What is GEO (Generative Engine Optimization)?
GEO, or Generative Engine Optimization, is the set of practices aimed at getting a brand cited and recommended inside the answers of AI assistants — ChatGPT, Gemini, Claude, Perplexity, Google AI Overviews and Grok — instead of only chasing a good position in Google's list of links.
The term comes from a foundational academic work, the paper "GEO: Generative Engine Optimization" by Aggarwal et al. (Princeton, IIT Delhi, Georgia Tech, Allen AI), accepted at the KDD 2024 conference. These researchers were the first to formalize, measure and test what makes a piece of content more likely to be picked up in a generated answer.
Three often-confused notions are worth separating. SEO (Search Engine Optimization) tries to rank a page high in Google's results list. AEO (Answer Engine Optimization) aims to provide the direct answer to a question. GEO goes further: the goal is to be cited, and ideally recommended, inside the answer the AI writes.
One-sentence definition: GEO is the craft of structuring your content and your authority so that an AI cites and recommends your brand in its answer, rather than a competitor's.
In practice, doing GEO means optimizing three things: whether you are present in the answer (citation or mention), where you appear (first, among others, or in passing), and how you are described (recommended, neutral, or with incorrect information). To go deeper, see our complete GEO guide.
GEO vs SEO: what is the real difference?
The difference lies in the target outcome. SEO works to rank a page in a list of clickable links; GEO works to get a brand cited inside a written answer. One optimizes a ranking, the other a mention. The table below sums up the practical gaps between the two disciplines.
| Criterion | Classic SEO | GEO (AI visibility) |
|---|---|---|
| Target outcome | Rank in a list of links | Be cited inside a written answer |
| Surface | Google / Bing results page | Answers from ChatGPT, Gemini, Perplexity, AI Overviews |
| Format | Title + meta + blue link | Citation, mention, recommendation in the text |
| Key metric | Position and organic traffic | Citation rate, position in the answer, share of voice |
| Main lever | Keywords, link building, technical SEO | Structure, sourced facts, authority, third-party mentions |
| Competition | The 10 results for a single query | The brands cited across every AI engine |
| Measurement | Search Console, rank trackers | Citation tracking on each AI assistant |
Is SEO still a prerequisite?
Largely, yes. Google's AI Overviews and Gemini are built on the search index, so solid SEO remains a useful foundation for those surfaces. But the link is no longer mechanical. According to an Ahrefs analysis (2025), only about 12% of the links AI engines cite sit in Google's top 10, and nearly 80% rank nowhere at all.
The same trend shows up specifically on AI Overviews: Ahrefs (2025) measured that the overlap between AI Overview citations and Google's top 10 fell from 76% to 38%. In other words, ranking first on Google helps, but it no longer guarantees being cited by the AI. GEO is becoming a discipline in its own right.
Why is GEO becoming essential in 2026?
Because usage is shifting toward generated answers that no longer send people to the web. When an AI answers directly, users click far less, and a growing share of searches end without a single visit. If your brand is not in the answer, it is simply invisible to those users.
| Phenomenon | Figure | Source |
|---|---|---|
| Decline of traditional search | ~25% less volume by 2026 | Gartner, 2024 |
| AI Overviews audience | ~1.5 billion users / month | Google / Alphabet, 2025 |
| ChatGPT audience | ~800 million weekly active users | OpenAI, 2025 |
| Perplexity volume | ~780 million queries / month | Perplexity, 2025 |
| Clicks when an AI summary appears | ~8% vs ~15% without a summary | Pew Research, 2025 |
| Zero-click searches | 58.5% in the US / 59.7% in the EU | SparkToro / Datos, 2024 |
Sources: Gartner (2024) · Alphabet (2025) · OpenAI / TechCrunch (2025) · Perplexity / TechCrunch (2025) · Pew Research (2025) · SparkToro / Datos (2024).
