GEO / AEO vs SEO

For Google’s AI features, the company says the same SEO basics continue to apply. Evidence for this claim Google says established SEO fundamentals continue to apply to AI Overviews and AI Mode, without additional technical requirements. Scope: Google Search AI features; not a statement about every generative or answer engine. Confidence: high · Verified: 2026-07-14 Google: AI features and your website GEOGenerative Engine Optimization (GEO) is the practice of optimizing content and brand presence so AI-powered search engines and assistants — Google AI Overviews, ChatGPT, Perplexity — cite, recommend, or mention you when generating answers. Google's position is that it's still SEO., by contrast, originated as a research framework for visibility inside generated answers. Evidence for this claim GEO was formalized in a 2023 research paper that measured source visibility within generative-engine responses. Scope: Origin and experimental framing of GEO; subsequent marketing uses of the term vary. Confidence: high · Verified: 2026-07-14 Aggarwal et al.: GEO paper

TL;DR — GEOGenerative Engine Optimization — visibility inside AI answer engines. and AEOAnswer Engine Optimization (AEO) is the practice of structuring content so engines deliver it as a direct answer — featured snippets, voice assistants, and AI search — rather than just a ranked link. Coined for voice search in 2018 and revived for the LLM era. Google's position is that it's still SEO. are mostly the same job as SEO, just aimed at AI answers instead of blue links. The big stuff is identical: good content, being a trusted source, and a site that search engines can actually read. Google even says optimizing for AI searchAI search uses large language models and retrieval-augmented generation (RAG) to synthesize an answer from multiple sources rather than returning a ranked list of links. Examples include Google AI Overviews, ChatGPT Search, and Perplexity. “is still SEO.” The one thing that’s genuinely different: what the rest of the internet says about you (brand mentions) now matters more than links pointing at you — which is backwards from how traditional SEO works. That’s a correlation from one dataset, though, not a guarantee — treat it as a signal to watch, not a lever with a proven cause-and-effect.

The acronyms, in one breath

You’ll see three terms thrown around, and they overlap a lot:

• SEO (Search Engine Optimization) — getting your pages to rank in the list of links on Google and Bing. The original job.
• AEO (Answer Engine Optimization) — getting your content delivered as the answer: a featured snippet, a voice-assistant reply, an AI answer box. The goal is for the engine to read your text aloud or paste it at the top.
• GEO (Generative Engine Optimization) — getting cited inside an AI-written answer from ChatGPT, Perplexity, or Google’s AI OverviewsAI Overviews are the AI-generated summary box Google shows above or within its regular search results, written by Gemini models from pages retrieved out of Google's normal Search index. It's a Search feature, not a separate platform or index..

The cleanest way to keep AEO and GEO apart: with AEO you ARE the answer, with GEO you’re CITED in the answer. In real life the tactics for both are nearly the same, and plenty of people use the words interchangeably.

What’s actually the same

Almost everything. All three reward:

• Quality, helpful content written for people.
• Authority — being a source others trust.
• Technical basics — a page that can be crawled and indexedStoring a crawled page in the search index so it can appear in results. Crawled is not the same as indexed — Google selects what to keep, and indexing isn't guaranteed.. If Google can’t read your page, an AI can’t cite it either, because most AI searchAI search uses large language models and retrieval-augmented generation (RAG) to synthesize an answer from multiple sources rather than returning a ranked list of links. Examples include Google AI Overviews, ChatGPT Search, and Perplexity. reads from the same web indexes.

That’s why Google’s own guidance says you don’t need a separate playbook or special files to show up in AI OverviewsAI Overviews are the AI-generated summary box Google shows above or within its regular search results, written by Gemini models from pages retrieved out of Google's normal Search index. It's a Search feature, not a separate platform or index.. Do good SEO and you’re most of the way there.

What’s actually different

One thing stands out, and it’s a real flip:

Unlinked brand mentions matter more than backlinks. In traditional SEO, a mention of your brand that isn’t a clickable link is worth almost nothing — links are the currency. In AI search, those plain mentions are the strongest signal I’ve measured (more on the numbers in the Advanced tab). So PR, podcasts, and getting talked about across the web now feed your AI visibilityLLM visibility (or AI visibility) is the aggregate measure of how often and how prominently a brand or page shows up in AI-generated answers — across AI Overviews, ChatGPT, Perplexity, Copilot, and Gemini. It's the AI-search analog of organic visibility, but it's driven by different signals. directly.

A few smaller differences follow from that:

• There’s no “position 1.” You’re either cited or you’re not. A page ranking #5 in Google can get cited just as easily as the #1 page.
• Keyword stuffing backfires in AI answers (it can still scrape by in some traditional searches).
• AI traffic is tiny but high-quality — far fewer visitors than Google sends, but they convert at a much higher rate.

