What Is AIO? What to Do, and What Google Says You Can Skip (2026)
What AIO (AI optimization) means and how to approach it. This guide separates the tactics Google explicitly calls unnecessary — AI-specific markup, llms.txt, chunking content — from those with controlled-experiment support, and adds our own test of whether AI can relay official company information correctly across 100 question patterns.
Key takeaways
- AIO means preparing your information so that it appears in AI-generated answers in the correct form. The work is not about raising a ranking but about getting inside the answer itself
- Google states in its official guidance that no AI-specific markup and no llms.txt file are required. Several tactics still circulating in the field contradict that guidance
- Exposure is only half of it. When we asked five major AI services about companies' official policies, only 60.0% of the answers were correct
What AIO means
Preparing your information so that when a generative AI assembles an answer, your company appears among the candidates and is quoted accurately. AIO stands for AI Optimization, and is also used to mean optimizing for Google AI Overviews specifically.
Traditional SEO aims at appearing high in a list of results. AIO aims at appearing inside the answer. A search results page lists ten links, so ranking fifth still earns clicks, whereas an AI answer usually narrows to about three candidates. Miss that shortlist and you are functionally invisible.
There is a second consideration that SEO never had. Appearing in an answer does not mean the content is correct. AI assembles answers by cross-checking several sources, so when your official information is not machine-readable, the gaps get filled with outdated pages or third-party descriptions. Exposure and accuracy have to be treated as separate problems.
The full model of the discipline is in our overview of LLMO. This article is for readers arriving from the term AIO, and it sorts out what to do and what to skip.
AIO is used with two different meanings
The term has two usages, and article content shifts depending on which one the author means. One is AI Overviews Optimization, covering Google's AI answer panel in search results. The other is AI Optimization, covering AI systems in general including ChatGPT and Perplexity.
This article takes the second meaning. Most of the tactics overlap, but where you measure changes. For the terminology itself, see how GEO, LLMO, AIO and AEO relate.
Why AIO matters now
The arrival of AI answer panels has measurably reduced clicks from search results to websites.
Pew Research Center reported in July 2025 that when an AI Overview appeared, organic results were clicked in 8% of searches, against 15% when no AI Overview was present. Roughly half. The citation links inside the AI Overview were clicked about 1% of the time.
Ahrefs measured the drop in click-through rate for the top-ranking result at 58% when an AI Overview is present. The same company reported 34.5% in April 2025, so the effect grew substantially over roughly eight months.
Japan shows the same pattern. Browser log analysis found that the share of Google searches leading to a site visit fell to 41.1% in 2025. Generative AI usage in Japan reached 51% as of February 2026, nearly double the 27% recorded a year earlier, and Google only began offering AI Mode in Japanese in September 2025. The shift is early rather than settled.
What Google says you can skip
AIO articles often list dozens of tactics, and some of them are things Google has explicitly stated are unnecessary. Sorting this out has to happen before any budget is allocated.
| Commonly listed tactic | What Google states | What it is actually for |
|---|---|---|
| Add AI-specific structured data | There is no special schema.org markup to add for generative AI search | Rich results in search. Verifying consistency with your product feed |
| Publish an llms.txt file | There is no need to create one. Google Search does not use it | Publishing it costs little, but it is not a core tactic |
| Chunk your content | There is no need to split content. AI can extract the relevant part from a page covering several topics | Only when splitting helps the reader |
| Rewrite copy for AI | No special rewriting is required. Existing SEO best practices continue to apply | As a readability improvement |
In its guidance for AI features on Search, Google explains that generative AI features are rooted in the core Search ranking and quality systems. Existing SEO practice therefore continues to operate as a precondition.
If you're already following our image SEO best practices and video SEO documentation, you're already optimizing for generative AI search.
The same guidance states that there is no special schema.org markup to add for generative AI search, that creating an llms.txt file is unnecessary, and that content does not need to be chunked, because AI can extract the relevant portion from a page covering multiple topics.
Structured data still drives rich results in search, and Google itself recommends Merchant Center feeds for product information in AI answers. It simply is not a lever for increasing AI citations.
How to implement structured data for an online store, and for which purpose, is covered in our structured data guide.
What actually works
Once the unnecessary items are removed, what remains are the tactics with controlled-experiment support. There are three.
The first is working statistics, figures and sources into the body text. The GEO paper presented at KDD 2024 by a research team including Princeton compared nine rewriting strategies across 10,000 queries and found that adding statistics, adding citations and stating sources raised visibility in generative engines by up to 40%. AI favors claims backed by verifiable evidence, so placing that evidence in a machine-extractable form pays off.
The second is headings that answer the question directly. Ahrefs found a 41% citation rate for pages whose headings answer questions directly, against 29% for pages with vague headings. AI treats the passage immediately below a heading as the unit of extraction, so separating the heading from the answer makes the page harder to pick up.
