Search engines work very differently due to AI, which means brands need to adapt to remain visible. To be seen by major search engines like Google and Bing, as well as AI systems from OpenAI and Yandex, you have to blend classic search engine optimization (SEO) techniques with new generative engine optimization (GEO) concepts. 

Brand visibility, especially online, is key to any modern business, and optimizing content for these new search engines is a crucial part of obtaining it. Keep reading to learn exactly how these AI search engines work, and which SEO fundamentals remain essential even as major GEO concepts become a greater focus.

How Do AI Search Engines Work?

AI search engines work by combining traditional web crawling with large language models (LLMs). These unique models are also designed to deliver either a comprehensive answer to the user’s query or a basic overview of the most relevant information, rather than just a set of helpful links. 

When you type words or phrases into a modern search engine, its bots crawl through the internet and also check indexed data before summarizing the most authoritative and relevant information. This often results in a zero-click search where the user receives the answer they were looking for without having to click through to a listed or cited webpage.

Adapting to Modern Search Engines

Because the technology behind them has changed, businesses need to adapt their strategies to how these modern search engines work. Basic SEO tactics like keyword placement and internal linking are still effective parts of any brand’s content strategy, but the primary objective now is to optimize content so it is more likely to be seen and chosen by AI when they put together their overviews.

SEO Fundamentals

Keyword Placement

Keyword placement was once the basis of any SEO strategy, and it still plays a major role in making your content visible to AI search engines. The LLMs behind Google or Yandex still take the words and phrases entered in each user’s query and match them to similar content online. As a result, your business needs to ensure its content specifically mentions the most relevant keywords in your industry niche so the right audience can find you.

Although short and simple keywords tend to be the central focus of keyword placement strategies, long-tail keywords can also be very helpful for AI visibility. These longer, more difficult keywords can be identified by reviewing search metrics and ranking keyword difficulty. Many businesses will hire an SEO agency to complete such work and feed it into a new content strategy.

Backlinking

Backlinking is another SEO fundamental that still plays a big part in how modern AI search engines decide which sources are worth citing or mentioning. Other websites linking to yours signal to LLMs that your brand is both trustworthy and authoritative, and these signals are even stronger when they come from a larger, more reputable source. 

High-quality backlinks are usually the result of accurate, comprehensive content, which drives increased referral traffic. Google Search Console and similar tools will help you track how many sites link to yours and which ones they are. You can reach out directly to other brands or services in your industry for unique backlinking opportunities.

Technical SEO

Technical SEO is about improving your website’s infrastructure to better appeal to AI search engines. Human users need to be able to read your content with ease, but AI models must also be able to quickly crawl, digest, and summarize it. Slow-loading pages, broken internal links, redirect loops, duplicate content, and other technical issues will prevent bots from crawling and indexing your site. These changes will also greatly improve user experience (UX).

GEO Concepts

Structure and Schema

The most fundamental part of GEO is reworking content structure and schema so that it can be easily digested and summarized by AI models. This process starts with creating a clean layout for each page, including headings for each main topic, subheadings for each subtopic, and structural elements such as FAQs, bulleted lists, and explicit product placement.

All website content must also be organized into content clusters that bots can crawl and index. Large language models prefer information in discrete bundles (typically short paragraphs) so that the visual organization is clean, succinct, and consistent across the whole site. Schema markup defines how data is structured on each site, helping AI models contextualize content.

Brand Authority

The LLMs behind modern AI search engines also prefer to draw information from strong, authoritative brands. Traditional search algorithms focused on matching keywords and returning a list of links, whereas AI-powered search engines aim to provide comprehensive answers using information from only the most trustworthy and authoritative sources.

The best way to improve brand authority is to focus on accurate information that thoroughly covers a topic and its industry-specific subtopics. Backlinks from reputable brands will also greatly improve your site’s brand reputation. Forming partnerships and collaborations with other trusted brands will also signal to AI models that your site is authoritative.

Key Takeaways

The implementation of AI has changed how modern search engines operate, requiring businesses to adapt their content and data strategies. Brands can apply SEO fundamentals that remain crucial (e.g., keyword placement, backlinking, and technical SEO), but they also need to focus on GEO concepts such as optimizing content structure/schema and improving brand authority.

About the author:

Mikhail Slivinskiy is Search Ambassador at Yandex with over 15 years of experience in search technology and SEO. At Yandex, he has worked across product development, webmaster tools, and publisher engagement, including leading Yandex Webmaster from 2017 to 2024. He now focuses on how AI-driven search is evolving and how businesses can maintain visibility through authoritative content.

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