For a long time, digital visibility was measured by Google rankings. If a website appeared in the top results for an important search, there was a good chance of attracting visits and generating business opportunities.
This principle still holds true, but the way people search is changing. Instead of analyzing a page of results, many users ask questions directly to Google and AI tools and expect an informed answer.
Now, the question is no longer just “where does my website appear in search results?”, but also “does AI recommend or mention my brand when someone searches for what I offer?”.
It is in this context that optimization for AI engines emerges , an approach that seeks to increase the likelihood of a brand being found, understood, and mentioned in the responses generated by artificial intelligence tools.
Table of Contents
1. Being well-positioned doesn’t guarantee being cited.
In AI research, the process is different from what is usually known. The tool interprets the question, searches for information in various sources, and creates an answer that gathers the most relevant data for that context.
This means that AI can use a service page, blog article, online communities, etc., and then select these sources and present them as references to support its answer.
Therefore, being in first place still helps, but it’s no longer the only condition for gaining visibility. Data from AirOps helps explain this change; according to them, 60% of citations in AI Overviews come from URLs that don’t appear in the top 20 organic search results.
In practice, this means that traditional positioning and presence in AI-generated responses are not exactly the same thing. For example, a company may be well-positioned for the generic search “running shoes,” but not be mentioned when someone asks “what is the best running shoe store for someone with knee problems?” or “where to buy custom running shoes in Porto?”.
This is precisely where optimization for AI engines becomes relevant, since a brand’s visibility also depends on how the information available online can be interpreted and used by these tools.
2. The “publish and forget” feature no longer works.
For years, many companies have created articles to answer a question, published them, and moved on to the next topic. The problem is that information that is useful today may no longer be relevant in two years, especially when prices, services, regulations, trends, or customer needs change.
In AI research, this update becomes even more important. Data from AirOps shows that pages that go more than three months without being updated are three times more likely to lose visibility in citations than pages that have been recently updated.
This difference is particularly relevant in business searches, where users are comparing options or close to making a decision; in these cases, approximately 83% of citations come from pages updated within the last year.
This doesn’t mean a company has to publish every day, but that it should monitor and update existing pages to ensure the information remains accurate, relevant, and aligned with the reality of the business.
Optimization for AI engines also involves ensuring that existing content continues to provide current, clear, and relevant information to the questions users ask.
3. Age does not determine the quality of the content.
The need for updates can lead some companies to make the opposite mistake, which is rewriting everything too frequently. There’s no need to replace a solid, well-written article just because it’s no longer recent.
What matters is understanding whether the information remains accurate, useful, and relevant to the search intent. An analysis by Ahrefs, cited by Digital Applied , helps put this issue into perspective; the study analyzed nearly 17 million URLs cited across seven AI platforms and concluded that the cited content was, on average, 1,064 days old, approximately 2.9 years, while the top 10 organic results were, on average, 1,432 days old, approximately 3.9 years.
These data demonstrate that the content cited by AI tends to be more recent, but it also disproves the idea that only content published a few months ago can gain visibility; the difference between the two groups was 25.7%, not several years.
Therefore, the timeliness of the content matters, but it shouldn’t be treated as a magic formula; an article published two or three years ago can still be an excellent source if it has accurate information, a clear structure, and relevant answers for users.
The real problem is the abandonment of content; a page loses value when it presents outdated data, services that no longer exist, obsolete examples, or information that no longer reflects the brand’s reality. Therefore, before creating another article, ask yourself if there are important pages that need updating.
4. Brand reputation is built outside the website.
A website is the center of a company’s digital communication, but it’s not the only place where its brand is evaluated. When AI tools search for answers, they may also take into account what other sources say about the company.
According to AirOps , approximately 85% of brand mentions in commercial searches originate from third-party domains. This happens because, in the initial research phase, AI tools frequently use comparison sites, lists, and specialized articles to determine if companies are recognized within a specific category.
