What is AI search optimization?

What does “AI search optimization” mean?

AI search optimization is an umbrella phrase for making information about a business or topic easy for AI-powered search tools to find, understand and repeat correctly. Those tools include ChatGPT search, Google AI Overviews and AI Mode, Perplexity, Microsoft Copilot, and Claude when it searches the web.

We found no official definition of AI search optimization. No standards body we know of owns the phrase, and the companies that build AI search products use different words for the work, or avoid naming it at all. Treat any definition, including this one, as a working description rather than a rule.

For a small business, the practical goal is narrower than the jargon suggests. When someone asks an AI assistant about your kind of service in your area, or about your business by name, the assistant should be able to find you and get your details right.

Where did the term “GEO” come from?

“Generative engine optimization” comes from academic research. A paper titled “GEO: Generative Engine Optimization,” by Pranjal Aggarwal and colleagues, was first posted to arXiv in November 2023 and was later accepted to the KDD 2024 conference ^[2].

The GEO paper groups AI search tools under the label “generative engines”: systems that answer a question by gathering information from several sources and summarizing it with a large language model ^[2]. The authors propose GEO as a way for content creators to improve how visible their content is inside those generated answers, and they built a benchmark of test queries across many subject areas, called GEO-bench, to measure it ^[2].

The GEO paper reports that its methods improved visibility by up to 40% in its experiments, and that how well each strategy worked varied from one subject area to another ^[2]. That is a research result on a benchmark. It is not a promise about how any live product, such as ChatGPT or Google, will treat a particular website.

What do AEO, LLMO and the other terms mean?

Google’s own guidance spells out two of these acronyms: “AEO” stands for answer engine optimization and “GEO” for generative engine optimization, both terms used to describe work focused on improving visibility in AI search experiences ^[3]. Microsoft’s Bing team also uses the term, describing a new Bing Webmaster Tools report as an early step toward Generative Engine Optimization tooling ^[5].

Other labels circulate in marketing material, including LLMO (large language model optimization), “AI SEO” and “AI visibility.” We could not find a platform or standards body that formally defines these labels, so they are best read as near-synonyms used by different vendors.

Is AI search optimization just SEO?

For Google Search, Google’s answer is yes. Its guide to generative AI features says that optimizing for generative AI search is optimizing for the search experience, “and thus still SEO” ^[3]. Google’s page on AI features says no special optimizations are needed to appear in AI Overviews or AI Mode ^[4]. Google’s newer guide adds one site-level condition: the site must be included in Search generative AI features in Search Console ^[3], which Search Console says is the default setting ^[1].

The reason is how Google builds the features. Google says its generative AI features use retrieval-augmented generation, also called grounding, which relies on its core Search ranking systems to retrieve relevant, up-to-date pages from the Search index before a response is written ^[3]. A page that cannot be crawled or indexed is not available to be retrieved.

Google also lists tactics it says you can ignore for Google Search: llms.txt files and other special AI files, splitting content into tiny “chunks,” rewriting pages in a special style for AI, and adding special schema.org markup for AI ^[3]. Those points apply to Google Search only. Google itself notes that keeping an llms.txt file for other services that use one is fine ^[3].

Where does it overlap with traditional SEO, and where might it differ?

The overlap

• Crawl access: AI search tools need to reach your pages. Google lists allowing crawling in robots.txt, and by any CDN or hosting setup, as a best practice for its AI features ^[4].
• Indexing: to be shown as a supporting link in AI Overviews or AI Mode, a page must be indexed and eligible to appear in Google Search with a snippet ^[4].
• Plain text: Google advises making sure important content is available in textual form ^[4].
• Current business details: Google lists checking that your Business Profile and Merchant Center information is up to date ^[4].
• Original, useful content: Google’s guide says content people find unique, compelling and useful will likely influence presence in generative AI search in the long run more than any of its other suggestions ^[3].

The likely differences

Some things do look different, though the evidence here is thinner. An AI answer can draw on many pages at once. Google describes a “query fan-out” technique that issues several related searches across subtopics and data sources to build one response ^[4], so a page can support an answer to a question it was never written to rank for.

Success is also measured differently. Being cited inside an answer is not the same as being clicked. Bing’s AI Performance report, for example, counts citations, and Bing says those counts reflect how often pages are cited, not page importance, ranking or placement ^[5].

There are also more products to think about. Being visible in Google does not automatically mean being visible in ChatGPT, Perplexity, Copilot or Claude, and each company documents its search features separately. How AI assistants find local businesses compares what each one says.

Why is the terminology still unsettled?

AI search products are only a few years old, and they change quickly. The GEO paper itself describes generative engines as black-box and fast-moving, leaving content creators little control over when and how their content is displayed ^[2].

The companies involved frame the work differently, too. Google folds it back into SEO ^[3], while Bing names GEO as a direction for its webmaster tools ^[5]. Expect the vocabulary to keep shifting for a while.

For a business owner, the label matters less than the substance. If someone sells “GEO” or “AEO” services, ask what they will actually change on your website or listings, and how they will measure the result. Google suggests checking such advice against its guidance on third-party SEO help, and says no third-party tool has access to its internal ranking or AI systems ^[3].

No one can guarantee that a business will be included, cited or recommended in an AI answer. Google states that indexing and serving are not guaranteed, even for a page that meets every requirement ^[3].

What should a small business do with all this?

Start with the basics that serve both ordinary search and AI search, then check how AI tools currently describe you. SEO vs AI search optimization explains why those basics carry over, and the AI visibility checklist puts them in order.

Once the basics are in place, checking what AI knows about your business shows how to test the results without reading too much into a single answer.