What Is GEO? The Discipline of Being Considered When AI Answers
By Pedro Sonda, dooop
GEO (Generative Engine Optimization) is the set of practices aimed at increasing the likelihood that a company, brand, or content is found, understood, used, and cited by AI systems that generate answers, such as Google AI Overviews, AI Mode, ChatGPT, Gemini, Claude, and Perplexity.
The difference compared to traditional search is simple to state: in SEO, the company competes for a position in a list of links; in GEO, it competes for a place within an already prepared answer. When a director asks an AI "which consultancies help structure AI governance?" they receive a text that synthesizes alternatives, criteria, and recommendations. Those not included in this synthesis, in practice, were not considered.
Updated in October 2026.
Short answer: what is GEO
GEO is the discipline of making a company eligible, understandable, and defensible in AI-generated answers.
- Eligible: the content can be accessed, crawled, and retrieved by the systems assembling the answer.
- Understandable: the AI correctly understands who the company is, what it does, and for whom.
- Defensible: there is evidence, both proprietary and third-party, that allows the AI to justify including the company.
The term was formalized in the academic article GEO: Generative Engine Optimization, by researchers from Princeton University and IIT Delhi, among other authors, published at the KDD 2024 conference. The authors describe GEO as a paradigm to help content creators improve the visibility of their content in generative engine answers (Aggarwal et al., arXiv).
Why GEO became important for companies
The reason is behavioral: a growing portion of decisions starts with an answer, not a list of links.
| Evidence | What it shows | Source |
|---|---|---|
| ChatGPT with 900 million weekly active users (Feb. 2026) | Conversational AI became a mass research channel | TechCrunch |
| Google’s AI Mode with over 1 billion monthly active users (Jul. 2026) | Generated answers are already part of common Google search | |
| Users who saw an AI summary clicked traditional results in 8% of visits, versus 15% for those who did not | Generated answers reduce navigation to websites | Pew Research Center |
The Pew data was measured with 900 adults in the United States in March 2025 and should not be read as a universal rule. But the management implication is direct: if part of the evaluation happens inside the answer, the visibility that matters is presence in that answer, not just the click after it.
How GEO works in practical terms
A generative engine typically does three things when responding: interprets the question, searches for information (in its own index, on the web, or both), and writes a synthesis, sometimes with links to sources. Google, for example, states that AI Overviews and AI Mode may use the query fan-out technique, which triggers multiple related searches on subtopics to build the answer (Google Search Central).
This changes what it means to "appear":
- The AI evaluates snippets, not just entire pages.
- The original question becomes multiple subquestions, so content can be useful to the answer even if it is not the top result for the exact phrase.
- The answer is probabilistic: the same question can generate different lists each time. A SparkToro study with Gumshoe, analyzing about 2,961 runs of 12 prompts on ChatGPT, Claude, and Google AI, found less than a 1 in 100 chance that ChatGPT or Google AI repeated the same brand list (MediaPost).
Implication: GEO is not managed by "ranking." It is managed by frequency of presence across a set of relevant questions, measured over multiple runs. Detailed operation is explained in What is Generative Engine Optimization?.
Is GEO different from SEO?
Yes, but it is not the opposite of SEO.
| Dimension | SEO | GEO |
|---|---|---|
| Unit of competition | Page in a list of results | Snippet, entity, and argument within an answer |
| Management question | What position do we appear in? | Are we included, well described, and justified? |
| Main metric | Position, clicks, traffic | Presence by intent, citation, accuracy of description |
| Terrain | Mainly the company’s own website | The website and the ecosystem of sources about the company |
| Technical base | Crawling and indexing | The same base, which remains mandatory |
The technical base is shared. Google states there are no additional requirements to appear in AI Overviews or AI Mode: the page must be indexed and eligible to appear in search with a snippet (Google Search Central). In other words, without technical SEO, there is no GEO; but having SEO does not guarantee GEO. The full comparison is in Is GEO the new SEO?.
The thesis: GEO is about consideration, not ranking
Most explanations about GEO focus on content formats: lists, FAQs, data, citations. These elements help, and the Princeton study showed that adding source citations, statistics, and textual quotes increased content visibility in their experiment (Aggarwal et al.). But format is only part of the problem.