The bottom line

Do your SEO first — it’s the foundation and it’s where the traffic still is. Then layer the AI-specific signals on top: earn brand mentions, write clear front-loaded answers, keep key pages fresh. You’re not replacing anything. Want the data and the official quotes? Switch to the Advanced tab.

Google explicitly frames AI-feature eligibility through existing Search requirements rather than a new technical discipline. Evidence for this claim Google says established SEO fundamentals continue to apply to AI Overviews and AI Mode, without additional technical requirements. Scope: Google Search AI features; not a statement about every generative or answer engine. Confidence: high · Verified: 2026-07-14 Google: AI features and your website The original GEOGenerative Engine Optimization (GEO) is the practice of optimizing content and brand presence so AI-powered search engines and assistants — Google AI Overviews, ChatGPT, Perplexity — cite, recommend, or mention you when generating answers. Google's position is that it's still SEO. paper measured generative-answer visibility under its own benchmark, so its tactics should not be treated as permanent platform rules. Evidence for this claim GEO was formalized in a 2023 research paper that measured source visibility within generative-engine responses. Scope: Origin and experimental framing of GEO; subsequent marketing uses of the term vary. Confidence: high · Verified: 2026-07-14 Aggarwal et al.: GEO paper

TL;DR — GEOGenerative Engine Optimization — visibility inside AI answer engines., AEOAnswer Engine Optimization (AEO) is the practice of structuring content so engines deliver it as a direct answer — featured snippets, voice assistants, and AI search — rather than just a ranked link. Coined for voice search in 2018 and revived for the LLM era. Google's position is that it's still SEO., and SEO sit on the same foundation: quality content, authority, E-E-A-T, and technical eligibility — and AI searchAI search uses large language models and retrieval-augmented generation (RAG) to synthesize an answer from multiple sources rather than returning a ranked list of links. Examples include Google AI Overviews, ChatGPT Search, and Perplexity. runs RAGRAG is the retrieve-then-generate pattern behind AI search: the system retrieves relevant passages from an external index at query time, injects them into the model's context, and generates an answer grounded in those sources — without changing the model's weights. over the same web indexes traditional search uses, so most SEO carries over for free. Google and Bing both frame AI optimization as “still SEO.” The genuinely different part is one structural inversion: in Ahrefs’ 75,000-brand correlation study, branded web mentions correlate 0.664 with AI OverviewAI Overviews are the AI-generated summary box Google shows above or within its regular search results, written by Gemini models from pages retrieved out of Google's normal Search index. It's a Search feature, not a separate platform or index. brand visibility versus Domain Rating’s 0.326 — unlinked mentions, near-worthless in classic SEO, are the strongest AI signal. Everything else that’s “different” (citation vs. rank as the metric, passage-level retrieval, rank-5 beating rank-1, keyword stuffing hurting, 23x conversion at 190x less traffic) follows from how AI answers are assembled. Caveat: the correlation is descriptive, not causal, and none of these labels guarantee ranking, citation, traffic, or conversion lift. Priority: do SEO, then layer the AI signals on top.

First, the definitions that matter

None of these three labels are standardized the way SEO is. SEO carries decades of shared search-industry usage; GEO and AEO definitions vary by author, product, surface, and date — treat any GEO/AEO claim (including mine) as scoped to whoever is using the term, not an industry consensus.

Three acronyms, one job, three vantage points:

• SEO wins ranked link placement for a URL.
• AEO makes you be the answer — the engine extracts your text for a featured snippet, a voice reply, or an AI answer. Coined by Jason Barnard in a January 2018 Trustpilot white paper, originally a voice-search and featured-snippet idea, then revived for the LLMA large language model (LLM) is a deep-learning model trained on massive text corpora to predict the next token and generate human-like text. LLMs use the transformer architecture and power AI search features like Google's AI Overviews (Gemini) and Bing Copilot (GPT-4). era.
• GEO gets you cited as a source inside a synthesized AI response. Coined academically by Aggarwal et al. (KDD 2024).

The pedagogically useful split is you ARE the answer (AEO) vs. you’re CITED in the answer (GEO) — distinct origins, but the 2025–26 tactics overlap ~90%, so I’ll mostly treat GEO/AEO as one thing against SEO below.

What’s the same across all three

This is most of the surface area, and it’s why I keep calling this evolution, not revolution.

