AEO vs GEO vs SEO and Why B2B Teams Should Stop Separating Them
AEO vs GEO vs SEO is the wrong framing, because they aren't three competing strategies. They're three lenses on the same underlying visibility system. The way we use the terms, and no industry consensus exists here, SEO targets search results pages, AEO targets featured snippets and direct answers, and GEO targets AI-generated responses in tools like ChatGPT and Perplexity.
Plenty of practitioners treat AEO as the umbrella containing GEO, or the two as synonyms. The labels matter less than the fact that each targets a different retrieval surface, and that splitting them into separate line items fragments effort that should be building all three at once.
Your CMO just asked why a competitor appears in ChatGPT answers and you don't. Someone mentions GEO. Your AI search agency starts talking about AEO. Three acronyms, one budget conversation, no clear answer about where to start.
Key takeaways:
- GEO, SEO, and AEO each target a different surface, but share most of their upstream signals
- Treating them as separate line items fragments effort and underperforms on all three
- AEO is the one most B2B teams underrate and the cheapest to act on, because the tactics are well understood and work on a single page
- The vendors measuring how ranking converts into AI citation don't agree, and the published figures span more than 2x, so no single number should drive your plan
AEO vs GEO vs SEO compared
Here is the side-by-side comparison. The most important row in this table is the last one.
The right read on this table isn't "which one do I choose." It's that these three measure different surfaces of the same underlying system. Your SEO performance feeds your GEO citation rate. Your AEO structure improves your AI Overview appearances. None of them operates in isolation.
Does SEO still matter?
SEO still matters, because the AI systems now competing with it are built on top of its signals. It's the practice of making your content rank in Google search results, and you optimize for authority, relevance, and technical performance so that your page appears near the top and gets clicked.
It has been the primary organic channel for B2B companies for over a decade, and it remains foundational.
By September 2025, 54.5% of Google AI Overview citations went to pages ranking somewhere in organic search, up from 32.3% at launch in May 2024, across nine industries tracked in BrightEdge's 16-month analysis. That figure comes from BrightEdge's own proprietary parser, which matters for what follows. BrightEdge hasn't updated it since, and AI Overviews moved to Gemini 3 in January 2026.
Why no single number is reliable
The two most-quoted studies don't line up, and the reasons are more interesting than the gap.
BrightEdge's 54.5% counts pages that rank organically at all, though it never states the rank range it treats as ranking. What it does say is that most of the growth came from positions 21 to 100. Its own page also reports only 16.7% of AI Overview citations coming from top-10 results, without saying whether that's 16.7% of all citations or 16.7% of the ranking ones, which changes the number by a factor of two.
Ahrefs puts 37.1% in the top ten organic results, from a March 2026 study of 863,000 keyword SERPs. Its more widely quoted 37.9% counts the first ten SERP blocks, which include ads and search features, so the organic figure is the one that compares. It reports the number falling from roughly 76% eight months earlier, while warning its own two datasets aren't directly comparable because it improved its parsing in between.
Read side by side that's 16.7% against 37.1%. Before calling it vendor disagreement, note the two figures are six months apart, and Ahrefs' own data shows this metric moved from 76% to 38% in eight months. That's more movement over time than the distance between the vendors, so the gap may be measuring the calendar rather than the parsers.
They do agree on direction. Neither has top-10 ranking driving citation growth: BrightEdge puts the growth in positions 21 to 100, and Ahrefs says Google is increasingly pulling from fan-out query SERPs rather than the original one. Both companies sell AI visibility tools.
The useful conclusion isn't a number. Ranking is neither necessary nor sufficient, a large share of cited pages rank poorly or not at all, with Ahrefs putting 36.7% outside the top 100 organic results. Nobody currently has a stable measurement, which is the finding.
What is Generative Engine Optimization (GEO)?
Generative Engine Optimization is the practice of structuring content so AI systems can extract, synthesize, and cite it inside generated answers. Where SEO earns you a ranked link, GEO earns you a citation inside ChatGPT's response, Perplexity's summary, or Gemini's overview.
The target audience for GEO isn't a search algorithm. It's a language model deciding which sources to pull from when constructing an answer. That changes what "good content" looks like.
In practice, three things help:
- Each paragraph standing alone as a complete, useful unit of information
- Claims that are verifiable, with numbers, sources, or named examples attached
- Authority demonstrated on the topic across multiple pieces, not covered once
Only the middle one has direct research behind it. The other two are practitioner heuristics, ours included.
The term comes from a paper by researchers at Princeton and IIT Delhi, published at KDD 2024, which found that citing sources, adding quotations and adding statistics were the content changes that moved visibility most. The figure everyone quotes from it, "up to 40%", carries caveats that matter if you're budgeting against it, and our GEO playbook for B2B sets them out.
One of the most common GEO metrics is Share of Model: how often your brand appears in AI-generated responses compared to competitors for relevant queries. It's the AI equivalent of search market share, though no standard definition or measurement method sits behind it yet, and "AI share of voice" is used just as widely.
What is Answer Engine Optimization (AEO)?
Answer Engine Optimization is the practice of structuring content to be surfaced as a direct answer rather than a ranked link. Its original application was voice search. Its current scope is much wider: Google Featured Snippets, AI Overviews, Google AI Mode, and any interface that returns an answer instead of a list.
The tactical core is question-intent content. Put the question in the heading, answer it in the first sentence beneath, keep that answer self-contained, and give it a length that fits the slot, as a rule of thumb 40 to 60 words.
One correction to advice still in wide circulation: Google deprecated FAQ rich results on 7 May 2026, and HowTo in 2023, so FAQPage markup earns nothing in Google Search now. Existing markup is harmless and AI crawlers may still parse it, but don't add it expecting a search benefit.
