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Ranking highly in search was the ultimate goal of traditional search engine optimization (SEO), but ranking first is no longer enough to succeed in AI search. A brand’s new objective is to have its content mentioned, cited, and synthesized as part of AI-generated answers to user queries. In this article, we will discuss how AI systems have reshaped the search landscape and explain how companies can adapt their SEO strategies to improve AI visibility.
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Traditional SEO Basics
Traditional search algorithms once functioned very differently, and SEO was initially designed to optimize content so that webpages would rank high on search engine results pages (SERPs). The main facets of traditional SEO were placing keywords that matched user queries, earning backlinks from other sites, and having proper site infrastructure so that search engines could easily read the content. All of these factors still matter to some extent, but they function differently under AI-powered search engines.
How AI Has Changed Modern Search Engines
Zero-Click Searches
The adoption of AI-generated summaries has significantly increased the prevalence of zero-click searches, in which users get direct answers to their queries without clicking any links on the SERP. The primary objective of traditional SEO was to get webpages to rank first for the most relevant keywords, but ranking high matters less if users are no longer clicking through to any webpages.
Synthesized Answers
AI search engines now provide synthesized answers to search queries, rather than forcing users to pull information from multiple sources and synthesize their own answers. Traditional search engines were designed to index linked, relevant webpages so that users could click and read until they had enough information to answer their own query. AI search engines, in contrast, act as respondents, providing clear, direct answers.
Dynamic Results
In this new era of AI, search engines provide dynamic results instead of static rankings. Older models returned the same webpages and rankings for all users, regardless of the query, as long as they typed the same or similar keywords. Modern AI search engines, meanwhile, utilize continuous, real-time re-ranking that takes into account a user’s search history, location, and other factors. Ranking first is still important, but different people asking the same question may get different results.
What Is GEO?
Generative Engine Optimization (GEO) refers to the process of optimizing webpages so that AI search engines like Google or Yandex are more likely to synthesize, mention, or cite them in their answers. Traditional SEO tactics remain helpful for getting content indexed and ranked by search engines, but GEO is necessary for AI visibility. Ranking first can still be a goal, but it should be secondary to appearing in AI-generated answers.
Adapting SEO for AI Search
User Intent
AI search engines are designed to interpret the user intent behind each query. They classify each query into one of four types: informational, commercial, transactional, or navigational. Search engines then surface content that best meets the user’s intent, even if the exact phrasing does not match the content.
User queries are also becoming longer and more conversational, making it harder to match content to keywords. SEO adapted for AI search should move away from keyword density and focus on aligning with the content target users want to see.
Entity Clarity
Large language models (LLMs) powering AI-powered search engines parse online content to extract named entities and relationships. They scan indexed content for identifiable nouns, such as the names of people, places, concepts, or brands. Coherent statements with clear entities enable AI systems to associate a specific brand with a particular topic.
Businesses that want to adapt their SEO to AI search should make explicit, accurate claims so that search engines can anchor their brand to specific knowledge categories. Vague statements and unclear entities reduce the likelihood of citations or mentions in AI-generated summaries.
Answer-First Content
Content that leads with answers is much more likely to be mentioned, cited, or synthesized by AI search engines. They specifically scan content looking for clusters of information that are easy to extract without too much surrounding context. Even high-quality information is less likely to be incorporated into AI-generated answers if it is buried under a long introduction or excessive background information.
To increase the likelihood of appearing in AI search results, brands should front-load information whenever possible. The key point of any section on a webpage should be stated in the first sentence or at least the first paragraph of that section. For the same reason, the opening paragraphs of each webpage are especially critical.
Authority and Trust Signals
AI search engines prioritize content from sources that they deem authoritative and trustworthy. Google’s own E-E-A-T evaluation framework stands for Experience, Expertise, Authoritativeness, and Trustworthiness. Content that signals all four qualities is much more likely to be seen as credible by AI systems.
The most important authority and trust signals are being mentioned, cited, linked to, and reviewed by trusted third-party sources in relevant industries. Backlinking remains an important aspect of SEO, but it serves as a topical authority signal to AI search engines.
Structured Data and Markup
Improving a site’s structured data and schema markup enhances AI systems’ ability to extract and cite information in response to user queries. Modern search engines read structured data directly because it consists of machine-readable JSON-LD labels that explain what a piece of content is.
Businesses that want to improve their structured data and markup should add common content types like articles, FAQs, products, reviews, and how-tos. Some companies also hire AI visibility agencies that specialize in technical SEO, increasing the likelihood that their content will be extracted and cited.
Critical Insights
The widespread popularity of AI-powered search engines like Google, Yandex, and Bing has shifted the goal of SEO beyond ranking first on SERPs. Brands want their content to be extracted, mentioned, and cited in AI-generated answers to relevant user queries. To become visible in this new era of AI search, businesses should focus their SEO strategies on user intent, entity clarity, answer-first content, authority signals, and structured data.
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.