• Quality content is the foundation. The same helpful, people-first contentThe Helpful Content Update (HCU) was a series of Google updates starting in August 2022 that added a site-wide, machine-learning classifier to demote content made primarily to rank rather than to help people. In March 2024 it was folded into Google's core ranking system. that ranks also gets cited.
• Authority still matters — it’s just measured differently (next section). The concept “trusted sources win” is unchanged.
• Technical eligibility is a shared gate. A page that can’t be crawled and indexedStoring a crawled page in the search index so it can appear in results. Crawled is not the same as indexed — Google selects what to keep, and indexing isn't guaranteed. can’t be cited. CrawlabilityCrawlability is how well search engine crawlers can discover, access, and fetch a site's pages. A crawlability issue is any technical condition — blocked access, broken links, server failures, or bloated URL inventory — that stops pages from reaching the index., indexability, HTTPSHTTPS is the encrypted version of HTTP — it uses TLS to authenticate the server and protect data in transit between a browser and a website. Google announced it as a lightweight ranking signal in 2014 and today conditionally prefers HTTPS pages as canonical; Chrome marks plain HTTP pages 'Not Secure.', and structure are prerequisites for both.
• AI searchAI search uses large language models and retrieval-augmented generation (RAG) to synthesize an answer from multiple sources rather than returning a ranked list of links. Examples include Google AI Overviews, ChatGPT Search, and Perplexity. reads the same indexes. Google AI OverviewsAI Overviews are the AI-generated summary box Google shows above or within its regular search results, written by Gemini models from pages retrieved out of Google's normal Search index. It's a Search feature, not a separate platform or index., ChatGPT Search, Bing Copilot, and Perplexity ground answers with retrieval-augmented generation (RAG) — pulling from the same web indexes traditional search uses. Microsoft says it outright: getting cited “comes down to two things: first, make sure Bing has indexed your content so it appears in result sets, and second, make sure your content is clear, structured, and trustworthy enough to win the citation.”

What’s genuinely different — the signal inversion

If you remember one thing, remember this. In Ahrefs’ 75,000-brand correlation study by Louise Linehan and Xibeijia Guan, which I presented and interpreted at Ahrefs Evolve 2025, the signals predicting Google AI Overview inclusion line up like this:

Read that top-to-bottom: unlinked brand mentions — which pass no PageRankPageRank is Google's original recursive link-graph algorithm: a page's score depends on the scores of the pages linking to it, and in the published model each page's score is split across its outbound links (the simplified version: links are weighted votes). Google says it's evolved since launch but still part of its core ranking systems. and contribute almost nothing in traditional SEO — are the single strongest predictor, and they beat Domain Rating, the classic link-based authority proxy. That is a structural inversion, not a marginal difference. It means PR, social, and brand-building teams now own a direct AI-visibility lever, not just an indirect one. My one-line framing of the whole shift: “From ‘Optimize Your Site’ → ‘Optimize How The Internet Talks About You’.”

That table is a dated correlation from one dataset, not a causal test. It doesn’t control for confounders — an established brand may earn both more mentions and more AI Overview inclusion because it’s simply bigger and better-known, not because the mentions caused the inclusion — and no controlled experiment here isolates whether adding mentions moves inclusion for a given site. Read it as a descriptive predictor worth tracking, not a guaranteed lever.

The other differences (they follow from how answers are built)

These are real, but they’re downstream of “an AI assembles an answer from passages” rather than “a SERP ranks URLs”:

• Citation, not rank, is the success metric. SEO gives you a position number (average position 2.3). AI search gives you cited / not-cited — and even that is hard to measure consistently. There’s no “outranking” anyone; you’re in the citation set or you’re not.
• Passage-level retrieval, not URL-level ranking. AI systems extract specific passages and can synthesize across several pages. So a rank-5 page can be cited over the rank-1 page if it has the better paragraph for the sub-question — which is structurally impossible in a traditional SERP. The Princeton GEO paper found rank-5 pages gained +115.1% in citation frequency from GEO tactics, while the rank-1 page actually lost ~30.3%.
• Keyword stuffing inverts. The same GEO paper measured keyword stuffing at -9% for AI citation. In limited exact-match SEO cases it can still scrape a marginal benefit; in AI answers it degrades fluency and hurts you.
• A different traffic profile. AI search sends far less traffic — in my analysis of 76,000 sites, Google sent roughly 190x more website traffic than ChatGPT, and ChatGPT’s estimated click-through rate was about 96% lower than Google’s (1.3% vs. 29.2%). But that trickle converts: in my analysis of Ahrefs’ June 2025 internal data, I found AI search visitors converted at about 23x the rate of traditional organic search for Ahrefs. Tiny channel, disproportionately valuable.

The AEO-specific angle

AEO predates GEO and came from a different place — voice search and featured snippets, where there is exactly one spoken or boxed answer. That origin is why the AEO mental model is “be the extractable answer”: front-load a direct one-to-two sentence answer under a clear heading, use tables and lists, keep it simple. GEO’s origin is the LLM citation. In 2025–26 they’ve converged — the same structured, front-loaded, citable content wins both — but the distinction is worth keeping because it tells you what you’re optimizing toward: extraction (AEO) vs. inclusion as a cited source (GEO).

