What is AI and How is it Changing Search?
The rise of AI is fundamentally changing how search works, along with how people search and what their expectations are as a result. Instead of relying solely on keywords, AI deeply understands the meaning and relationships between words and the context of queries, matching them to the underlying intent of a user’s search (or prompt) to generate relevant text. This means search is moving from “strings” to “things“, where topics and entities (well-defined concepts like people, places, or products) are the focus instead of just keywords. AI also places a greater emphasis on quality authoritative, credible and trustworthy content sources that are well-structured and address specific user intent. The end result is more accurate, contextually relevant, and personalized search results.
Traditional search engines like Google and Bing are now integrating AI into their algorithms and have gone beyond just showing a list of links to websites in their results in response to user searches. They are incorporating AI-powered features like Google’s AI overviews for a rapidly growing number of queries. These generative AI summaries of information directly answer simple search queries to more complex, deeper open-ended questions or asks to perform a task that users couldn’t search for before, all at the top of traditional search results. They are also providing users with the ability to search in “AI Mode” directly on the search engine itself using their AI assistants Gemini and Copilot, which are powered by large language models (LLMs) trained on vast datasets that synthesize information from a variety of indexed authoritative web sources and provide quick, direct, robust and authoritative responses based on an understanding of the underlying intent behind the prompt, shifting traditional behavior of exploring multiple websites.
In addition, stand-alone AI-powered answer engines like Perplexity and other generative AI assistants and chatbots like ChatGPT and Grok have exploded in popularity and are becoming powerful alternatives to traditional search platforms. These LLMs and answer engines do not “rank” content in the traditional search engine sense. Rather, LLMs surface content by first training on massive datasets to learn patterns and context, then by analyzing user prompts to retrieve relevant information from their internal knowledge and the live web (i.e. search engine indices). They then generate responses by predicting the most probable sequence of words, often prioritizing clarity, structure, and semantic relevance from sources that demonstrate expertise, authority and trustworthiness. Content is “surfaced” for an LLM to process when it’s crawled and deemed relevant and authoritative enough to be included in the AI’s response. They are increasingly being used for quick answers, more thorough research and information gathering, and summarizing things, furthering the shift of clicking through to websites to getting direct answers to searches in results even more.
Rather than the link-based “card catalogs” where users have to click through multiple websites to find the information they need, AI is transforming search into a direct, conversational, and personalized experience with “answer engines” and assistants that integrate information from various sources across the web, changing how info is consumed and reducing the effort needed to find answers. AI is not a trend but a profound, fundamental shift that is redefining the rules of search.
While AI search is still evolving, it has already established itself as the new dominant force in information access. It is here and the shift will be ongoing.
How is AI Changing User Behavior and Impacting Search Visibility?
When it comes to traditional search engines, while they have been moving beyond simple keyword matching to interpreting the nuances of human language, the context of a query and understanding user intent for quite some time and integrating that into their search results, AI has brought this shift front and center. Their algorithms have evolved and AI is now embedded within every step of today’s search process – crawling, indexing, and ranking – as it has enabled search engines to better understand user intent and evaluate content quality. This has brought about many changes to search and its results which are changing user behavior and impacting visibility for businesses and organizations.
The rise of AI-powered search engine features, like Google’s AI Overviews, directly answers user questions at the top of search results, altering how users interact with content. Because AI Overviews frequently satisfy the user’s need for information directly on the search engine results page (SERP), users may not even feel the need to click through to cited websites or any of the traditional blue links below the AI Overview, taking prominence away from individual websites and leading to a possible decrease in a ranking site’s organic click-through rates (CTR) and traffic. This rise in “zero-click” searches has also led to the phenomena known as the “Great Decoupling”, where a website may see a rise in impressions for some queries if it happens to be a cited source in an AI Overview, but a decrease in visits to it because users are not clicking through.
As a result, AI overviews are changing how search engine visibility and traffic need to be measured. Success metrics for organic search have shifted from solely ranking highly on a traditional results page with a “blue link” and traffic from that, to include presence within AI-generated answers as a featured source as well. Having content featured within AI summaries can still drive visibility, awareness and establish brand authority, even if a mention doesn’t result in a direct click.
In addition to the evolving of search engines, the growth and adoption of AI assistants – including those that are integrated into the major search engines – have rapidly accelerated in the past few years and will only continue to spike in the future as users become even more accustomed to AI-driven searching and responses. Their increase in popularity and usage is also making visibility in the answers that these assistants cite extremely important as well. This is forcing businesses to shift their focus to different metrics beyond just clicks, such as how often a brand appears AI-generated answers on the different platforms for relevant topics and prompts, how often a brand is cited by AI-generated answers, brand sentiment, and conversion rates to measure the value of higher-intent traffic.
