SEO is the work of getting found and chosen through search engines. AEO (answer engine optimization) and GEO (generative engine optimization) are two names for getting included and cited in AI-generated answers, and in practice they describe the same work. The three share most of their foundations; what differs is where you appear, what counts as winning and how you measure it.
What do SEO, AEO and GEO mean?
| Term | Stands for | Where the definition comes from | What it aims at |
|---|---|---|---|
| SEO | Search engine optimization | Google's SEO Starter Guide: helping search engines understand your content, and helping users find your site through search | Being ranked, shown and clicked in search results |
| AEO | Answer engine optimization | Google's generative AI guide lists it as a term for work on visibility in AI search; Perplexity describes itself as an answer engine that searches, picks trusted sources and writes one answer | Being a source an answer engine uses and cites |
| GEO | Generative engine optimization | A research paper by Aggarwal and colleagues, first posted in November 2023 and accepted to KDD 2024 | Being visible inside the responses generative engines write |
Read literally, AEO names the product (an engine that answers) and GEO names the technology (an engine that generates). The work behind both labels is the same. What is answer engine optimization? and what is generative engine optimization? define each term on its own.
Where does the term GEO come from?
GEO comes from a paper, "GEO: Generative Engine Optimization", by Pranjal Aggarwal, Vishvak Murahari, Tanmay Rajpurohit, Ashwin Kalyan, Karthik Narasimhan and Ameet Deshpande (arXiv 2311.09735). It was first posted on 16 November 2023, revised through 28 June 2024, and accepted to the KDD 2024 conference.
The paper describes generative engines as systems that answer queries by gathering information from multiple sources and summarizing it with large language models. It introduced GEO as a way for content creators to improve their visibility in those responses, and GEO-bench, a benchmark of 10,000 queries, to test it. Its main findings:
- Classic keyword stuffing did not work. The authors tested nine ways of rewriting a source page, and keyword stuffing was among those that performed poorly.
- Evidence did. Adding citations to credible sources, quotations and statistics performed best: a relative improvement of 30% to 40% on one of the paper's two visibility measures (position-adjusted word count) and 15% to 30% on the other (a judged "subjective impression" score). The paper's published prompts let the rewriting model invent that material: quotes "even though fake and artificial", statistics "even if hypothetical", and sources it "may invent". Its test engine was built on GPT-3.5. So the gain shows what quote-, statistic- and citation-shaped text did to that engine, not that real evidence has the same effect on today's engines.
- It held up on a live engine. Tested on Perplexity, the methods improved visibility by up to 37%.
- Lower-ranked sites gained most. In one result, citing sources raised the visibility of sites ranked fifth in search results by 115.1%, while the top-ranked site's visibility fell by 30.3% on average.
Read those numbers as lab results. The test engine wrote answers with GPT-3.5 over search results, and the engines people use have changed since. What is retrieval-augmented generation? explains the retrieve-then-write design the paper modeled.
What do the three have in common?
More than the debate suggests. The engines' owners say so themselves:
- Google says its AI features are rooted in its core Search ranking and quality systems, and that from its perspective, optimizing for generative AI search is still SEO.
- Microsoft says Bing and Copilot rely on the same crawling, indexing and ranking foundation as traditional search, and that SEO best practices also support eligibility for AI answers and citations.
- Access comes first. Google requires pages to be indexed and eligible for a snippet; OpenAI, Anthropic and Perplexity each document a search crawler whose blocking removes or reduces your visibility; Microsoft describes Copilot as powered by Bing's index.
The content advice converges too. Google asks for original, non-commodity content; Microsoft asks for clear, focused pages whose facts stand on their own; the GEO paper found that adding evidence helped. All three point to specific, well-supported pages, which is also good SEO.
What actually differs?
