Not the content; the signalling layer underneath it. And it doesn't matter whether you call the service AEO consulting, GEO optimisation, or AI search optimization. The fix is the same.

What to do next

If you're not sure where your site currently sits: whether the technical infrastructure is correct, whether AI crawlers can access it, or whether your entity signals are consistent, the Infrastructure Audit is the right starting point. A half or full day that produces a clear picture of the gaps and a prioritised fix list, ready to act on.

If you know what's wrong and need the full blueprint, the Infrastructure Architecture produces a complete specification ready to hand to any developer, including me.

If you're ready to build it properly end-to-end, the Infrastructure Project takes it through to completion.

Aimee Q Devlin is a Systems and Infrastructure Architect based in San Miguel de Allende, Mexico. She works with founders and operators of established businesses who are ready to stop patching and build properly.

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