At the end of the day however, while clicks may decrease and changes in measurement is needed, brand mentions within AI summaries create new touchpoints for awareness, requiring companies to adapt their strategies to capture user attention.
Strategies to Adapt Your SEO for the AI Era
There is no question that we are living through the biggest transformation in search since Google launched in 1998. And while you may have heard that SEO is dead and that optimizing for AI-powered search engines and answer engines, with all new buzzy terminology and acronyms like generative engine optimization (GEO), answer engine optimization (AEO), artificial intelligence search engine optimization (AI SEO), and large language model SEO (LLM SEO) coming into focus, the reality is that SEO is not dead, it’s simply evolving and expanding.
All of the modern, fundamental SEO principles that have become critical for today, such as writing for your readers, focusing on E-E-A-T, and improving content quality, are the same things that will help you show up on search engines, in AI overviews, and across any of the AI search platforms. Will there be new approaches and tactics that help you rank across these platforms down the road? Surely, but for now keep your strategy focused on the fundamentals. Google themselves even say so….
Google has stated that AI Search does not require specialized optimization, saying that “AI SEO” is not necessary and that the standard SEO of today is all that is needed for both AI Overviews and AI Mode. Their core message is that new AI-powered features like AI Overviews and AI Mode are built upon the same fundamental processes as traditional search. They utilize the same crawler (Googlebot), the same core index, and are influenced by the same ranking systems. They have repeatedly emphasized that a separate, distinct strategy for “AI SEO” is unnecessary. The foundation of creating high-quality, helpful content remains the primary focus.
Despite all of these changes, modern SEO is still valuable and effective. Building high-quality content for real people on trusted sites is what wins, not tricks or shortcuts. Even Google’s search team has confirmed it: “Good SEO is good GEO.” If you have or can build strong organic search rankings, you will likely have strong rankings in AI as well.
So, considering the growing proliferation of AI Overviews in traditional search results and usage of AI-powered chatbots and answer engines, what are the core SEO strategies that companies need to be focusing on to ensure they are visible in AI-generated summaries? Here they are:
On-Page Content
- Create high-quality, original, genuinely helpful, comprehensive, clear, and contextually rich content that puts readers first that AI can cite. Prioritize user intent by understanding the core needs driving a user’s search query, and address those needs directly and thoroughly in your content.
- Structure and logically format your content for clarity, scan-ability and easy retrieval, and organize it using descriptive headings, bulleted lists, tables and concise paragraphs. Make content easy for AI-powered engines to parse and extract key information that they can synthesize into their answers.
- Don’t keyword stuff your content! Create content that is semantically relevant, addressing broader concepts and user problems.
- Optimize for natural language searches and conversational queries, such as those used in voice search or with an AI chatbot. Use FAQs to provide direct, concise answers to common questions.
- Strengthen your Experience, Expertise, Authority and Trust (E-E-A-T)). This is now more important than ever as LLMs are trained to favor content from credible, authoritative and trustworthy sources. Showcase authors with credentials and deep experience. Focus on demonstrating genuine expertise and providing unique, factual content rather than mass-producing generic material.
- Strengthen your topical authority. LLMs think in terms of “entities” – concepts, people, brands, and places – instead of just keywords. Focus on building topical authority around a core subject by publishing comprehensive content and using internal links to show connections between related entities to create topic clusters.
- Publish new content consistently and refresh existing content to keep it current and relevant. Up-to-date information is important so think about incorporating “Last Updated” dates, referencing the current year, and possibly include the estimated amount of time to read.
- Optimize for multimodal success by incorporating high-quality images and videos alongside your text. This helps you appear in more diverse search formats, especially as AI features expand to include multimodal queries.
Technical
- Prioritize fundamental technical health with mobile-friendliness, fast load times, clean and organized site structure, and easy navigation that is easily accessible and crawlable. Basically, optimize the user experience.
- While structured data has not been proven to have an impact in ranking within LLMs, it’s importance when it comes to traditional search engines and helping them to better understand and discern real meaning from content is well documented. Therefore, integrating it into your site content is a smart, future-proof strategy.
Off-Page Authority Building
- Build a trusted brand to drive positive sentiment and mentions across the web (i.e. relevant and popular forums, publications, news articles, customer reviews on relevant platforms and directories, etc.) and continue to manage it. Even unlinked mentions are important. Try to create a presence in places that AI engines tend to cite.
- Build a strong backlink profile. High-quality backlinks from relevant, reputable websites continue to signal trustworthiness, authority and credibility, which AI models use to determine which sources to cite.
To succeed now and in the future, companies must embrace AI’s capabilities, integrate them strategically, and focus on delivering high-quality, user-centric experiences.