Digital search has changed—and that means content producers must change too. Until recently, finding information online meant typing keywords into a search engine. Marketers and product managers optimized website content so their sites would earn high rankings in search engine results, which would in turn drive more traffic to their sites.

But generative AI (GenAI) has altered that model. Today, users often type full questions into GenAI tools such as Google’s Gemini, OpenAI’s ChatGPT, or Perplexity, which produce answers that draw from multiple websites. Even when users turn to familiar search engines, those search engines are increasingly using GenAI to provide answers alongside traditional linked results.

The shift to these AI-assisted searches for information is happening rapidly. The number of prompts that ChatGPT processed per day rose from 1.1 billion in late 2024 to 2.5 billion by July 2025. Meanwhile, Google AI overviews now appear in more than 50% of Google search results, totaling between 4 and 8 billion AI overviews each day. As the use of GenAI tools and AI-powered search increases, Gartner’s prediction of a 25% decline in traditional search volume could become a reality.

This shift to AI-assisted searches requires a change in content optimization strategies. Instead of focusing exclusively on search engine optimization (SEO), marketing and product teams must incorporate generative engine optimization (GEO) into their workflow. They need to optimize content so it is more easily retrieved and cited within AI-generated responses.

How should your team modify your content optimization strategy? Understanding how generative engine algorithms work, what GEO is, and how GEO differs from SEO are key steps in building a new strategy.

#How do generative engine algorithms work?

The generative engines that power AI-assisted searches collect information from multiple sources and then use large language models (LLMs) to produce answers for specific user questions.

Think of generative engines as AI-powered research assistants who are expert at finding information, synthesizing content, and delivering complete answers rather than offering a list of links to possible sources.

Broadly, the generative engine process can be divided into two stages:

Retrieval: When a user asks a question in a GenAI tool or AI-enhanced search engine, the generative engine performs a “query fan out”: It breaks the question into small parts and runs numerous simultaneous searches, exploring commercial websites, digital publications, discussions on social media, and more.

The engine is not looking for matching keywords; it is searching for context and supporting proof points that can answer the question. Generative engines favor “answer-shaped” content—that is, content that has already been structured as answers to questions.

Generation: Once the engine gathers all this information, it selects the most authoritative content and synthesizes a single response, in conversational language. It offers citations to the most authoritative, answer-shaped content used for the response.

#What is generative engine optimization (GEO)?

GEO is the practice of optimizing digital content so that generative engines and their LLMs are more likely to retrieve, synthesize, and cite that content directly within AI-generated responses.

In addition to structuring content as answers to questions, GEO aims to provide an authoritative, trustworthy source that AI systems will reference.

GEO should complement SEO, not replace it—after all, traditional search is not dead (yet). By incorporating GEO into content optimization, organizations help ensure that their content continues to be readily discoverable and recommended as the shift toward AI-powered search accelerates.

#What are the differences between SEO and GEO?

GEO is like an evolution of SEO. The two approaches share core foundational elements and principles, but their tactics differ significantly. Here are some similarities and differences:

#Best practices for building a GEO strategy

How should your team start implementing GEO? Three best practices can help you develop your strategy.

1. Establish baselines

Before you rewrite content and restructure web pages, it’s important to understand how your content is already performing with GenAI tools and AI-assisted searches.

• Identify key user questions: What customer or user questions do you want to answer most? In addition to defining keywords (which can help with SEO), pinpoint the questions your customers or other users would typically type into a search engine or GenAI tool. Consider how they might ask different questions at each point in the customer or user journey.

• Find citation gaps: Does your content appear in answers to key user questions, or are your competitors appearing more often? Try to determine whether your content is not being retrieved or not being recommended—each issue requires a different solution.

• Establish a share-of-answer baseline: If your brand does appear in some answers, approximately what percentage of the AI-generated answer comes from your content?

• Examine accuracy: Is content that cites your brand accurate and up to date?

• Evaluate brand sentiment: Do generative engines shine a positive light on your brand?

2. Restructure content for generative engines

Unless your content is already overachieving in AI-generated answers, you’ll need to rethink what to say and how to say it. Keep in mind that optimizing content for generative engines means presenting content that is easily extracted and synthesized by machines.

• Answer the question first: Place clear definitions and direct answers to user questions toward the top of pages.
• Use scannable formats: Organize information using descriptive headings that map to common questions, and use bulleted lists and data tables.
• Simplify semantics: Use simple sentence structures to help AI systems extract content and understand relationships between concepts.
• Optimize for retrieval: Instead of producing numerous thin pages, build deep pages that help generative engines find the context they need as they conduct background searches.

Remember that establishing the authority preferred by generative engines means getting your content cited elsewhere—such as in third-party articles and in online forums. In other words, don’t just write for LLMs; craft engaging, authoritative information that can be incorporated into other content. Meanwhile, encourage and incentivize users to write about your products and brand on other digital platforms.

See Checklist: How to structure content for LLMs for a detailed guide on optimizing content in this new AI-assisted search landscape.

3. Measure success and further optimize

To continue refining and optimizing content for generative engines, measure the effectiveness of your efforts. Compare metrics to your baseline measurements, such as:

• Share of answer: Is your content more prominently featured in AI answers than content from competitors?
• Citation accuracy: Have you improved the accuracy of how your brand, products, or ideas are represented in answers?
• Sentiment: Do AI responses now present your brand and content in a more favorable light?

Evaluate how well the AI responses that include your content answer user questions and refer users to your brand or website.

• Prompt alignment: Does your content match specific prompts from users?
• Citation rate: How often do AI tools cite your brand and provide a clickable link to your site within answers?
• Referral rate: Have you increased the volume of traffic to your website from GenAI tools and AI-powered searches?

#Get started with Hygraph

The shift toward AI-assisted search will continue to accelerate. To ensure your brand and your content continue to be top of mind for users seeking answers, implementing a GEO strategy now is essential.

Hygraph allows you easily make content structure, relationships, and context explicit—which is critical for the retrieval and use of your content in AI-generated answers. In addition, marketers and product managers can easily optimize and update content, delivering relevant, up-to-date information without need for developer intervention. Your team gains a foundation for improving traditional SEO and building the GEO strategy that is critical for this new era of AI-assisted search.

See how Hygraph handles SEO and GEO for thousands of global content teams, or contact us for a demo.