The “still SEO” case

The official positions are unambiguous. Google: “From Google Search’s perspective, optimizing for generative AI search is optimizing for the search experience, and thus still SEO,” with “no additional requirements to appear in AI Overviews or AI Mode.” Danny Sullivan’s compressionCompression (HTTP content encoding) shrinks text-based responses — HTML, CSS, JS, JSON, SVG, XML sitemaps — before they're sent over the network, using an algorithm like Gzip, Brotli, or Zstd, so the browser or crawler downloads fewer bytes. It's not a ranking factor, but it speeds up page loads and helps pages stay under crawler fetch limits. of it: “Good SEO is good GEO.” Ryan Law’s Ahrefs piece is titled, accurately, GEO, LLMO, AEO… It’s All Just SEO. The practitioner data agrees — most companies run AI search through their existing SEO teams rather than a separate specialty.

That guidance is scoped to Google’s own AI features. AI Overviews and AI Mode run on Google’s crawl, index, and eligibility systems, so Google’s “still SEO” framing doesn’t automatically extend to ChatGPT, Perplexity, or other generative products — those run their own retrieval and source-selection systems outside Google’s control, even where the underlying tactics overlap in practice.

The “actually different” case

The honest counterweight: the brand-mention inversion is not cosmetic. A site with many mentions but mediocre backlinks can out-cite a high-DR site with fewer mentions — something that doesn’t happen in a traditional SERP. Combine that with passage-level retrieval (page authority no longer guarantees the citation), citation-not-rank measurement, and a fundamentally different traffic/conversion profile, and you have enough divergence to warrant attention even if it doesn’t warrant a separate team. “Evolution” doesn’t mean “no change” — it means the foundation holds while the execution layer expands.

Keep outcomes and measurement scoped

Two guardrails before you act on any of this:

• Don’t collapse outcomes into one score. Ranking, retrieval, context inclusion, extraction, mention, citation, prominence, clicks, conversions, and revenue are separate things. A tactic that moves one doesn’t necessarily move the others — the GEO paper’s rank-5/rank-1 numbers above are about citation frequency inside its own benchmark, not clicks or revenue. None of the SEO, AEO, or GEO labels or tactics guarantee ranking, extraction, mention, citation, traffic, or conversion lift; they’re a description of what tends to correlate, not a promise.
• Scope every measurement. Google Search ConsoleA free Google service that reports how a site performs in Google Search and surfaces problems with how Google crawls, indexes, and serves it. It's first-party data straight from Google — but you don't need it to appear in results. reports clicks, impressions, CTR, and position for Google Search under its own documented dimensions — it doesn’t observe ChatGPT, Perplexity, or other generative products. Treat any GEO/AEO visibility claim (including the numbers on this page) as tied to a specific provider, prompt, model, market, and date; an unscoped “AI visibility” figure isn’t measuring anything specific.

Practical priority

Do SEO first; it’s the foundation and it’s where the volume still is. Then layer the incremental AI signals on top — none of them conflict with SEO (except keyword stuffing, which already hurt both):

1. Earn brand mentions across credible third-party sites, podcasts, and publications — the 0.664 signal.
2. Write passage-quality answers — every section should answer its question in the first two or three sentences.
3. Establish entity clarity — consistent brand/author identity, Wikipedia/ Wikidata, sameAs.
4. Keep key pages fresh — AI assistants lean toward recently updated material.

Weight the AI signals more heavily when your audience is high-converting (B2B, research and informational intent) — that’s where the 23x conversion makes a tiny channel worth real effort. For a deeper hub on the whole topic, see AI search optimizationAI search optimization is the practice of making your brand and content visible, citable, and accurately represented across AI-powered search — Google AI Overviews, ChatGPT, Perplexity, Copilot. It's built on traditional SEO plus a heavier emphasis on off-site brand mentions and content AI systems can cite..

AI summary

A condensed take on the Advanced version:

• One job, three vantage points. SEO = ranked links; AEOAnswer Engine Optimization (AEO) is the practice of structuring content so engines deliver it as a direct answer — featured snippets, voice assistants, and AI search — rather than just a ranked link. Coined for voice search in 2018 and revived for the LLM era. Google's position is that it's still SEO. = be the extracted answer; GEOGenerative Engine Optimization (GEO) is the practice of optimizing content and brand presence so AI-powered search engines and assistants — Google AI Overviews, ChatGPT, Perplexity — cite, recommend, or mention you when generating answers. Google's position is that it's still SEO. = be cited in a synthesized AI answer. AEO/GEOGenerative Engine Optimization — visibility inside AI answer engines. tactics overlap ~90%.
• What’s the same (most of it): quality content, authority, E-E-A-T, and technical eligibility — and AI searchAI search uses large language models and retrieval-augmented generation (RAG) to synthesize an answer from multiple sources rather than returning a ranked list of links. Examples include Google AI Overviews, ChatGPT Search, and Perplexity. runs RAGRAG is the retrieve-then-generate pattern behind AI search: the system retrieves relevant passages from an external index at query time, injects them into the model's context, and generates an answer grounded in those sources — without changing the model's weights. over the same web indexes, so SEO carries over. Google and Bing both call it “still SEO.”
• The one structural difference: branded web mentions correlate 0.664 with AI OverviewAI Overviews are the AI-generated summary box Google shows above or within its regular search results, written by Gemini models from pages retrieved out of Google's normal Search index. It's a Search feature, not a separate platform or index. inclusion vs. Domain Rating’s 0.326. Unlinked mentions, near- worthless in classic SEO, are the strongest AI signal — an inversion, not a tweak.
• Downstream differences: citation (not rank) is the metric; passage-level retrieval means a rank-5 page can beat rank-1 (+115.1% vs. -30.3% in the Princeton paper); keyword stuffing -9%; AI sends ~190x less traffic but converts ~23x better.
• AEO angle: “you ARE the answer” (voice/snippet origin, 2018) vs. GEO’s “you’re cited” (LLMA large language model (LLM) is a deep-learning model trained on massive text corpora to predict the next token and generate human-like text. LLMs use the transformer architecture and power AI search features like Google's AI Overviews (Gemini) and Bing Copilot (GPT-4). era) — converged in practice.
• Guardrails: the 0.664 correlation is descriptive, not causal (one dataset, unconfirmed confounds); keep rank, extraction, mention, citation, click, conversion, and revenue as separate outcomes rather than one visibility score; Google’s “still SEO” framing covers Google’s own surfaces, not every generative product; scope any AI-visibility number to a provider, prompt, model, market, and date (GSCA free Google service that reports how a site performs in Google Search and surfaces problems with how Google crawls, indexes, and serves it. It's first-party data straight from Google — but you don't need it to appear in results. only observes Google Search). None of these labels guarantee ranking, citation, traffic, or conversion lift.
• Priority: do SEO first, then layer brand mentions, passage clarity, entity signals, and freshness on top. Nothing conflicts (except keyword stuffing).

Official documentation

Primary-source documentation on how AI optimization relates to SEO.

Google

• AI optimization guide — the “optimizing for generative AI searchAI search uses large language models and retrieval-augmented generation (RAG) to synthesize an answer from multiple sources rather than returning a ranked list of links. Examples include Google AI Overviews, ChatGPT Search, and Perplexity. is still SEO” guidance; what you do and don’t need.
• AI features in Google Search — how AI OverviewsAI Overviews are the AI-generated summary box Google shows above or within its regular search results, written by Gemini models from pages retrieved out of Google's normal Search index. It's a Search feature, not a separate platform or index. and AI Mode work (RAGRAG is the retrieve-then-generate pattern behind AI search: the system retrieves relevant passages from an external index at query time, injects them into the model's context, and generates an answer grounded in those sources — without changing the model's weights. / groundingGrounding is anchoring an AI model's answer to source documents it retrieves at the moment you ask — not to the patterns frozen into its weights during training. Retrieval-Augmented Generation (RAG) is the most common way to do it. and query fan-outQuery fan-out is the technique where an AI search system breaks a single user question into multiple related sub-queries, runs those searches concurrently, and synthesizes the retrieved results into one answer. Google confirms AI Overviews and AI Mode 'may use a query fan-out technique' issuing multiple related searches across subtopics.), and why SEO best practices carry over.
• In-Depth Guide to How Google Search Works — the crawl → indexStoring a crawled page in the search index so it can appear in results. Crawled is not the same as indexed — Google selects what to keep, and indexing isn't guaranteed. → serve foundation AI features are rooted in.

Bing / Microsoft

• Introducing AI Performance in Bing Webmaster Tools (Feb 2026) — citation counts, cited pages, and groundingGrounding is anchoring an AI model's answer to source documents it retrieves at the moment you ask — not to the patterns frozen into its weights during training. Retrieval-Augmented Generation (RAG) is the most common way to do it. queries — the first publisher view of Copilot citation data.
• Optimizing for generative AI and public websites — Bing’s “make sure you’re indexed, then win the citation” framing.

Quotes from the source

On-the-record statements on whether AI optimization is its own discipline. Each link is a deep link that jumps to the quoted passage.

Google — “it’s still SEO”

• “From Google Search’s perspective, optimizing for generative AI searchAI search uses large language models and retrieval-augmented generation (RAG) to synthesize an answer from multiple sources rather than returning a ranked list of links. Examples include Google AI Overviews, ChatGPT Search, and Perplexity. is optimizing for the search experience, and thus still SEO.” — Google Search Central, AI optimization guide. Jump to quote
• “The best practices for SEO continue to be relevant because our generative AI features on Google Search are rooted in our core Search ranking and quality systems.” Jump to quote
• “Good SEO is good GEOGenerative Engine Optimization (GEO) is the practice of optimizing content and brand presence so AI-powered search engines and assistants — Google AI Overviews, ChatGPT, Perplexity — cite, recommend, or mention you when generating answers. Google's position is that it's still SEO..” — Danny Sullivan, Google Search Liaison, via Search Engine Land (November 2025).