Where AEO and GEO diverge is in what does the extracting. AEO is extraction by existing interfaces, mainly Google's, working from a single page. GEO is citation by generative models, which adds requirements around topical authority, verifiability and depth built across multiple pieces. A well-structured FAQ page can earn AEO coverage on its own merits. It won't, by itself, make a language model treat your brand as a source worth citing.
Why splitting the three fails B2B teams
Treating GEO, SEO, and AEO as separate workstreams creates three half-strategies instead of one complete one. B2B companies feel this most acutely because their buyer journeys span the most surfaces.
The SEO team chases rankings. The content team starts optimizing for AI with a separate checklist. Someone books an agency for an AEO audit. Three workstreams, three briefs, three definitions of success, none talking to each other.
The output is predictable. Rankings hold steady but AI citations don't improve. AI citations improve for one tool but not others. AEO work produces featured snippets that nobody connects back to the pipeline report.
B2B makes this worse because the buying decision is made by a group, each member researching independently across whichever surface they trust. Visible on Google but absent from ChatGPT, you miss buyers at one stage. In Perplexity but not AI Overviews, you miss a different segment. Diagnosing where you're missing is the job our competitor gap analysis walks through.
How do the three work together?
GEO, SEO and AEO work as three layers built on one shared foundation. That is why building them separately wastes most of the effort: each layer depends on the one below it.
Foundation: technical SEO, topical authority, E-E-A-T. This serves all three. Technical problems cap everything above them, and thin topical authority keeps you out of the citation pool entirely. Build it first, and expect topical authority to be the slowest part.
Layer 2: content structure. Self-contained paragraphs, clear question-led headings and concise answers serve AEO and GEO at once. One asset, three surfaces.
Layer 3: citation signals. Original data, verifiable statistics, named examples and third-party mentions primarily serve GEO. These appear to be what shifts a language model from treating you as a relevant source to a trusted citation, though no operator documents how it chooses.
Every layer builds on the one below. The diagnostic question for your next strategy review: does your content team have one brief covering all three, or three separate strategies written by three different people?
What does this mean for your investment?
Clicks per ranking position are declining, and conversion rates from AI-referred visits run higher. For B2B companies the shift is straightforward: optimize to be cited, not just ranked.
Two data points define the scale of the change, and both come from vendors selling into this market.
The presence of an AI Overview correlates with a 58% lower click-through rate for the page ranking first, across 300,000 keywords comparing December 2023 with December 2025 in Ahrefs' February 2026 analysis. Their earlier April 2025 estimate was 34.5%, on a different design, so treat the direction as solid and the gap as indicative rather than a measured trend. Note what it measures: clicks per ranking position, not total search volume.
Against that, Semrush's July 2025 study put the average visitor arriving from an LLM at 4.4 times as valuable as the average organic visitor, a figure it derives from conversion rate rather than reporting as one. Semrush publishes no methodology behind it: no sample size, no site count, no date window. It sits inside a study of 500-plus digital marketing and SEO topics, Semrush's own category, whose other figures are labeled extrapolations. It still points the same way: fewer clicks, better-qualified ones.
For B2B companies, where lead quality matters more than lead volume, that trade is a net positive, but only for companies earning those citations. Companies treating AI visibility as an afterthought see the traffic decline without the conversion quality improvement to offset it.
FAQs
Is GEO the same as SEO?
No. SEO optimizes content to rank in Google search results, while GEO optimizes content to be cited inside AI-generated answers from tools like ChatGPT, Perplexity and Gemini. They share the same upstream signals but target different output surfaces.
Must you choose between the three?
No. The most effective approach builds them as one unified visibility stack rather than three separate workstreams, because the foundation of technical SEO, topical authority and E-E-A-T serves all three. Separating them creates duplicated effort and underperforms on all three.
What is Share of Model?
Share of Model measures how often your brand appears in AI-generated responses, compared to competitors, for a defined set of relevant queries. No standard definition exists yet, and some teams call the same idea AI share of voice. It's the AI search equivalent of search market share.
Is AEO the same as GEO?
No, though they share most of their tactics. AEO targets the answer slot in an existing interface, mainly Google's, and works from a single page, while GEO targets citation inside a generated response and depends on authority built across multiple pieces. You can earn AEO on one well-structured page; GEO takes a body of work.
Do you need special AEO tools?
Not to start. AEO progress is visible in Search Console and by checking whether your answers get lifted, and GEO needs a fixed prompt set run across ChatGPT, Perplexity and AI Overviews, which you can do by hand for a first diagnosis. Dedicated platforms earn their place when you need to track movement over time rather than diagnose once.
Does AEO only apply to voice search?
No. Voice search was AEO's original application, but its scope now covers Google Featured Snippets, AI Overviews, Google AI Mode, and any interface returning a direct answer instead of a list. Question-intent structure and concise 40 to 60 word answers serve all of them.
Which matters more, GEO or SEO?
Neither, in isolation. SEO authority helps get your pages into the pool AI systems draw from, but ranking converts into citation less reliably than it used to, and the two vendors measuring that conversion disagree by more than 2x. Fund the shared foundation first, then the GEO layer.
When do you need outside help?
The clearest signal is a gap between your Google rankings and your AI citation rate. Ranking well in traditional search but rarely appearing in ChatGPT, Perplexity or AI Overviews means your content is structured for ranking rather than citation. Our guide to evaluating B2B content vendors covers what to ask before you sign anything.
Moving from definitions to execution
GEO, SEO, and AEO aren't three choices. They're one strategy with three lenses, sharing one foundation and diverging only at the surface they target.
Start by auditing which surfaces you're already visible on, then fund the shared foundation before the layer above it.