The differences are real, but they sit in the output, the competition and the measurement, not in a secret set of techniques.
| Dimension | Search results (SEO) | AI answers (AEO and GEO) |
|---|---|---|
| What the searcher gets | Ranked options to choose from, per Bing | One written answer with cited sources; Bing says a grounding system may abstain when evidence is thin |
| What gets picked | The page | Passages and facts; Bing says the unit shifts from pages to individual facts that can be supported |
| Sources per answer | Many ranked results | 3.5 (Gemini) to 20.2 (Perplexity) third-party citations per answer in our scans |
| Who else shapes the result | Your pages compete with other pages | Other sites' pages about your category: roundups took 45% to 79% of citations to each engine's top third-party sites in our scans |
| How many engines to watch | The search engines your audience uses | Several AI engines with different reading lists; ChatGPT's and Grok's five most-cited sites had nothing in common in our scans |
| What counts as winning | Rankings, impressions, clicks | Mentions and citations; Bing notes a citation is not a click |
| Owner-supplied measurement | Search Console and Bing Webmaster Tools performance reports | Search Console's Generative AI performance report (impressions in AI Overviews and AI Mode) and Bing's AI Performance report (citations); OpenAI's publisher FAQ points to referral tagging (utm_source=chatgpt.com) |
The data rows come from our scans of the questions Cituna tracks about AI visibility software, 33 scans in the 30 days to 22 September 2026, described in what seven AI engines cite.
Two consequences follow. First, a single blended AI visibility score hides real differences, because the engines disagree about sources; how to measure AI share of voice shows how to measure per engine. Second, off-site work (roundups, reviews, community threads) carries a large share of the weight in AI answers, so it belongs in the plan from the start.
Where do the terms overlap, or get used loosely?
Almost everywhere:
- Google treats both as SEO. Its May 2026 guide lists AEO and GEO as terms for AI-search work, says optimizing for generative AI search is still SEO, and devotes a section to common AEO and GEO misconceptions.
- Microsoft uses GEO and SEO side by side. Bing's guidelines define GEO as focused on eligibility for grounding and reference in AI responses, and say GEO no more guarantees citations than SEO guarantees rankings. Bing called its AI Performance report an early step toward GEO tooling. A Bing product manager began a 2025 post with "Whether you call it GEO, AIO, or SEO".
- Vendors bundle them. Writesonic's homepage, for one, sells GEO, AEO and AI visibility as one platform, and several vendors, Semrush with its AI Visibility Toolkit among them, put AI visibility in their product names (what is AI visibility?).
So when someone says AEO or GEO, ask what they will actually do and measure. The label rarely tells you.
What can you ignore?
Google is blunt about Google Search. It says you can ignore llms.txt and other special AI files, splitting pages into small chunks, rewriting content just for AI, chasing inauthentic mentions and treating structured data as required. It adds that keeping an llms.txt for other services is fine; Google Search simply ignores it. What is llms.txt? covers the file.
Microsoft's line on structured data is slightly different: it may support clearer grounding in Bing, but it does not guarantee visibility. Both companies warn against manipulation: Google against scaled content made to game AI answers, Microsoft against prompt injection.
So which should you do?
All three, as one program. SEO fundamentals are the entry ticket to Google's and Microsoft's AI answers, and letting the engines' search crawlers in is the entry ticket for ChatGPT, Claude and Perplexity. The AI-specific layer is measurement by engine, outreach to the sources each engine cites, and fact-dense pages that can be quoted. 10 ways to get cited by AI answer engines lists the tactics with the evidence for each.
What to do first
- Agree on what you measure: rankings and clicks for search, mentions and citations per engine for AI answers.
- Check that search crawlers and AI search agents can reach your pages.
- Open Search Console's Generative AI performance report and Bing's AI Performance report.
- Pick five buyer questions and see which sources each engine cites for them.
Correction
23 September 2026: added what the GEO paper's published prompts allowed (invented quotes, statistics and sources) and the GPT-3.5 test engine, so the 30 to 40 percent figure is not read as proof that real evidence works the same way.