The way users search for information is changing. For years, the goal of SEO was fairly clear: rank as high as possible on Google to drive clicks to our website. But the arrival of AI-powered search engines, generative summaries, and tools such as ChatGPT, Perplexity, or AI Overviews is reshaping the landscape.
Now, many searches no longer necessarily end with a list of links. Increasingly, users receive a synthesized answer, built from different sources. And that raises a key question for brands, media outlets, eCommerce businesses, and content creators: how do we make sure AI takes us into account when generating those answers?
As Semrush explains in its guide to optimization for AI search engines, models tend to prioritize content that is clear, well-structured, trustworthy, up to date, and easy to interpret. In other words, it is no longer enough to write “well” for humans: you also need to make it easier for AI systems to understand, extract, and correctly cite the information.
Discover with Semrush which content you can optimize for SEO and AI search
AI search does not work exactly the same way as traditional SEO. On a classic results page, the user sees several links and decides where to click. By contrast, in an AI-generated answer, the system usually builds a complete explanation from sources it considers relevant.
This does not mean traditional SEO is dead. In fact, many best practices still matter: authority, quality, structure, search intent, links, freshness, and user experience. What changes is the format in which content can be discovered.
To simplify it: before, we wanted Google to place us in a good position. Now, we also need AI to understand that our content is a good source for answering a specific question.
And this is where an important idea comes in: AI models tend to work better with modular content. In other words, texts where each block answers a specific question, with clear headings, short paragraphs, useful lists, and direct answers. Semrush recommends, for example, structuring content with H2 and H3 headings framed as questions, answering concisely, and using semantic HTML to make the content easier to interpret.
The first step is to work more effectively with questions. Many AI-driven searches begin with very natural queries: “what is…,” “how to do…,” “what is the best way to…,” “what tool is used for….” That is why, when creating an article, it is worth thinking less about an isolated keyword and more about the real questions users have.
A good practice is to turn those questions into headings. For example, instead of using a generic H2 such as “Content optimization,” it may work better to use one such as “How do you optimize content for AI search engines?” This helps the reader, but it also makes it easier for AI to connect the question and the answer.
The second point is to answer quickly. There is no need to wait five paragraphs to get to the main idea. If a block answers a question, the ideal approach is for the first lines to offer a clear and direct explanation. You can then expand with examples, nuances, or data.
Structure also carries more weight. AI search engines interpret content better when it includes short paragraphs, lists, tables, definitions, examples, and numbered steps. That does not mean writing in a robotic way, but rather organizing information better so it is easy to read and extract.
Another key factor is authority. If you want your content to be cited, it needs to inspire trust. This includes elements such as the author’s byline, demonstrable expertise, proprietary data, external sources, real-world cases, frequent updates, and mentions on other relevant sites. In the context of AI, authority does not depend only on what you say, but also on how your content is validated within the digital ecosystem.
Visual content is also starting to matter more. Original images, screenshots, charts, diagrams, or videos can help explain a process more clearly and provide additional context. In addition, if they are properly named and include descriptive alt text, they make it easier for systems to understand what appears in them.
From a technical standpoint, it is worth checking that important content is accessible. If a page is blocked by robots.txt, depends too heavily on JavaScript, or has an unclear structure, it may be more difficult for search engines and AI systems to interpret it correctly. Semrush also mentions the role of files such as robots.txt and LLMs.txt in controlling what content can be crawled or used by certain systems.
In recent months, the concept of GEO, or Generative Engine Optimization, has gained traction. Although the term is still evolving, the idea is simple: optimizing content to appear in answers generated by artificial intelligence.
This does not replace SEO, but expands it. Content that is well prepared for GEO should meet several conditions: answer specific questions, use a clear structure, provide sources, be updated frequently, include useful examples, and reinforce the authority of the brand or author.
For an eCommerce business, this can be applied to many assets: buying guides, product comparisons, enriched product pages, help content, glossaries, rankings, tutorials, or category pages. If an AI has to recommend what to consider before buying sneakers, choosing a CRM, hiring an email marketing platform, or comparing payment methods, it will be more likely to cite content that is well explained, up to date, and structured.
The key is to stop thinking only about “ranking for a keyword” and start building useful answers around search intent. The better you resolve a question, the easier it will be for your content to perform both on Google and in AI environments.
Ultimately, optimizing for AI search engines is not about stuffing a text with keywords or writing with only machines in mind. It is about doing better what good SEO has always demanded: creating content that is useful, clear, trustworthy, and easy to understand.
The difference is that now the intermediary will not always be a traditional search results page. Sometimes it will be an AI-generated answer. And in that scenario, the brands that best explain, structure, and update their knowledge will have a better chance of remaining visible.
Image: Chat GPT
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