Search is changing and growing at lightning speed. Just look at how the quality of AI-generated content has skyrocketed over the past year. Even we, as digital specialists, can’t always tell real videos from AI ones. We hear everywhere: “Keywords and backlinks are a thing of the past. Forget about blue links. Forget about classic SEO. AI will eat your traffic.” But is that really the case? Let’s find out together!
So, AI Mode is entering the scene — a new approach to search engines that is already transforming how people get information and how companies get visibility in search results. In this article, we will look at how AI Mode works, why it is important for American companies, and what to do to avoid getting left behind in the pursuit of your customers.
What is AI Mode
AI Mode is a search engine mode that uses LLM, large language models, to generate responses to user queries based not only on individual pages, but on generalized information from multiple sources. In other words, instead of just showing you links, the system creates a new answer compiled from many pages at once.
AI Mode in Google began to appear in the form of SGE (Search Generative Experience) back in May 2024. Even then, it was clear that a fundamental transformation had begun in how search understands queries, interprets user intent, and selects sources.
AI Mode was first launched in the US and India, and is now available in 180 countries. To do this, simply go to the home page (google.com) and click on “AI Mode.” The only thing is that it currently only supports English, but we think localization is just around the corner.
We’ve noticed that when people click on search results using AI Overviews, those clicks are higher quality, meaning users are more likely to spend more time on the site.
Google Search Central
How AI Mode works
Of course, Google has published detailed documentation on how AI Overviews and AI Mode work, but we will try to present the information in a more concise manner.
AI Mode can be summarized in three key principles: search query distribution (Query Fan-Out), document corpus construction (Custom Corpus), and response generation using language models (LLM).
Step 1. Query Fan-Out — query distribution
In response to your search query, AI Mode is not limited to a single formulation. It searches for dozens of related keyword or phrase options that better cover the topic and anticipate the context that interests the user. This principle is called “query fan-out.”
For example, a user enters: “hosting for an online store.” The system simultaneously analyzes: “fast woocommerce hosting,” “wordpress hosting prices”, etc.
Step 2. Building a document corpus
After generating query options, the system selects documents from the index that may contain useful information and forms a “custom corpus” from them. This set does not necessarily include the most popular pages, but rather those that are most thematically relevant to the various query options.
The corpus includes forums with real reviews (local white and blacklists, Hotline.ua, DOU.ua, Reddit for foreign companies), articles with technical comparisons, and rating platforms.
Step 3. Generating a response via LLM
Based on the selected corpus, a large language model generates the response that the user ultimately sees. It is important to understand that this is not a copy from the website, but new text synthesized based on data from many sources.
So, Google has patented the “Pairwise Comparison Text Ranking Method.” The essence of this method is that you are compared directly with other sources fragment by fragment, rather than by absolute metrics.
The excerpt that the model considers more relevant will win, not just the one that contains more keywords. Information density, completeness, and semantic clarity become decisive.
Ultimately, the answer will look like this:
User personalization
Interestingly, the system stores not only content but also the user’s digital profile: which sites they visit, what topics they are interested in, and what types of responses they linger on. Accordingly, AI Mode matches the query to this profile and generates the most personalized responses possible.
Let’s look at an example. If over the last month a user has spent 70% of their time on English-language technical forums and blogs, AI Mode will raise GitHub and Stack Overflow to the top 5 sources for answers, even if local sites contain similar content.
How AI Mode changes SEO
Semantic relevance is more important than keywords. Content should be expert, unique, and thematically relevant, not just optimized for frequent queries.
Snippet optimization. Google analyzes not only the page as a whole, but also individual snippets. Each paragraph can be an “entry point” to the answer. Therefore, fewer descriptive constructions and redundancy mean a significantly higher chance of getting into the AI search results.
Loss of direct traffic. Although Google denies it, some traffic is indeed lost. The user receives the answer immediately in the search results, which increases the value of brand recognition, quality content, and a strong offer.
The emergence of new visibility formats. In AI Mode, links to the site can appear in the form of quotes, mentions, or a “read more at…” block. This opens up new opportunities for brands that have expert content.
| Traditional SEO | SEO in AI Mode |
| Keyword optimization | Semantic relevance to queries |
| PageRank rating | Evaluation of snippets and thematic clusters |
| Users come from links in search results | Users come from LLM responses |
Practical tips on how websites can get into Google’s AI search results
According to Google’s own advice, the basis for successful positioning in both traditional and AI search results is original, useful content (so-called “people-first” content).
But first and foremost, you must adhere to the basic technical minimum:
- the page must be indexed by Google Search and displayed with a web snippet;
- site scanning must be allowed in robots.txt, as well as by any CDN or hosting infrastructure.
There are no additional special requirements for AI Mode — what works for classic search is sufficient.
1. It is advisable to write more non-commercial content that actually solves user queries — after all, in AI search, we formulate long, specific questions and often make additional queries for a deeper understanding.
One strong longread with examples, diagrams, and local cases will work much more effectively than dozens of superficial posts. Google also recommends supplementing text content with high-quality images and videos wherever possible.
2. Ensure a human-centric UX. Even the best content is disappointing if the page is cluttered and navigation is difficult. Check that pages display well on different devices, that visitors can easily distinguish between primary and secondary content, and most importantly, how quickly pages load.
This is influenced by hosting optimized for your CMS, server-level caching, and adequately compressed images.
Here are some helpful resources:
- How to properly configure caching and speed up your website
- How to properly add and optimize media on your website
3. Get microdata right. Structured data and text on the page must match. For example, if the schema says that product.name is “Super Hosting Plan,” then this text must be visible on the page. Or if you set FAQPage, then the questions and answers must be in the layout.
If your page has well-formed structured data, it is easier for it to be included in the set of “candidates” for AI responses, because Google understands what exactly is posted on it. It can also be used partially: for example, only the product description or only contact information.
4. Optimize snippets. Give clear answers, use headings, lists, tables, FAQ and HowTo sections — they are easier to read and are pulled up faster in AI Mode.
Google experts also advise paying attention to internal linking and the relevance of the material (the newer the date, the better). We recommend reading our guide on how to visualize and analyze internal linking on a website with ChatGPT.
5. Increase recognition. The name of the company, its expertise, and the frequency of mentions in other sources influence whether it will be included in AI Mode responses. That’s why we work on guest posts, partnerships, and check that the information in Merchant Center and Business Profile is up to date.
In conclusion
AI Mode is changing the very definition of search. It is no longer a set of links, but an attempt to immediately provide the best answer to a user’s query. It takes into account context, personal preferences, and the expertise of sources.
For companies, this means moving from mechanical optimization to real content marketing, deep expertise, and trust building. This is both a challenge and an opportunity to become a leader in your niche in the new era of search.