AI Search · Definitions
AEO, GEO, AIO and LLM SEO: definitions, differences and what actually matters
Four acronyms, heavy overlap, and a great deal of marketing built on the gaps between them. Here is what each one means, where they genuinely differ, and how much of the work is new.
01 · The short answer
What is the difference between AEO, GEO, AIO and LLM SEO?
AEO, GEO and LLM SEO describe substantially the same work: making content that AI engines can retrieve, parse and quote accurately. AIO is not a discipline at all — it is Google's AI Overviews surface.
Answer Engine Optimization (AEO) originated with featured snippets and voice assistants, where a passage was extracted more or less intact. Generative Engine Optimization (GEO) describes appearing inside an answer a model composes from several sources. LLM SEO is an informal umbrella for both. In day-to-day practice the three are used interchangeably, and the work you do for one is the work you do for all three.
The distinction that does carry weight is between all of them and conventional search engine optimisation — and even there, roughly 70% of the work is technical SEO you should already be doing.
- AEO
- Answer Engine Optimization — extractable direct answers
- GEO
- Generative Engine Optimization — synthesised AI answers
- AIO
- AI Overviews — a Google surface, not a discipline
- LLM SEO
- Informal umbrella term, no settled definition
02 · Definitions
What does each term actually mean?
Each definition below is written to stand on its own, because that is how an AI engine will read it.
Answer Engine Optimization (AEO)
AEOAnswer Engine Optimization is the practice of structuring content so it can be extracted and presented as a direct answer.
AEO predates generative AI. It grew out of optimising for Google featured snippets and voice assistants, where a single passage was lifted from a page and read aloud or displayed in a box. The underlying discipline — write the answer plainly, put it near the top, structure it so a machine can find its boundaries — transferred almost unchanged to AI assistants.
Example: A page headed “How long does a website audit take?” that answers in the first two sentences, before any preamble about the company.
Generative Engine Optimization (GEO)
GEOGenerative Engine Optimization is the practice of improving how often and how accurately a brand appears inside answers synthesised by generative AI engines.
The term entered wider use through academic work on optimising content for generative engines, and was adopted quickly by agencies. Where AEO assumes extraction of a passage, GEO assumes synthesis — the model reads several sources and writes something new, citing some of them.
Example: Asking Perplexity “best recruitment agency in Bangalore for AI roles” and being named in the composed answer, with your page cited beneath it.
AI Overviews (AIO)
Surface, not a disciplineAI Overviews is Google's AI-generated summary block, shown above conventional search results.
AIO is a place your content can appear, in the same way featured snippets were a place. It is not a method. Treating it as a discipline leads teams to optimise for one destination owned by one company, rather than for the mechanics that apply across ChatGPT, Perplexity, Claude and everything that follows them.
Watch for: Vendors selling “AIO optimisation” as something separate from GEO. It is the same work, aimed at one surface.
LLM SEO
InformalLLM SEO is an informal umbrella term for optimising content so large language models retrieve, understand and cite it.
It has no settled technical definition and no body of work behind it. Used loosely, and interchangeably with AEO and GEO. Also appears as “AI SEO”, “AI search optimisation” and “chatbot SEO”.
Practical note: Useful as a search term because buyers type it. Not useful as a category, because it does not describe a distinct method.
03 · Side by side
How do AEO, GEO, AIO and LLM SEO compare?
| Dimension | AEO | GEO | AIO | LLM SEO |
|---|---|---|---|---|
| Full name | Answer Engine Optimization | Generative Engine Optimization | AI Overviews | — (informal) |
| What it targets | Extractable direct answers | Synthesised AI answers | One Google surface | All AI surfaces, loosely |
| Origin | Featured snippets, voice search | Academic work, then agencies | Google product name | Agency coinage |
| Primary metric | Citation rate | Share of voice in answers | Presence in the AIO block | Varies by who is selling it |
| Is it a discipline? | Yes | Yes — ≈ AEO | No | Loosely |
| Overlap with SEO | High | High | Very high | High |
04 · The part nobody sells
Is any of this actually different from SEO?
About 30% of it. Mapping the work honestly is more useful than defending a category boundary.