The key finding: when an AI summary appears, Pew Research (2025) observed that only ~8% of users go on to click a link (versus ~15% without a summary), and barely ~1% click a link inside the summary itself. Visibility is now decided in the text of the answer, not in the list of links.
How do AI assistants choose the sources they cite?
Assistants favor sources that inspire confidence and are easy to reuse: content that is recent, clearly structured, published by a source perceived as authoritative, and whose information is corroborated elsewhere on the web. The more a fact is repeated and cross-checked by several reliable sources, the more readily an AI repeats it.
Multi-source corroboration is measurable. According to Pew Research (2025), 88% of AI Overviews cite at least three sources, and a trio of domains — Wikipedia, YouTube and Reddit — accounts on its own for roughly 15% of cited sources, ahead of government sites (~6%). AI engines like to cross-check before they assert.
Perceived authority matters just as much. Within Google's E-E-A-T framework, Trust is named as the most important element. For an AI, citing a credible brand is safer than citing an unknown source, because it limits the risk of spreading false information.
The role of third-party mentions (Reddit, Wikipedia, the press)
Your website is not the only source the AI consults. A Semrush study (2025) covering 230,000 prompts and more than 100 million citations shows that Reddit and Wikipedia are among the domains ChatGPT cites most. Concretely, being mentioned positively on forums, encyclopedia pages or in the press strengthens your chances of being picked up.
- Forums and communities (such as Reddit): authentic opinions there are frequently cited as social proof.
- Encyclopedias and reference databases: an accurate Wikipedia entry feeds the models' "memory".
- Press and specialist media: credible editorial coverage acts as an authority signal.
Keep in mind: AI engines are not infallible. Columbia's Tow Center (2025) found that AI search engines get more than 60% of source attributions wrong. Providing clear, dated, easy-to-verify information reduces the risk of being miscited — or of your facts being attributed to a competitor.
How should you structure content to get cited (actionable method)?
By making your content easy to cite: headings phrased as questions, a self-contained answer paragraph under each heading, lists and tables, and above all sourced facts. The foundational Princeton paper measured that the most effective methods revolve around evidence: adding source citations, expert quotes and statistics.
This is the single most useful result to remember. According to Aggarwal et al. (KDD 2024), applying these methods can increase a piece of content's visibility in generative answers by up to +40%. Adding source citations, expert quotes and precise statistics are among the highest-performing levers identified on their benchmark.
Structure for the machine
Question-style headings, a 40-to-60-word answer paragraph right below, lists and tables. Scannable content is citable content.
Build your authority
Identified author, real expertise, accurate content. Trust, in Google's E-E-A-T framework, is the most decisive signal.
Be where AI reads
Presence on the sources they consult: reference pages, forums, press, credible directories in your industry.
Provide facts
Dated figures, named sources, expert quotes. Factual data points are the elements models reuse most.
Cultivate mentions and reviews
A brand cited positively by third parties (reviews, forums, media) is easier for an AI to recommend than a silent one.
Guarantee technical access
AI crawlers allowed, content readable without JavaScript, fast pages. If the bot cannot read your page, it cannot cite you.
Technical access in practice
Before any editorial optimization, make sure AI crawlers can read your pages (check your robots.txt), that the essential content renders without JavaScript, and that the HTML structure is clean. The llms.txt file is an emerging, non-mandatory convention that can help guide bots to your key pages.
Good news on the Google side: there is no magic schema to install. Google officially confirms that no structured data or special schema.org markup is required to appear in AI Overviews. And if you do use structured data, it must match the visible content of the page.
How do you get cited specifically by ChatGPT, Gemini and Perplexity?
