If you have spent any time in the AI search market in 2026, you have probably heard three different acronyms used to describe what is mostly the same thing: SEO, AEO (Answer Engine Optimization), and GEO (Generative Engine Optimization). Vendors lean hard on whichever label sells best to a given audience. Buyers end up confused, and confused buyers either over-pay or under-invest.

This piece is the working distinction we use at Citable. The short version: SEO and GEO are two real disciplines with overlapping technical foundations and divergent objectives. AEO is mostly a label, not a separate discipline. The longer version is below.

SEO — Search Engine Optimization

What it optimizes for: ranking in a list of links on a search engine results page (SERP).

Primary surface: Google Search, Bing.

Measurement metric: keyword ranking position, organic traffic volume, click-through rate from SERP.

Mature discipline. SEO has been a defined practice for ~25 years. The signals are well-understood: technical accessibility, on-page content quality, backlink authority, Core Web Vitals, schema markup, intent matching. There is enormous variation in execution quality — but the discipline itself is mature.

What changed recently: the SERP shrank. AI Overviews now appear in 25.11 percent of searches, occupying the space that would otherwise have been the first organic result. Even when classic blue links are present, fewer users click them — zero-click search rates have climbed steadily for 5 years.

This is what created the demand for the next two acronyms.

GEO — Generative Engine Optimization

What it optimizes for: being cited inside a synthesized AI answer.

Primary surfaces: ChatGPT, Perplexity, Gemini, Claude, Google AI Overviews.

Measurement metric: Share of Answer (the percentage of relevant prompts in which your brand is cited), citation frequency by surface, competitor citation map.

Real, distinct discipline. GEO inherits SEO’s technical primitives — fast pages, clean schema, semantic HTML, authoritative content — but adds layers SEO ignores: content extractability, prompt-aligned H2 structures, AI crawler access (GPTBot, PerplexityBot, ClaudeBot), entity disambiguation across multiple knowledge sources, and Share of Answer measurement across multiple AI surfaces.

A brand can rank in the top 3 organic Google results for a high-intent keyword and have 0% Share of Answer on the equivalent prompt in ChatGPT or Perplexity. The two systems pick what to surface using different mechanics. Optimizing for one does not automatically optimize for the other.

We covered the full GEO methodology in What is Generative Engine Optimization? — this is the brief version.

AEO — Answer Engine Optimization

What it optimizes for: being the structured answer surfaced in featured snippets, “People Also Ask” boxes, voice search responses, and AI Overview cards.

Primary surfaces: Google AI Overviews, Featured Snippets, Google Assistant, Alexa, Siri.

Measurement metric: appearance frequency in answer formats, position-zero capture rate.

Mostly a label. AEO predates GEO as a marketing term — it gained traction around 2018–2020 as voice search and Featured Snippets became more prominent. The signals AEO targets — FAQPage schema, question-format H2s, direct-answer paragraph structure, HowTo schema — are a proper subset of what modern GEO targets. Optimizing for AEO is optimizing for a specific subset of GEO’s outputs.

The honest framing: AEO was a useful label when answer engines (voice assistants, Featured Snippets) were the primary AI-adjacent surface. Now that synthesized chatbot answers are the primary surface, AEO has been absorbed into GEO. Most agencies that branded themselves “AEO specialists” in 2022 are now selling the same methodology under the GEO label in 2026.

If a vendor is selling you AEO as something separate from GEO and quoting different prices for each, you are probably being sold the same work twice. Ask them to define the methodological difference. If they cannot, they do not have one.

Which do you actually need?

The actual question worth asking is “where do my buyers do their research, and where am I currently absent?”

If your buyers consistently arrive via Google Search and your traffic-to-conversion ratio is healthy, SEO is your discipline. Keep investing. Watch AI Overview encroachment on your top keywords, but the core work is the same as it has been.

If your buyers are increasingly arriving via ChatGPT/Perplexity/Gemini referrals (or arriving with brand recognition you cannot trace to a search query), GEO is your discipline. The starting point is measurement: a documented Share of Answer baseline tells you whether you are absent, partially present, or already winning. The methodology compounds from there.

If your buyers are using voice or asking questions that surface in AI Overviews and Featured Snippets, the AEO subset of GEO is your priority focus area. Deploy FAQPage schema, restructure your H2s into question format, lead with direct answers in the first 2 sentences of every section. This is mechanical work with measurable lift in 4–8 weeks.

For most growth-stage B2B brands in 2026, the honest answer is SEO + GEO together, with no separate AEO line item. The technical primitives overlap heavily. The measurement layers are different. The price for both, executed by a serious provider, is in the 3,000–6,000 EUR/month band — not double that.

What changes signal-by-signal

Concretely, here is how the same site-level signal shows up in each discipline:

Signal	SEO weight	GEO weight	AEO weight (subset of GEO)
Backlinks	High	Medium	Low
Domain authority	High	Medium	Low
Schema (Organization)	Low	High	Medium
Schema (FAQPage)	Low	High	High
Schema (Article)	Medium	High	Medium
sameAs entity chain	Low	High	Medium
Core Web Vitals	High	High	High
Content extractability	Low	High	High
Question-format H2s	Low	High	High
Lead-with-the-answer paragraph structure	Low	High	High
Author attribution (Person schema)	Medium	High	Medium
Third-party citations in authoritative sources	Medium (via backlinks)	High	Medium
AI crawler access (GPTBot etc.)	None	High	High
Wikipedia / Wikidata presence	Low	High	Medium

The pattern is clear: GEO weights signals SEO has historically de-prioritized, especially the entity layer and the extractability layer. A site that has done SEO well will have a meaningful head start on GEO — but it will not be done.

What about LLM optimization, brand visibility in AI, AI SEO, etc.?

These are all the same thing as GEO under different labels. Buyers should not let label proliferation confuse the underlying market. The work is real; the labels are mostly marketing.

The label we use is GEO because it is the most precise (it explicitly names the surface — generative engines), it has emerged as the dominant academic and industry term over the past 18 months, and it does not collide with the existing AEO subset.

What to do this week

Three concrete moves, regardless of which label your current vendor is using:

1. Run the brand audit yourself, free. Open ChatGPT, Perplexity, and Gemini. Type 10 prompts your ICP would type to find a brand like yours. Count how many times your brand appears. If the answer is zero or one, you have a measurable AI visibility gap regardless of how strong your SEO is.
2. Audit your sameAs chain. Open the JSON-LD on your homepage. Does it have an Organization schema with a sameAs array referencing Wikipedia, LinkedIn, Crunchbase, and Wikidata? If it does not, this is the highest-leverage 30-minute change you can make this quarter.
3. Check your robots.txt for AI crawler blocks. Confirm that GPTBot, ClaudeBot, PerplexityBot, OAI-SearchBot, and Google-Extended are explicitly allowed. Many sites that locked down crawlers during the 2023–2024 scraping panic are inadvertently blocking the very models they now need to be cited by.

If those three pass, you are ready for a real measurement engagement. If any of them fail, you have a problem you can fix yourself before paying anyone for anything.

If you want a documented Share of Answer baseline against which to evaluate any provider’s pitch — including ours — the AI Visibility Audit is 1,200 EUR and delivers in 5 business days. We do not invent a separate AEO audit; we do not invent a separate LLM visibility audit. There is one engagement and one number. The number is what gets better.