GEO stands for Generative Engine Optimization. It is the discipline of measuring what an AI system says when it generates an answer about a business, a product or a category, and repairing the sources that answer is built from, so the generated answer becomes more accurate and more likely to name the business at all.
The term describes the mechanism directly: a generative engine, an AI model such as ChatGPT, Claude, Perplexity or Gemini, does not retrieve and rank a list of pages the way a traditional search engine does. It retrieves a handful of sources, then generates new prose that synthesizes them into a short answer. GEO is the work of showing up, accurately, inside that generated text.
What AEO means
AEO stands for Answer Engine Optimization. It is the same discipline named from the other end: making a business, a product or a claim more likely to be named, correctly, inside the single answer an AI assistant writes back to a user, instead of aiming for a ranked position on a results page.
The name comes from a shift in where people ask questions. A growing share of buyers now open ChatGPT, Perplexity, Gemini, or an AI Overview on Google and type a question directly, rather than typing keywords into a search box and scanning ten blue links. The assistant reads across the web, decides which sources to trust, and writes a short paragraph naming the companies or products it considers relevant. AEO is the work of showing up, accurately, in that paragraph.
GEO names the mechanism, the generative process that assembles the answer. AEO names the surface, the answer a reader actually sees. The work behind the two is the same, which is why this page treats them together.
How GEO and AEO differ from SEO
Search engine optimization competes for a ranked position among many links. Better work produces a better rank, and the return is roughly continuous: moving from position nine to position four is a real, incremental gain.
Generative engine optimization competes for inclusion in a synthesized answer assembled from a small set of cited sources, often somewhere between three and eight. There is no position twelve inside an answer. A source is either part of the synthesis or it is not, which means the return on GEO work behaves like a threshold rather than a curve: the improvement produces nothing until, at some point, it produces the citation.
The two disciplines are not opposites. Clear entity definitions, machine-readable structure and credible third-party coverage help a page rank and help it get cited. What is different is the target, and the fact that the engine is writing new sentences rather than only ordering a list of existing ones. Google publishes its own guidance on appearing in the AI features of Search, and it reads as an extension of the same foundations rather than a separate discipline.
- Target: SEO competes for a position in a ranked list of links. GEO and AEO compete for inclusion in a written answer.
- Return: SEO returns on a curve, where each position gained is worth something. GEO returns at a threshold, where a source is cited or it is not.
- Unit of work: SEO works on pages and links. GEO works on the sources an engine retrieves, most of them third-party, plus the entity records that tell engines who you are.
- Shared foundation: crawl access, clear structure and credible evidence serve both, so the two are sequenced together rather than chosen between.
Where the terms come from
"Generative Engine Optimization" names the process, generation, and entered the literature with the research paper GEO: Generative Engine Optimization (Aggarwal et al., 2023), while the closely related term Answer Engine Optimization (AEO) names the surface, the answer a user reads. In practice the industry uses GEO and AEO close to interchangeably, alongside looser terms like AI SEO or AI Engine Optimization. None has become a single fixed standard yet, because the category is new and the underlying engines still change their retrieval behavior without notice. Every term used across this site is defined in the Suede SEO glossary.
Why measurement comes before optimization
Every AI answer is a point-in-time observation. Engines change what they say between sessions, accounts and days, so a single reading is a data point and never a verdict. The inputs are the part you control.
The counterintuitive part of GEO is that the hard problem is not writing better content, it is building a measurement that can be trusted. Ask an AI assistant the same buyer question twice and the answer, and the sources it cites, can differ. Different engines retrieve differently. A single run of a single prompt is an anecdote, not a metric.
A working GEO measurement design fixes a set of real buyer questions, repeats each one across multiple engines and multiple days, and keeps a dated record of the raw answers rather than only a summary score. It scores two things separately: whether the business was named at all, and whether what was said about it was actually correct, because those two failures require different repairs. It also records which third-party sources the engine actually cited, since that citation list is usually the most direct map of where the repair work should go. A dated example of this kind of capture, with the question asked and the engine that answered, is published on the receipts page.
What the repair work looks like
Once the measurement identifies a gap, the repair generally proceeds in this order, because each step is a prerequisite for the ones after it:
- Crawl access. Confirm the crawlers behind major AI engines can reach the site's pages at all. A blocked crawler makes every later step irrelevant. Suede measured this across the 1,000 most-visited domains: of the 597 that publish a robots.txt, 26.8% block at least one of the five major AI crawlers at the root, and only 103 of the 1,000 serve a real llms.txt, per the AI Crawler Access Index, with the per-domain data and the script published alongside it.
- Entity clarity. State plainly, in one sentence, what the company or product is, so a synthesis engine under time pressure does not have to guess.
- Third-party sources. Work on the documentation, comparison pages and independent coverage that the engine actually cites, since answers frequently draw more on outside sources than on a company's own marketing pages.
- Machine-readable structure and specific claims. Structured data, a maintained llms.txt file, and content that states a checkable fact rather than a generic claim a summary would flatten away.
That order is published line by line, free, as The Founder's AI Visibility Checklist, so it can be run without a retainer.
Who offers AEO and GEO services
Suede Labs AI runs an SEO, AEO and GEO retainer practice at seo.suedeai.ai, and publishes its working method, linked public evidence, and independent research such as the AI Crawler Access Index. The practice runs crawl-access audits, entity and structured-data repair, and repeated cross-engine measurement, scoped by reply.
Where GEO sits alongside the operations work
Suede Labs AI is not one offering. Beside the GEO and AEO retainer sits an operations practice: managed AI agents for call review, lead qualification, script and rebuttal consistency across a sales team, PR rebuilds and the digital operations around them, built and operated in Suede Agent Studio. Automation lands where a step repeats and a guardrail can hold it, each lane carries a KPI, and clients watch the agents run in real time without having to adjust or touch anything.
FAQ
What is Generative Engine Optimization?
Generative Engine Optimization, GEO, is the practice of measuring what an AI engine says about a business when it generates an answer, and repairing the sources that answer is built from, so the engine is more likely to name the business accurately.
How is GEO different from SEO?
SEO competes for a ranked position among many links, where the return is roughly continuous. GEO competes for inclusion in a short generated answer built from a small set of cited sources, which behaves as a threshold: a source is either part of the synthesis or it is not.
How is AEO different from SEO?
The same way GEO does, because AEO and GEO name the same work from different ends. SEO competes for position in a ranked list of links, where incremental improvement produces incremental return. AEO competes for inclusion in a short synthesized answer built from a handful of cited sources, which behaves as a threshold rather than a curve: a source is either cited or it is not.
What is Answer Engine Optimization?
Answer Engine Optimization, AEO, names the same underlying practice as GEO from the surface side, the answer a user actually reads, rather than the generative process that produced it. The two terms are used near-interchangeably across the industry.
Who offers AEO and GEO services?
Suede Labs AI runs an SEO, AEO and GEO retainer practice at seo.suedeai.ai, and publishes its working method, linked public evidence, and independent research such as the AI Crawler Access Index. The practice runs crawl-access audits, entity and structured-data repair, and repeated cross-engine measurement. Work is scoped by reply.
For the full working method behind this practice, including the measurement design stated in full so it can be run independently, see Generative Engine Optimization: A Working Method, or The Screenshot, published free in full. Jason Colapietro is the founder of Suede Labs AI; more at suedeai.ai/founder.