Each engine has its own logic. ChatGPT (and its SearchGPT search) blends training memory with the live web. Gemini and AI Overviews lean heavily on Google's index. Perplexity is first and foremost a real-time citation engine. The table below sums up how to adapt your work to each.
| Engine | What makes it different | GEO priority |
|---|---|---|
| ChatGPT / SearchGPT | Training memory + live web; often cites reference sources and forums | Presence on the sources it consults (Reddit, Wikipedia, media) + factual content |
| Gemini & AI Overviews | Built on Google's index; AI Overviews cite several sources on average | Solid SEO + people-first content, no special schema required |
| Perplexity | Real-time citation engine; shows numbered clickable sources | Freshness, clear structure, verifiable and well-sourced facts |
The Gemini special case: according to Strauss et al. (2025), Gemini provides no clickable source in roughly 92% of its answers. So the goal is not always to win a link: it is to get your brand mentioned in the text, even without a clickable link. Named awareness beats the click.
How do you know if it is working?
By measuring, because you can only steer what you measure. Three indicators matter: your citation rate (how often the AI mentions you), your position in the answer (cited first or in passing) and your share of voice against competitors. Without that tracking, GEO remains a hunch you cannot act on.
The problem is that every assistant answers differently, changes often, and never warns you when it starts or stops citing your brand. Manually testing your customers' real questions on ChatGPT, Gemini, Claude, Perplexity and Grok is doable once, but unmanageable over time.
That is exactly what GEO console, the "search console for AI", does: it automates that test across all these engines and tracks over time whether, where and how your brand is cited, plus your share of voice against competitors. For the full method, read our guide to measure your AI share of voice, and see how to track your AI citations.
GEO is iterative work: you structure your content, measure the citations, identify the questions where you are absent, then fix. Without measurement, you cannot tell which action worked — or on which engine. Measurement turns GEO from a bet into a discipline you can manage.
Sources
- Aggarwal et al., "GEO: Generative Engine Optimization", KDD 2024 (Princeton, IIT Delhi, Georgia Tech, Allen AI).
- Strauss et al., study on Gemini citations, arXiv 2508.00838, 2025.
- Tow Center for Digital Journalism, Columbia, "We compared eight AI search engines", 2025.
- Gartner, prediction of a ~25% drop in search volume by 2026, 2024.
- Google / Alphabet, Q1 2025 results (~1.5B AI Overviews users), 2025.
- OpenAI / TechCrunch, ChatGPT at ~800M weekly active users, 2025.
- Perplexity / TechCrunch, ~780M queries per month, 2025.
- Pew Research Center, clicks and sources of AI summaries, 2025.
- SparkToro / Datos, 2024 zero-click search study.
- Ahrefs, AI citations / Google top 10 overlap and AI Overview citations, 2025.
- Semrush, most-cited domains in AI answers, 2025.
- Google Search Central, AI features, succeeding in AI search and E-E-A-T, 2025.
Frequently asked questions
GEO or SEO: do you have to choose?
No, you don't have to choose. GEO extends SEO rather than replacing it. Solid SEO remains a useful foundation, especially for Google's AI Overviews and Gemini, which draw on search. GEO adds the citation and recommendation layer inside the AI's answer, on engines like ChatGPT and Perplexity where Google rankings matter less.
How long does it take to get cited by an AI?
It depends on the engine and your starting point. Engines connected to the live web, like Perplexity or SearchGPT, can reflect new content within days to weeks. Models that rely more on their training memory move more slowly. Regular tracking lets you measure real progress instead of guessing.
Is an llms.txt file mandatory?
No, llms.txt is not mandatory and no engine requires it today. It is an emerging convention that can help guide AI crawlers to your most important content. What matters most is that your pages are accessible to AI crawlers, readable without JavaScript and clearly structured.
Does GEO work for a small business?
Yes. AI assistants cross-reference many sources: reference sites, forums, reviews, directories, local press. A small business can get cited thanks to precise, factual content on niche questions and solid third-party mentions, even without a big-brand budget. Specialization and clarity often matter more than size.
Do you need schema.org to appear in AI Overviews?
No. Google confirms that no structured data or special schema is required to appear in AI Overviews. Schema.org can help with other search features, but it is not a requirement. What counts is helpful, accurate, well-structured content; if you do use structured data, it must match the visible content.
More questions? See our full FAQ or the complete GEO guide.