For a Portuguese small and medium-sized enterprise (SME), this should be adapted to the reality of its sector and audience, namely through specialized directories, industry press, business associations, Google reviews, and also a presence in relevant Facebook groups.
An optimization strategy for AI engines should therefore consider not only what the company says about itself, but also the signals and references that exist about the brand on other platforms and websites.
5. Measuring only clicks is not enough.
When discussing visibility in AI-powered search, it’s natural to ask how many visits that presence generates. However, this metric no longer tells the whole story.
One reason is that AI-powered research directly answers many questions without requiring the user to visit any website. A study by the Pew Research Center , cited by Kevin Indig, observed that only about 1% of users clicked on quotes included in AI Overviews.
Furthermore, measuring this traffic is difficult; the same analysis indicates that 70.6% of the traffic referred by AI may arrive in Google Analytics identified as “Direct” because the source is removed before the visit is recorded. This doesn’t mean that clicks no longer matter; it means they should be interpreted in conjunction with other metrics and not as the sole indicator of success.
Imagine, for example, that someone asks an AI tool which are the best barbershops in Porto. Your company is mentioned, but the user doesn’t immediately click on the mention; days later, they might directly search for your company name, visit the website, or fill out a form. However, if you only analyze the clicks generated by the AI’s initial response, this influence might go unnoticed.
Therefore, a more useful metric is citation share, that is, how often your brand appears in questions relevant to the business, is correctly mentioned, and emerges among the recommended options.
6. SEO and AI should work together.
With the growth of AI research, new terms have emerged such as GEO (Generative Engine Optimization), AEO (Answer Engine Optimization), and LLMs (Large Language Models). These can be useful for describing the evolution of the market, but they should not distract companies from the essentials. GEO and AEO refer to the optimization of content for AI-generated answers, while LLMs are the models responsible for interpreting questions and producing those answers.
AI-powered search engine optimization does not replace SEO . AI-powered search does not replace SEO, it complements it. A website that is accessible, fast, well-structured, and understandable to search engines is still more likely to be found, interpreted, and cited.
A study by Semrush , conducted with 481 marketing professionals, concluded that only 22% have a fully integrated process between SEO and AI-powered search. Among the teams that work with both channels in a unified way, 81% reported more traffic or leads associated with AI platforms, compared to 36% of teams that manage them separately.
These data do not mean that there is a guaranteed formula for appearing in AI search results. Rather, they suggest that treating SEO and AI search as completely independent areas can make it difficult to create a coherent strategy.
In practice, a page must fulfill several objectives simultaneously: be technically accessible, answer search intent, present clear information, demonstrate expertise, and reinforce brand authority. The difference lies not in a secret formula, but in ensuring that the content strategy, technical SEO, digital reputation, and results analysis all align with the same goal.
So what can you do?
Researching with AI may seem like a complex change, but the first steps are quite practical.
- Start by identifying the most important pages on your website, especially those related to services, products, prices, comparisons, and content that generates leads.
- Review all pages older than 12 months and confirm that the data, examples, services, and calls to action are still accurate.
- Update first the pages that have the greatest commercial impact and those that are losing traffic, conversions, or visibility.
- Ensure that each page directly answers the main question in the first few paragraphs, without forcing the user to search for the essential information.
- Organize the content with a clear H1, subheadings in logical order, lists when useful, and sections that make sense even when read in isolation.
- Confirm that the website is accessible to search engines, returns functional pages, and does not use blocks that may prevent content preview.
- Strengthen your brand’s presence beyond your website through reviews, directories, partnerships, and content relevant to the industry community.
Artificial intelligence doesn’t create a reputation from scratch; it gathers signals and information online to build a response. When these signals are weak, outdated, or contradictory, it becomes more difficult for the brand to be recognized as a relevant option. Conversely, a clear, consistent digital presence validated by credible sources increases the likelihood of the company being mentioned when someone is specifically searching for the products or services it offers.
Want to know if your brand appears in the searches that really matter to your business? Talk to us .
