Most advice on appearing in AI tools ends up being the same: write clearly, use schema markup, demonstrate your expertise, and so on. AI visibility optimization requires more than following these basic SEO practices, because AI tools evaluate and select information differently. This is not wrong, but it ignores the nuance of what tools like ChatGPT do when researching queries.
This guide provides a framework for optimizing AI visibility. It offers a brief overview of the research behind this advice and introduces a simple framework called CITE.
The Myth That Old SEO Practices Can Simply Be Adopted
The ability to acquire backlinks was the cornerstone of SEO for the last two decades. However, this theory appears to be entirely inadequate when it comes to AI-powered search. An analysis of 75000+ brands conducted by Ahrefs in December 2025 revealed a link-to-AI visibility correlation of only 0.22. By contrast, the same report found that mentions of a brand across the web had a much stronger correlation (0.66). In fact, mentions of a domain on YouTube specifically had the highest correlation of any factor investigated (0.74). Thus, brands that want to maximize their visibility in AI tools should prioritize mentions over backlinks.
Being Found Is Not Being Cited
One common misconception among many marketing professionals is that being found by an AI means being cited by it. Many fail to realize that there is a qualitative difference between a page being retrieved by a model and actually appearing as a citation.
A large-scale research study conducted by AirOps and published in March 2026 sheds light on this matter. The findings are based on the analysis of over 548000 webpages retrieved by ChatGPT when attempting to answer 15000 different queries. Remarkably, only 15% of these pages were ultimately cited in the responses. The remaining 85% did not make it to the final output despite being retrieved. Thus, a significant effort should be dedicated to improving a page’s chances of being actually cited rather than simply found.
The CITE Framework for AI Visibility Optimization
Instead of relying on vague lists, it may be useful to optimize for the specific factors highlighted by the research findings. This can be organised into a framework referred to as CITE, which consists of the following elements:
C: Clarity and Chunking for AI Visibility
AI language models tend to benefit from clear formatting and information that can be easily extracted. When optimizing for AI visibility, one should prioritize content that is structured in a way that facilitates this process. One practical way to achieve this goal is to make one’s answer immediately visible upon loading a page. To elaborate, it may be useful to use the first sentence or paragraph to address the query directly rather than describing the topic in general. In addition, it’s advisable to use numbered lists, tables, and similar elements when presenting one’s answer.
I: Identify Through Owned Content
A comprehensive study of 6.8 million citations from ChatGPT, Gemini, and Perplexity published by Yext in Q4 2025 revealed that 86% of AI citations came from sources controlled by the companies being cited. With that said, it is important to note that forums, social media posts, and other types of user-generated content were much less impactful than direct mentions on a brand’s own website.
Thus, when optimizing for AI visibility, one should prioritize publishing informative content on one’s own domain while maintaining existing pages in good condition.
T: Third-Party Trust
Although the value of direct mentions on one’s domain is difficult to overestimate, neglecting mentions elsewhere can prove to be a critical mistake. In fact, the findings suggest that most mentions come from independent publishers, which means that one should try to appear in as many of them as possible. A practical way to do that is to include one’s website in relevant lists, comparison articles, video descriptions, and other materials.
E: Everywhere Across a Topic
The ability to appear in responses to multiple questions about a particular topic is another important consideration when optimizing for AI visibility. A study conducted by Semrush and published in late 2025 demonstrates why this is the case. An analysis of 50000 domains revealed that only 15% of AI categories had clear leaders, meaning that in 85% of cases, no particular brand was significantly better at answering specific questions than its competitors.
One common mistake is to provide extensive details about one element of a topic while describing others in only one sentence.
Additionally, the Semrush findings indicate that there is no particular overlap between brands appearing in AI responses and domains being directly cited by AI tools. Thus, one should prioritize ranking highly in response to different questions about one topic rather than trying to appear in the answers to the same query.
A Few Common-Sense Examples
Assume that there are two web pages describing what a payroll tax is. The first page begins with a brief history of the company, its mission statement, and other general information before defining the term in question in paragraph 4. The second page, by contrast, begins with a clear definition and provides a short table with information about payroll tax.
An AI scanning these two pages will extract the data from the second one almost every time since it is much easier to identify and cite.
Common AI Visibility Optimization Mistakes
Effective AI visibility optimization requires avoiding the following common mistakes:
Trying to incorporate keywords without actually answering a query. Search algorithms benefit from keyword placement, but a language model will be unable to extract information from a poorly structured page regardless of its keywords.
Assuming that optimizing for AI is a one-time endeavor. Like traditional search, AI visibility relies on continuous improvements. One should revisit one’s efforts to ensure that they remain relevant to the latest developments.
The CITE Checklist
A quick reminder is in order before one proceeds to optimize for AI visibility. Whenever one edits a page, it may be useful to ask oneself the following questions:
➤ Does the first sentence or paragraph respond to the query or merely describe the topic in general?
➤ Is this information presented in clearly defined sections or paragraphs, rather than long, unfocused blocks of text?
➤ Does each section contain readily identifiable facts, figures, or other elements that can be directly extracted by an AI?
➤ Is there sufficient information to address every aspect of a particular topic, rather than only one or two elements?
➤ Would the response to a query benefit from being shortened to three sentences?
The Future of AI Visibility
ChatGPT and other similar tools are unlikely to scrape the entire web with every query. Research from Q4 2025 suggests that only 34% of ChatGPT queries, on average, originate from the live web, down from 46% in 2024. This means that an increasing number of responses are derived from the model’s training data.
In other words, one’s visibility in AI searches is no longer a short-term endeavor. Notably, Gartner predicted in 2024 that traditional search volume will decrease by 25% overall by 2026. The brands that continue to invest in SEO practices, particularly visibility in AI tools, will reap significant reward in the future.
Conclusion
Effective AI visibility optimization requires more than following vague SEO advice. The easiest way to improve visibility in AI tools is to structure your content into clearly defined sections containing specific facts, figures, and information that can be easily extracted and cited.
Most brands are being scanned by AI tools right now, but only a fraction are actually getting cited. The difference comes down to strategy. Xpo Outdoors helps businesses apply the CITE framework to their web presence, turning overlooked pages into trusted, citable sources across ChatGPT, Gemini, and Perplexity. Don’t leave your AI visibility to chance.