GEO vs AEO vs LLMO: the AI-search alphabet soup, explained
GEO, AEO, LLMO, AIO and GSO are, in practice, different names for the same goal: getting your brand named and cited when AI engines answer a question. The industry hasn't settled on one term, and the distinctions between them are mostly emphasis, not method. If you're choosing what to actually do, the label matters far less than the fundamentals — crawlability, entity clarity, answer-shaped content, and corroboration.
What each term means
- AEO — Answer Engine Optimization. Structuring content so it gets extracted and surfaced as a direct answer. Originally associated with voice search and featured snippets; now used broadly for AI answers.
- GEO — Generative Engine Optimization. Optimizing your content and digital presence so generative engines (ChatGPT, Perplexity, Gemini, Google AI Overviews, Claude) cite, mention or recommend you.
- LLMO — Large Language Model Optimization. Same goal, framed around the underlying models rather than the search interface.
- AIO / GSO / "AI SEO". Further variants — AI Optimization, Generative Search Optimization — that different practitioners prefer for the same work.
Do the differences actually matter?
Mostly no. Surveys of the field in 2026 found practitioners using these acronyms interchangeably, with few maintaining one consistent term across a year. The clearest distinction anyone draws is the old one between this whole family of terms and traditional SEO: SEO is about ranking pages for clicks; this family is about being selected as a source in a synthesized answer. Beyond that, arguing GEO-versus-AEO is mostly semantics.
Google's own position is blunter still: from its perspective, optimizing for its generative features is just optimizing for search — i.e. still SEO — and it cautions against treating "AEO/GEO hacks" as a separate discipline. That's a useful reminder not to chase tricks. But the buyer behaviour the terms describe — people getting answers from AI instead of clicking links — is very real, whatever you call the response to it.
What to focus on instead of the label
Whichever acronym your agency uses, the work that moves the needle is the same:
- Be crawlable by AI bots — the most common silent failure.
- Be a clear entity — consistent facts, structured data, and a
sameAstying your profiles together. - Write answer-shaped content that leads with the answer.
- Earn corroboration from the third-party sources models trust.
- Measure citations, not just rankings, and maintain them over time.
If you're new to the category, our primer on what AEO is and the breakdown of how AEO differs from SEO are the right next reads.
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Get your free visibility auditFrequently asked questions
Is there a difference between GEO and AEO?
In practice, very little. Both describe getting your brand cited in AI-generated answers. AEO leans on the "answer extraction" framing and GEO on the "generative engine" framing, but practitioners use them interchangeably and the underlying tactics are the same.
What does LLMO mean?
Large Language Model Optimization — the same goal as GEO/AEO, framed around the underlying language models rather than the search interface. It's another label for optimizing to be cited by AI.
Which term should I use?
Whichever your team and partners understand. The label has no effect on results; the fundamentals — crawlability, entity clarity, answer-shaped content, corroboration, and measurement — are what matter.
Does Google recognize AEO and GEO?
Google acknowledges the terms but treats optimizing for its generative features as part of normal SEO, and warns against treating "hacks" as a separate discipline. The buyer shift toward AI answers is real regardless of terminology.