Same as technical SEO
- Crawlability and indexation
- Site architecture and internal linking
- Schema markup and structured data
- Topical depth and content freshness
- Canonical handling and duplicate control
- Page performance and rendering
If a page cannot be crawled or indexed, it cannot be retrieved. If it cannot be retrieved, it cannot be cited. This is the gate everything else sits behind.
Genuinely new
- Answer-shaped passage formatting
- Entity and fact consistency across the whole web
- Accuracy monitoring — what AI says about you, and whether it is true
- Share of voice inside AI answers
- Agent-readiness files and content negotiation
Only the two bolded items are impossible under a conventional SEO programme. They are also the two that most marketers have never measured.
05 · Mechanism
How does an AI engine decide what to cite?
Two gates, not one. Most content advice addresses only the second, and most SEO advice only the first.
Retrieval — can it find you?
The engine runs a search, often decomposing your question into several queries you never see, and pulls a candidate set of passages. If your page is not in that set, nothing downstream matters.
Controlled by: conventional search visibility. Analyses consistently find a high proportion of AI-cited sources also rank in Google's top 10.
Selection — does it use you?
From that candidate set, the model picks which passages to use and attribute. Retrieved is not the same as cited — and the gap is large.
Controlled by: whether your passage answers the question cleanly and can stand alone. This is where answer-shaped formatting earns its keep.
of pages ChatGPT retrieves actually appear in the final answer
Search Engine Land analysis, March 2026
of ChatGPT citations come from the first third of a page's content
Citation analysis, February 2026
of all AI citation share is captured by just 15 domains
AI Citation Source Index, 680M+ citations, 2026
Why the concentration figure should change your plan
If fifteen domains take roughly two-thirds of all citations, then for many queries the fastest route into an AI answer is not your own page at all — it is being referenced by a source the engine already trusts. That makes earned media, community presence and third-party listings part of the AEO programme, not a separate marketing line item.
06 · Engine behaviour
Do all AI engines cite the same sources?
No — and the divergence is large enough that “optimise for AI” is not a coherent instruction.
Ask ChatGPT, Gemini, Perplexity and Claude the same question and you get answers drawn from substantially different source pools. June 2026 engine-level data shows Reddit accounting for roughly 29% of ChatGPT's citations and close to zero of Claude's, where brand-owned sites take around 64%. YouTube leads on Perplexity and AI Overviews and barely registers on Claude.
The practical consequence: if your buyers use Claude — common among technical and developer audiences — investment in Reddit and video is close to wasted, and your own domain is the lever. If they use ChatGPT, the reverse is closer to true.
Establish which engines your buyers actually use before allocating budget. Ask them in discovery calls. It is a two-minute question that redirects a quarter of spend.
engine reddit brand sites chatgpt 29.4% — gemini 27.5% — ai overview 19.6% — perplexity 16.6% — claude ~0% 64% → one content strategy cannot serve engines this different
07 · Action
What should a marketer actually do about this?
Six things, in order. The first two are not glamorous and they matter most.
Check you are not blocking citation agents
Training crawlers (GPTBot, Google-Extended, CCBot) and citation agents (ChatGPT-User, PerplexityBot, Claude-User) are different things. Blocking the second group removes you from AI answers entirely. Plenty of sites have done this by accident while trying to block the first.
Confirm your content survives without JavaScript
If content disappears when JavaScript is disabled, most AI crawlers never see it. This is a gate failure: everything downstream is compromised. Testable in two minutes with curl.
Put the answer first
Two to three sentences that fully answer the heading, before any context or preamble. Each section should be readable on its own, because retrieval pulls passages, not pages.
Fix schema drift before adding more schema
Structured data that contradicts the visible page erodes trust. Pricing in JSON-LD that no longer matches your pricing page is worse than no markup at all. Accuracy before density.
Audit what AI currently says about you
Ask the engines the questions your buyers ask and read the answers. Discontinued services still being recommended, competitors named in your place, wrong pricing — all common, all invisible until you look.
Work on sources beyond your own domain
Given the citation concentration, being referenced by sources the engine already trusts often does more than anything on your own site. Earned media, directories, review sites, community presence.
08 · Measurement
How do you measure AEO and GEO performance?