Microsoft Bing — indexedStoring a crawled page in the search index so it can appear in results. Crawled is not the same as indexed — Google selects what to keep, and indexing isn't guaranteed. first, then win the citation

• “Getting cited comes down to two things: first, make sure Bing has indexed your content so it appears in result sets, and second, make sure your content is clear, structured, and trustworthy enough to win the citation over competitors.” — Microsoft Copilot guidance. Jump to quote

Ryan Law, Ahrefs — it’s all just SEO

• “the core mechanism for improving visibility in LLMA large language model (LLM) is a deep-learning model trained on massive text corpora to predict the next token and generate human-like text. LLMs use the transformer architecture and power AI search features like Google's AI Overviews (Gemini) and Bing Copilot (GPT-4). output is: creating relevant content on topics your brand wants to be associated with, both on and off your website. That’s SEO.” — Ryan Law, GEO, LLMO, AEO… It’s All Just SEO (April 2025). Jump to quote

What to ADD for GEO/AEO (don’t replace your SEO)

Assuming your SEO fundamentals are already in place — crawlable, indexable, quality content, sound architecture — these are the incremental moves that earn AI visibility. None of them replace SEO work; they layer on top.

• Earn unlinked brand mentions in credible third-party publications, podcasts, and industry sites (the 0.664 signal — stronger than backlinks for AI).
• Front-load every section’s answer — the specific question answered in the first two or three sentences, then the supporting detail.
• Add original data/research where you can — studies and comparison pages out-cite standard blog posts in AI answers.
• Establish entity clarity — consistent brand/author identity, Wikipedia/ Wikidata where applicable, sameAs schema, consistent NAP.
• Keep key pages fresh — AI assistants lean toward recently updated material.
• Drop keyword stuffing entirely — it’s -9% for AI citationAn AI citation is the visible source link an AI answer engine shows next to its generated text — the clickable reference that credits the web page it used. A citation's presence is a separate thing from whether the cited page actually supports the statement, and from being retrieved (read behind the scenes) or merely mentioned (named without a link); citation is driven more by brand mentions and being retrievable than by traditional ranking. (and it wasn’t helping much in SEO either).
• Don’t block AI crawlersAI crawlers are bots from AI companies that fetch web pages to train language models, build AI-search indexes, or answer live user questions. They come in three categories, each with its own user-agent tokens and its own robots.txt controls. if you want AI visibilityLLM visibility (or AI visibility) is the aggregate measure of how often and how prominently a brand or page shows up in AI-generated answers — across AI Overviews, ChatGPT, Perplexity, Copilot, and Gemini. It's the AI-search analog of organic visibility, but it's driven by different signals. — blocking removes you from citations and doesn’t help traditional SEO.
• Skip the “AI magic” busywork — no llms.txtllms.txt is a proposed (not adopted) Markdown file at /llms.txt that gives AI systems a curated map of a site's most important pages. Proposed by Jeremy Howard in 2024, it's read mostly by coding agents like Claude Code — not search crawlers — and Google ignores it., no AI-only schema; Google ignores them.
• Track brand mentions and AI citationsAn AI citation is the visible source link an AI answer engine shows next to its generated text — the clickable reference that credits the web page it used. A citation's presence is a separate thing from whether the cited page actually supports the statement, and from being retrieved (read behind the scenes) or merely mentioned (named without a link); citation is driven more by brand mentions and being retrievable than by traditional ranking. alongside rankings (Ahrefs Brand Radar, GSCA free Google service that reports how a site performs in Google Search and surfaces problems with how Google crawls, indexes, and serves it. It's first-party data straight from Google — but you don't need it to appear in results. AI features, Bing AI Performance).

Traditional SEO vs. GEO/AEO — side by side

The priority model: SEO first, AI signals on top

1. Do SEO first — it’s the foundation and the volume. Crawlable, indexable, quality content, authority, sound architecture. Google sends orders of magnitude more traffic than every AI tool combined, and the AI features are rooted in the same ranking systems. Skipping SEO to chase GEOGenerative Engine Optimization (GEO) is the practice of optimizing content and brand presence so AI-powered search engines and assistants — Google AI Overviews, ChatGPT, Perplexity — cite, recommend, or mention you when generating answers. Google's position is that it's still SEO. is optimizing the 0.5% and ignoring the 99.5%.

