By Mehdi HassanWhat is the difference between SEO, AEO and GEO?
SEO, AEO and GEO describe the same underlying work aimed at different outputs. SEO, search engine optimization, targets rankings and clicks in a list of results. AEO, answer engine optimization, targets being the quoted, cited source in an AI-written answer. GEO, generative engine optimization, targets being mentioned and recommended inside generated responses, with or without a link.
The labels overlap heavily, and people use AEO and GEO almost interchangeably. LLM SEO is a fourth name for roughly the same idea; see what LLM SEO is. For the full method behind all of them, start with our answer engine optimization guide.
How do SEO vs AEO vs GEO compare side by side?
Side by side, the three differ in where they show up and how you measure them far more than in what you do. The table sums it up.
SEO | AEO | GEO | |
|---|---|---|---|
Goal | Rank and earn the click | Be the cited answer | Be named in the answer |
Where it shows | Google and Bing results | AI Overviews, ChatGPT search, Perplexity | ChatGPT, Gemini, Claude, Copilot answers |
Unit that competes | The page | The passage | The brand |
Main inputs | Relevance, links, technical health | Clear, extractable answers | Mentions and reputation across the web |
Measured by | Rankings, clicks, conversions | Citations, AI referrals | Mention share in prompts |
Main tools | Search Console, rank trackers | Prompt audits, GA4 AI channel | Prompt audits, AI visibility tools |
Origin | Early web search engines | Voice search and featured snippets | 2023 Princeton research paper |
The "main inputs" row is where people expect the big differences, and it's the row with the least. A page that's crawlable, answers its question clearly and comes from a brand others mention does well on all three.
What do SEO, AEO and GEO have in common?
All three depend on the same foundation: engines must be able to crawl your page, understand it and trust it. AI answer systems retrieve from indexes and the live web; if a page can't be fetched or doesn't say anything clearly, it can't be ranked, quoted or mentioned.
Google says this outright. Its documentation for AI features states that there are no additional requirements beyond normal SEO best practice, and its May 2026 guidance calls llms.txt, content chunking, AI-specific schema and AI rewrites unnecessary. That doesn't make Google the last word on ChatGPT or Perplexity, but those engines draw on similar signals: helpful content, accessible HTML and reputation.
- Crawlable, server-rendered HTML that every bot can read.
- Pages that answer one clear question, with the answer near the top.
- Trust signals: named authors, real proof, consistent company facts.
- Freshness on pages where facts change.
Where do AI engines diverge from Google?
AI engines diverge from Google in three ways that matter: they cite pages that don't rank, they weight off-site mentions heavily, and they vary a lot from one engine to the next. Those are the real reasons AEO and GEO deserve their own attention.
They cite outside the top 10
BrightEdge puts the overlap between AI Overview citations and top-10 rankings near 17%, and Conductor says 57% of citations come from outside the top 10. Methods differ, but the direction is clear: engines break questions into sub-queries and cite whoever answers a narrow piece best. We explain how in how AI search engines choose sources.
Mentions beat links
In Ahrefs' study of 75,000 brands, web mentions correlated 0.664 with AI Overview visibility, against 0.218 for backlinks. Classic SEO has always valued links; GEO puts reputation, meaning what others say about you, closer to the center.
Engines behave differently
Semrush's AI Visibility Index, from 126 million prompts, found ChatGPT cites about 15 sources per answer and Gemini about 3. Perplexity tends to favor long-form content. A single "AI ranking" doesn't exist; you track each engine separately.
Where did the term GEO come from?
Generative engine optimization was named in a 2023 research paper from Princeton and collaborators, which tested how content changes, such as adding citations, quotations and statistics, affected visibility in generated answers from a test engine. It's a useful starting point, but it was a lab setting, not live ChatGPT or Google. We review what it found and what has held up in generative engine optimization: what the research says, and the short definition is in what GEO is.
Do you need separate SEO, AEO and GEO strategies?
No. You need one strategy with three scoreboards. Splitting the work across separate teams or vendors usually produces duplicated audits and contradictory advice, while the work underneath stays the same.
Pros
- One content plan serves rankings, citations and mentions together
- One technical audit covers every crawler
- Budget goes into pages and proof, not overlapping retainers
- Easier to see which change caused which result
Cons
- You still need separate measurement for each engine
- Mention-building needs PR-style effort SEO teams may lack
- Some engine-specific behavior can't be planned for in advance
What should you do first?
Start with the foundation all three share, then add the AEO and GEO emphases. In order: make sure every important page is server-rendered and crawlable, rewrite your money pages answer-first, give the company consistent facts across the web, and start a monthly prompt audit so you can see the AI scoreboards.
The AEO-ready website checklist turns that into 30 specific fixes. If a term in this article was new, our web design, SEO and AEO glossary defines the rest.
