How AI search (GEO) differs from SEO

AI Overviews and AI Mode are dramatically changing organic search traffic. Content creators are focusing on “position zero” — that is, in the search snippet or AI Overview, which appears at the top of many Google search result pages.  

The process of optimizing your website’s content to boost its visibility to AI-driven search engines (ChatGPT, Perplexity, Gemini, Copilot and Google AI) through GEO (generative engine optimization) has some similarities to increased visibility to search engines (Google, Microsoft Bing) through SEO (search engine optimization). SEO is a sort of guessing game, a digital Jeopardy! in which the person creating web content tries to anticipate the query that will bring users to their content. GEO has the same goal, only toward AI overviews and AI mode.

The game has some similarities for both SEO and GEO. They use keywords and contextual phrasing, prioritize engaging content and aim to connect with conversational user queries. Both consider how fast a website loads, mobile friendliness, and prefer technically sound websites.  

However, while SEO focuses on metatags, keywords and backlinks, AI models are trained to provide quick, direct responses from the synthesized content gathered from multiple sources. GEO is about, not only the query, but information about the user — from their social media footprint to their Google Docs usage. This informs, not only the search at hand, but future searches. AI will evaluate who created the content, its trustworthiness, and how it fits within the broader knowledge graph the AI is using.

Generative search efforts, therefore, attempt to fit into this reasoning process. AI judges the content value, not just on whether it ends up a part of the final answer, but whether it helps the model reason its way toward that answer. This is why, despite performing all the typical SEO common practices, a GEO effort may not make it to the other side of the AI reasoning pipeline. It’s not enough to be generally relevant to the final answer. Your content is now in direct competition with other plausible answers, so it must be more useful, precise, and complete than the next-best option. In fact, the same content could go through the pipeline a second time and yield a different result. And since newer models are rapidly changing right now, the best GEO may be effective when using an older model but not with a more recently trained model.  

There is also a user shift to consider toward longer, more natural queries, from one- or two-word keywords to three- and four-word search terms. Research indicates that queries in AI mode are generally two to three times the length of traditional searches.  

What do AI Overviews avoid? Content that is overly generalized, speculative, or optimized for clickbait over clarity. Vague and generic writing underperforms. So what kind of content does the Google AI Overviews favor?

  • Content that contains the who, what, why

  • Straightforward content offering distinctiveness; AI rewards niche-specific content

  • Is written in natural, conversational terms (AI will attempt to deliver its answer in that same way)

  • Uses strong introductory sentences that convey clear value 

  • Has H2 tags (subheadings) that align with user questions

  • Is structured to match common question structures (open, closed, probing)

  • Answers complex questions

  • Allows for restatement of quires and implied sub-questions, where a main question is broken down into smaller parts; content structured in a way to be easily grabbed — in citable chunks

  • Contains multi-faceted answers

  • Is rich in relationships

  • Has explicit logical structures and supports causal progression

  • Has clear headlines

  • Cites sources and has clear authorship

  • Includes statistics & quotations 

  • Has multimedia integration

  • Content that tells the world something new

  • Uses HTML anchor jump links to connect different sections of content to one another

  • Podcasts that include full transcripts in YouTube video descriptions, which are easily searchable

  • Appears on YouTube (a Google-owned company) based on the titles, descriptions & transcripts of videos

More information:

What is AI reading? Takeaways from a report on AI brand visibility

How AI Mode and AI Overviews work based on patents and why we need new strategic focus on SEO

What is generative engine optimization (GEO)?

How To Get Your Content (& Brand) Recommended By AI & LLMs

Google Ads data shows query length shift post-AI Mode

The winners and losers of Google’s AI Mode

SEO Is Dead. Say Hello to GEO

Stephen Goforth

Writing for AI Overviews & Generative Engine Optimization

AI Overviews and AI Mode are dramatically changing organic search traffic.

While search engine optimization (SEO) focuses on matching a user’s query, generative search also considers information about the searcher themselves—from their Google Docs usage to their social media footprint. This information is used to inform, not only the current search, but future searches as well.  

Likewise, the process of optimizing your website’s content to boost its visibility in AI-driven search engines (ChatGPT, Perplexity, Gemini, Copilot and Google AI) has a similar path. As SEO helps brands increase visibility on search engines (Google, Microsoft Bing), generative engine optimization (GEO) is all about how brands appear on AI-driven platforms. There is overlap between the goals of GEO and traditional SEO. Both SEO and GEO use keywords and prioritize engaging content as well as conversational queries and contextual phrasing. Both consider how fast a website loads, mobile friendliness, and prefer technically sound website. However, while SEO is concerned with metatags and links in response to user queries from individual pages, GEO is about quick, direct responses from synthesizes content out of multiple sources.

AI models are not trained solely to retrieve relevant documents based on exact-match phrasing. Generative search is about fitting into the reasoning process, starting with the user’s identity. That’s why your content is being judged, not just on whether it ends up in the final answer, but whether it helps the model reason its way toward that answer. Despite performing all the typical SEO common practices, your response may not make it to the other side of the AI reasoning pipeline. In fact, the same content could go through the pipeline a second time and yield a different result. It’s not enough to be generally relevant to the final answer. Your content is now in direct competition with other plausible answers, so it must be more useful, precise, and complete than the next-best option.

It appears now that Google AI Overviews favors content that:

  •  contains the who, what, why

  • offers clarity and distinctiveness in the small sections

  • is written in natural, conversational terms (AI will attempt to deliver its answer in that same way)

  • uses strong introductory sentences that convey clear value 

  • has H2 tags that align with user questions

  • is structured to match common question structures (open, closed, probing)

  • allows for restatement of quires and implied sub-questions, where a main question is broken down into smaller parts.

  • contains multi-faceted answers,

  • is rich in relationships,

  • has explicit logical structures and supports causal progression,

  • has clear headlines

  •  cites sources

  • includes statistics & quotations 

  • has multimedia integration

AI Overviews attempt to exclude content that is overly generalized, speculative, or optimized for clickbait over clarity. Vague and generic writing underperforms.  

LLMs are being trained to favor content that helps them reason well. Writers should attempt to match those paths that the models take to arrive at high-confidence answers. 

More information: 

How AI Mode and AI Overviews work based on patents and why we need new strategic focus on SEO

What is generative engine optimization (GEO)?