Six metrics, tracked together. Any one of them read alone will mislead you.
| Metric | What it measures | Why it matters |
|---|---|---|
| Mention rate | How often the brand is named at all | Baseline visibility |
| Citation rate | How often one of your URLs is attributed | Stronger signal than a mention |
| Share of voice | Your mentions against all vendors named | Competitive position |
| Accuracy rate | How often the description is correct | The reputational metric, and the least tracked |
| Source mix | Own-domain vs third-party citations | Tells you where to spend |
| Retrieval mode | Did the engine search, or answer from memory? | Determines whether on-site work can move it at all |
The measurement error that invalidates most AI visibility reports
AI answers are non-deterministic. The same prompt, the same engine, the same day returns different answers. A tool reporting a single observation as a fact is reporting a coin toss. Run each prompt several times per period, report rates rather than binary present or absent, pin model versions, and treat any movement smaller than the variance as no detected change.
09 · Common questions
AEO, GEO and LLM SEO — answered
Is AEO the same as GEO?
In practice, yes. Most practitioners use Answer Engine Optimization and Generative Engine Optimization interchangeably. The historical distinction is that AEO grew out of featured snippets and voice search, where a passage was lifted more or less intact, while GEO describes appearing inside an answer the model composes from several sources. The work you actually do for each is close to identical, so the distinction rarely changes a decision.
Is AIO a discipline or a surface?
AIO stands for AI Overviews, which is Google's AI-generated summary block. It is a surface within Google Search, in the same way that featured snippets were a surface. It is not a separate discipline, and treating it as one leads teams to optimise for one destination rather than for the underlying mechanics that apply across every AI engine.
How much of AEO is just SEO?
Roughly 70 percent. Crawlability, indexation, site structure, internal linking, schema markup, topical depth and content freshness are all conventional technical SEO and all of them affect whether an AI engine can retrieve your page. The genuinely new work is answer-shaped passage formatting, entity and fact consistency across the web, accuracy monitoring of what AI says about your brand, and share of voice measurement inside AI answers.
Does schema markup get you cited by AI?
Not on its own. An Ahrefs study of 1,885 pages found that adding schema markup alone barely moved AI citations. Schema remains useful for entity disambiguation and for conventional rich results, but density without accuracy achieves little. Schema accuracy matters more than schema presence: structured data that contradicts the visible page erodes engine trust and is a defect most audits never check for.
Which AI engines should a marketer optimise for?
It depends on where your buyers are, because the engines cite very different sources. June 2026 data shows Reddit accounting for roughly 29 percent of ChatGPT's citations and close to zero of Claude's, where brand-owned sites take about 64 percent. A single content strategy cannot serve both. Establish which engines your buyers actually use before allocating budget across community content, video and your own domain.
Can an agency guarantee a citation in ChatGPT?
No. AI answers vary by prompt, by engine, by model version and by day, and none of the major engines publishes a ranking mechanism or accepts submissions. Any guarantee of placement or citation frequency is a guess. What can be committed to is a measured baseline, a repeatable method, transparent reporting and multiple sampled runs per prompt rather than single observations reported as facts.
How do you measure AEO and GEO performance?
Track six things together: mention rate, citation rate, share of voice against named competitors, accuracy rate, source mix between your own domain and third-party sources, and retrieval mode. Each prompt should be run several times per period and reported as a rate with a confidence range, never as a single yes or no, because AI answers are non-deterministic and a single observation is not a measurement.
Author
Code4X Research Team
AI Visibility & Search Intelligence · Code4X
The Code4X Research Team audits web infrastructure, crawler behavior, and answer engine citation patterns across modern web applications.
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Sources
Every figure on this page, with its origin
| Claim | Source | Date |
|---|---|---|
| ~15% of retrieved pages appear in ChatGPT's final answer | Search Engine Land citation analysis | Mar 2026 |
| ~44% of ChatGPT citations from first third of content | Citation analysis | Feb 2026 |
| Top 15 domains ≈ 68% of AI citation share | AI Citation Source Index (680M+ citations) | 2026 |
| Reddit 29.4% of ChatGPT citations; ~0% on Claude | Engine-level citation snapshots | Jun 2026 |
| Schema alone barely moved AI citations (1,885 pages) | Ahrefs | 2026 |
| Google dropped FAQ rich results | Google Search Central documentation | 7 May 2026 |
Published research on AI citation behaviour disagrees substantially between studies. Figures above are reported as found, with methodology and date, and should be treated as directional rather than precise.