2. Layer the incremental AI signals on top — they don’t conflict. After baseline SEO, add the levers that are genuinely AI-specific:

• Brand mentions (0.664) — the strongest AI signal, and a job for PR/social, not just links.
• Passage clarity — front-loaded answers, one question per section.
• Entity clarity — well-established brand/author entities.
• Freshness — keep key pages current.

The only thing that “conflicts” is keyword stuffing, which hurt both anyway.

3. Weight GEOGenerative Engine Optimization — visibility inside AI answer engines./AEOAnswer Engine Optimization (AEO) is the practice of structuring content so engines deliver it as a direct answer — featured snippets, voice assistants, and AI search — rather than just a ranked link. Coined for voice search in 2018 and revived for the LLM era. Google's position is that it's still SEO. more heavily when the audience justifies it. The 23x conversion rate makes a tiny channel worth disproportionate effort when:

• High-converting B2B — AI visitors are pre-vetted, high-intent buyers.
• Research and informational queries — exactly where AI answers dominate the experience and where being the cited source compounds.
• Comparison and original-data content — the content types AI answers favor.

For low-margin, high-volume, broad-consumer plays, traditional SEO still does the heavy lifting — let AI be additive, not a substitute.

Test yourself: GEO, AEO, and SEO

Resources worth your time

The “it’s all just SEO” case

• Ryan Law, GEO, LLMO, AEO… It’s All Just SEO (Ahrefs) — the clearest articulation of the convergence argument.

My studies and data

• AI Search Traffic Converts at 23x — Ahrefs Data — the conversion-quality gap.
• Insights From 56 Million AI Overviews — what shows up in AI OverviewsAI Overviews are the AI-generated summary box Google shows above or within its regular search results, written by Gemini models from pages retrieved out of Google's normal Search index. It's a Search feature, not a separate platform or index..
• AI Search Traffic by Page Type — where AI traffic actually lands.
• Meet the New Web Crawlers — AI botsAI crawlers are bots from AI companies that fetch web pages to train language models, build AI-search indexes, or answer live user questions. They come in three categories, each with its own user-agent tokens and its own robots.txt controls. vs. search botsA crawler — also called a spider or bot — is an automated program that fetches web pages, extracts their links, and queues new URLs to visit. Search engines use crawlers to discover and download content for their index..

My speaking

• GEOGenerative Engine Optimization (GEO) is the practice of optimizing content and brand presence so AI-powered search engines and assistants — Google AI Overviews, ChatGPT, Perplexity — cite, recommend, or mention you when generating answers. Google's position is that it's still SEO.? AEOAnswer Engine Optimization (AEO) is the practice of structuring content so engines deliver it as a direct answer — featured snippets, voice assistants, and AI search — rather than just a ranked link. Coined for voice search in 2018 and revived for the LLM era. Google's position is that it's still SEO.? LLMOAI search optimization is the practice of making your brand and content visible, citable, and accurately represented across AI-powered search — Google AI Overviews, ChatGPT, Perplexity, Copilot. It's built on traditional SEO plus a heavier emphasis on off-site brand mentions and content AI systems can cite.? What’s With All This AI SEO Stuff? — Ahrefs Evolve 2025 (slides, video). My standing disclaimer applies: this is my understanding, not gospel.

Ahrefs guides

• Generative Engine Optimization (GEO) and the Answer Engine Optimization guide (Despina Gavoyannis) — the GEOGenerative Engine Optimization — visibility inside AI answer engines. and AEO playbooks.

The academic source

• Aggarwal et al., GEO: Generative Engine Optimization (KDD 2024) — where the rank-5 lift and keyword-stuffing findings come from.

From around the industry

• AI optimization guide (Google Search Central) — Google’s primary statement that optimizing for generative AI is “still SEO”; no additional requirements for AI OverviewsAI Overviews are the AI-generated summary box Google shows above or within its regular search results, written by Gemini models from pages retrieved out of Google's normal Search index. It's a Search feature, not a separate platform or index..
• Optimizing for generative AI and public websites (Microsoft) — Bing’s “get indexedStoring a crawled page in the search index so it can appear in results. Crawled is not the same as indexed — Google selects what to keep, and indexing isn't guaranteed., then win the citation” framing for Copilot.
• Danny Sullivan: “Good SEO is good GEO” (Search Engine Land) — Google’s Search Liaison compressionCompression (HTTP content encoding) shrinks text-based responses — HTML, CSS, JS, JSON, SVG, XML sitemaps — before they're sent over the network, using an algorithm like Gzip, Brotli, or Zstd, so the browser or crawler downloads fewer bytes. It's not a ranking factor, but it speeds up page loads and helps pages stay under crawler fetch limits. of the convergence argument.
• GEO: Generative Engine Optimization paper summary (arXiv / KDD 2024) — Aggarwal et al. original academic paper; the source of rank-5 +115.1% and keyword-stuffing -9% findings.