The third is being technically retrievable. Major AI crawlers such as GPTBot and PerplexityBot do not execute JavaScript and read only the HTML that comes back. On a page where price, stock or specifications are rendered by JavaScript alone, the content effectively does not exist. Our article on GEO for e-commerce covers this with measurements.
Can AI relay your official information correctly?
This is the second consideration, separate from exposure. Your company name appearing in an answer does you no good if what follows is wrong.
We ran a study putting questions about the return and warranty policies of five electronics retailers to five major AI services. Across four scenarios covering returns and initial defects, extended warranties, point refunds and warranty repairs, the test produced 100 question patterns.
Measured against the official information, 60 answers (60.0%) were correct. Twenty-five were wrong and fifteen produced no usable answer. Of the incorrect answers, fifteen described return windows or extended warranty terms as more generous than the official policy, which would cause real problems if used in customer communication.
The handling of sources was worse. Sixty-two answers cited a URL that did not exist, was unofficial, or belonged to a different brand. For Microsoft Copilot, 19 of 20 answers (95.0%) had a problem with the source. Accuracy rate alone does not capture how safe an answer is.
The implication is direct. Before increasing exposure, confirm that your official information is machine-readable and unambiguous. When pricing or terms contradict each other across your own pages, AI cannot judge which is correct and treats you as a candidate it is not confident about.
Five checks you can run today
None of these require tooling.
Ask the major AI services about your own company. In a temporary chat (the mode that ignores history and memory), ask ChatGPT and Gemini about your company and service, then check whether the answer matches the facts
Open a page with JavaScript disabled. Turn off JavaScript in your browser settings and see whether pricing, terms and conditions still appear
Check for contradictions across your own pages. Compare the numbers on your pricing page, your FAQ and your terms of service
Check that pages carry a date. A page that gives no indication of when the information applies is one AI has reason to avoid
Open your robots.txt. Visit yourdomain/robots.txt and check whether AI crawlers such as GPTBot and OAI-SearchBot are blocked wholesale
Whichever check fails is where the work starts.
How to work through it
The steps depend on each other, so they run bottom-up.
Done when AI answers to your key questions, and whether they are correct, are on record
Done when AI crawlers are not blocked and key information reads without JavaScript
Done when pricing, terms and durations agree across your own pages
Done when claims carry statistics and sources in the body text, with the date stated
Done when the same metric has been recorded two months running
The first two steps are technical and the rest are editorial. Most companies start at step three, and it does not pay off while step two is missing.
How to measure it
The available instrumentation changed over the past year.
Google announced generative AI performance reports in Search Console on 3 June 2026. It is the first official data separating impressions in AI Overviews and AI Mode from ordinary organic search. Only impressions are available for now, with no clicks, click-through rate or query data. Data begins on 18 May 2026 with no backfill. Availability has been rolling out in stages, so open your own property to see what is present.
For AI systems other than Google, no official instrumentation exists. The practical approach is to define around twenty questions your prospective customers would plausibly ask, run them in a temporary chat on each AI service several times, and record whether you are mentioned, in what position, which sources are cited, and whether the content is accurate.
Referrers frequently do not carry through, so the sessions land in "direct". Without a configuration that separates ChatGPT and Perplexity into their own channel, you will systematically undercount the results of your work.
Frequently asked questions
In practice they refer to nearly the same work. AIO tends to be used in the context of Google's AI answer panel, while LLMO is the general term that took hold in Japan. The tactics overlap substantially.
For the purpose of increasing AI citations, no effect has been demonstrated. It remains effective for rich results in search and useful for verifying consistency with a product feed. Separate the purposes.
Whether an AI Overview appears depends on the nature of the query. Even where it does not, ChatGPT and Perplexity still generate answers, so the need does not disappear.
Clearing technical faults can change answers within weeks once pages are re-fetched. Third-party evidence accumulates over months. The timeline depends on which stage you are working.
The editorial work — consistency and explicit evidence — carries across. The technical path differs, since ChatGPT relies on its own crawler and the Bing index, so your Bing indexing status needs checking too.
The work you can do in-house costs nothing. Start with the five checks above, plus robots.txt and the JavaScript dependency. Criteria for selecting an agency are covered in a related article below.
Summary
The first move in AIO is not adding tactics but sorting them. Budget spent on work Google has explicitly called unnecessary does not produce results.
Three things remain: putting statistics and sources in the body text, writing headings that answer the question directly, and being technically retrievable. Each is backed by a controlled experiment or by platform documentation.
When you reach the point of considering outside help, our guide to four agency types and twelve questions to ask sets out the criteria.
Beyond that, look at accuracy rather than exposure alone. In our measurements, AI answered correctly about official company information 60% of the time. What is being said about you is something you have to ask to find out. We offer a free AI visibility assessment for retail and e-commerce businesses.