For a company, the real problem is consideration: when someone asks for a recommendation, the AI builds a set of alternatives. The company needs to be in that set and there must be verifiable reasons for it. An Ahrefs study with 75,000 brands found a correlation of 0.664 between brand mentions on the web and presence in AI Overviews, stronger than the correlation with backlinks (0.218) (Ahrefs). This is correlation, not causation, but points in the same direction: AI tends to reflect what the information ecosystem says about the company, not just what the company says about itself.
dooop framework: the 7 questions of AI visibility
At dooop, we use seven questions to diagnose a company’s position in AI-mediated decisions. They organize GEO as a management problem, not a list of tactics.
| # | Question | What it reveals |
|---|---|---|
| 1 | Identity: Does the AI know who we are? | Whether the company description is correct and consistent |
| 2 | Relevance: Does the AI understand which problems we solve? | Whether the company is associated with the right problems |
| 3 | Discovery: Are we found when those problems are searched? | Presence in queries without the company name |
| 4 | Consideration: Do we enter the set of alternatives? | Presence in recommendation and choice queries |
| 5 | Competition: Who appears instead of us? | Competitors and sources occupying the space |
| 6 | Evidence: Can the AI justify our presence? | Strength of proprietary and third-party proof |
| 7 | Authority: Are we a source or just a mentioned company? | Whether the company’s content is used to explain the topic |
A company can perform well in Authority and poorly in Consideration: the AI uses its articles to explain the subject but does not recommend it. This is an actionable diagnosis, which is why a single "visibility" index hides too much information.
How to prepare a company for generative engines
Preparation follows a logical order. Skipping steps usually generates effort without effect.
- Ensure technical access. Important pages must be crawlable and indexable. For ChatGPT, OpenAI states that sites blocking the OAI-SearchBot do not appear in search answers (OpenAI).
- Make the entity unequivocal. Name, offer, audience, location, and differentiators described consistently on the website and external profiles.
- Organize content by intent. Each important page should answer a set of related questions well, in snippets that make sense independently.
- Build evidence. Data, cases, methodology, and third-party mentions that support what the company claims.
- Measure by intent. Define the questions that matter to the business and monitor presence across multiple runs and platforms.
The step-by-step is in How to make a company appear in AI answers.
What GEO is not
- It is not a guarantee of citation. Answers vary by platform, question, time, and context. No technique ensures presence.
- It is not writing for robots. Keyword stuffing performed worst among methods tested in the Princeton study (Aggarwal et al.).
- It is not a magic file. Google states there is no need to create text files for AI or special schema to appear in its AI features (Google Search Central).
- It is not just content. Identity, evidence, and presence in third-party sources weigh as much as website text.
What to do with this information
- If your company sells to decision-makers who research before talking to suppliers, GEO is already part of your funnel. The first step is to know how AIs describe you today.
- If you already invest in SEO, leverage the technical base and add the missing layer: measurement by intent, entity consistency, and third-party evidence.
- If you don’t know where to start, begin with questions 1 and 4 of the framework: does the AI know who you are? Does it include you when someone asks for a recommendation in your market?
To understand where your company stands today in these seven dimensions, see how a dooop AI visibility diagnosis works.
Frequently Asked Questions
Are GEO, AEO, and LLMO the same thing? They are similar names for overlapping practices. AEO (Answer Engine Optimization) emphasizes direct answers; LLMO (LLM Optimization) emphasizes language models. GEO is the term with formal academic origin and covers engines that generate answers from sources.
How long does GEO take to show results? There is no guaranteed timeframe. Technical changes can be noticed as soon as content is crawled again; reputation changes and third-party mentions take longer. Therefore, monitoring should be done by periodic measurement, not by expected dates.
Is GEO useful for B2B companies? Yes, and it is often more critical in B2B because questions like "which company to hire for X" involve supplier comparison, exactly the type of question where AI builds a set of alternatives.
Also read
- How to measure AI Visibility: metrics that show where the brand wins and loses in AI answers
- What is Generative Engine Optimization? Origin, mechanism, and what research really shows
- Is GEO the new SEO? What changes, what remains, and where to invest
About dooop
dooop is a consultancy based in Caxias do Sul (RS) that prepares leaders and organizations to transform artificial intelligence into business capability through strategy, governance, and training. This article is part of dooop’s series on GEO and AI Decision Infrastructure.