Stats worth citing

• Brand mentions beat backlinks for AI. Branded web mentions correlate 0.664 with Google AI OverviewAI Overviews are the AI-generated summary box Google shows above or within its regular search results, written by Gemini models from pages retrieved out of Google's normal Search index. It's a Search feature, not a separate platform or index. inclusion vs. Domain Rating at 0.326 — the structural inversion, from Ahrefs’ 75,000-brand study by Louise Linehan and Xibeijia Guan. Source
• AI converts ~23x better. AI searchAI search uses large language models and retrieval-augmented generation (RAG) to synthesize an answer from multiple sources rather than returning a ranked list of links. Examples include Google AI Overviews, ChatGPT Search, and Perplexity. visitors convert at roughly 23x the rate of organic search in Ahrefs’ internal data — high-intent, pre-vetted users. Source
• Google sends ~190x more traffic than ChatGPT, and ChatGPT’s CTR is about 96% lower (1.3% vs. 29.2%). Tiny channel, big conversion.
• Keyword stuffing is -9% for GEOGenerative Engine Optimization (GEO) is the practice of optimizing content and brand presence so AI-powered search engines and assistants — Google AI Overviews, ChatGPT, Perplexity — cite, recommend, or mention you when generating answers. Google's position is that it's still SEO., and rank-5 pages gained +115.1% in citation frequency from GEOGenerative Engine Optimization — visibility inside AI answer engines. tactics while the rank-1 page lost ~30.3% — Princeton GEO paper (Aggarwal et al., KDD 2024). Source

GEO / AEO vs SEO

GEO, AEO, and SEO share the same foundation — quality content, authority, technical eligibility — and AI search even draws on the same web indexes. The one structural difference: unlinked brand mentions (0.664 correlation) beat backlinks (Domain Rating 0.326) for AI visibility, inverting the traditional ranking hierarchy.

Related: AI Search Optimization, Generative Engine Optimization (GEO), Answer Engine Optimization (AEO)

GEO / AEO vs SEO

GEOGenerative Engine Optimization (GEO) is the practice of optimizing content and brand presence so AI-powered search engines and assistants — Google AI Overviews, ChatGPT, Perplexity — cite, recommend, or mention you when generating answers. Google's position is that it's still SEO. (Generative Engine Optimization), AEOAnswer Engine Optimization (AEO) is the practice of structuring content so engines deliver it as a direct answer — featured snippets, voice assistants, and AI search — rather than just a ranked link. Coined for voice search in 2018 and revived for the LLM era. Google's position is that it's still SEO. (Answer Engine Optimization), and SEO (Search Engine Optimization) are all the same job from different angles. SEO earns ranked link placement; AEO makes you be the extracted answer (featured snippets, voice, AI answers); GEOGenerative Engine Optimization — visibility inside AI answer engines. gets you cited inside a synthesized AI response. In practice the tactics overlap so heavily that Google states “optimizing for generative AI searchAI search uses large language models and retrieval-augmented generation (RAG) to synthesize an answer from multiple sources rather than returning a ranked list of links. Examples include Google AI Overviews, ChatGPT Search, and Perplexity. is still SEO.”

What’s the same is most of it: quality content, authority, E-E-A-T, and technical eligibility (crawlable, indexable) all carry over, because AI searchAI search uses large language models and retrieval-augmented generation (RAG) to synthesize an answer from multiple sources rather than returning a ranked list of links. Examples include Google AI Overviews, ChatGPT Search, and Perplexity. engines run retrieval-augmented generationRAG is the retrieve-then-generate pattern behind AI search: the system retrieves relevant passages from an external index at query time, injects them into the model's context, and generates an answer grounded in those sources — without changing the model's weights. (RAG) over the same web indexes traditional search uses. A page that can’t be crawled and indexedStoring a crawled page in the search index so it can appear in results. Crawled is not the same as indexed — Google selects what to keep, and indexing isn't guaranteed. can’t be cited either.

The one structural inversion is the authority signal. In traditional SEO, links — measured by something like Domain Rating — are the dominant off-site authority proxy, and unlinked brand mentions are worth almost nothing. In AI search, that flips: in my Ahrefs correlation research, branded web mentions correlate 0.664 with appearing in Google AI OverviewsAI Overviews are the AI-generated summary box Google shows above or within its regular search results, written by Gemini models from pages retrieved out of Google's normal Search index. It's a Search feature, not a separate platform or index., well above Domain Rating at 0.326. Other differences follow from how AI answers are built — citation rather than rank as the success metric, passage-level retrieval (a rank-5 page can be cited over rank-1), keyword stuffing actively hurting, and a traffic profile that’s tiny in volume but converts far better. None of that replaces SEO; it layers on top of it.

Related: AI Search Optimization, Generative Engine Optimization (GEO), Answer Engine Optimization (AEO)

Changelog