How to Optimize for AI Overviews? A Detailed Guide

What has changed in search engines after the introduction of genAI? Learn how to optimize content for AI search and not lose rankings in the new reality.

In 2025, search engines underwent a complete transformation — they entered the era of generative AI. So what does that actually mean? Let’s break it down.

Statistics show that every second search query now comes with a Google AI Overview. This is a radical change. Just last year, this figure did not exceed 25%. As a result, traditional results (SERP) are losing positions. Experts claim that when there is an AI-generated answer, the average CTR drops by 34.5%. This especially concerns informational queries.

At the same time, this shift creates major opportunities for those who’ve adapted to the new landscape. For example, if your branded keyword triggers AI Overviews, CTR will rise by 18.68% (source: SEL).

Here’s the bottom line: stop trying to compete with AI — start working with it. To do this, you need to understand:

🟢 How do Google AI overviews work?

🟢 How do they differ from traditional SERP?

🟢 What content formats does AI “see” best?

🟢 How to measure success in the new ecosystem?

🟢 What optimization strategies will allow you to get to the TOP in 2025?

This guide will give you answers to these and other important questions for maintaining leadership in the race called AI content optimization.

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Understanding AI Overviews

AI Overviews are brief, summarized answers that users see before the regular SERP – that is, sites from the first page of search results. They are generated by artificial intelligence based on large language models (LLMs). For example, Google’s Gemini, OpenAI’s GPT, or Anthropic’s Claude.

👉 For reference: LLMs are advanced machine learning models with impressive natural language processing capabilities. They are trained on large volumes of textual data and can understand, generate, translate text, and perform other tasks.

Creating such answers is a complex process. For this purpose, the system analyzes millions of pages. Then it extracts key information from them, forming a reasoned, relevant text. At the same time, it often inserts quotes by embedding links to the websites that served as sources.

Important! Instead of simply rephrasing the top results, they synthesize insights from multiple sources — giving priority to expert-written, original, and well-organized content.

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How do Google AI overviews work? Algorithm in action

Let’s look in more detail at how the new feature in Google search works. So, AI generates an answer to the user query in several steps:

1️⃣ Query type determination. The system classifies the query as requiring an expert or a summarized answer.

2️⃣ Content gathering. The “reading” system using LLM scans verified sources, then selects the highest quality among them.

3️⃣ Ranking by signal criteria. Among them are E-E-A-T (“Experience, Expertise, Authoritativeness, and Trustworthiness”), reasoning, clear structure and formatting, presence of supporting links.

4️⃣ Answer generation. Based on the sample, the system forms a brief, coherent summary.

5️⃣ Citation. At this stage, links to the sources are selected. Usually, they are formatted as links at the bottom of the answer or as embedded snippets.

As a result, the user sees an answer that is often sufficient for them. Accordingly, there is no need to click through the links in the SERP.

AI Overviews vs SERP: Comparative Characteristics

First, let’s look at the difference between them using a specific example. Suppose a user asks: “How does a solar panel work?” Google will provide them with a list of 20 links, which they will need to click. Then – explore the content of the websites and choose the most suitable answer for their specific situation.

With AI Overviews, everything is simpler. The user will receive a clear answer:

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That is, all the necessary information is gathered in one place. Fast, simple, convenient. Exactly the way the modern demanding audience wants it.

Now we offer you systematized information concerning the differences between AI Overviews and the traditional SERP:

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How Has User Behavior Shifted in 2025?

The shift to AI Overviews from traditional SERPs has significantly changed how users interact with search results. In the first case, a person usually reads the necessary information and leaves. In the second – clicks on links and studies the content of the opened websites.

In numbers, these changes can be described as follows:

➡️ 60% of search queries do not lead to visiting any website

➡️ Almost 62% of users trust AI Overviews to some extent (ExplodingTopics research)

➡️ At the same time, more than 40% of them almost never visit source websites to verify the information

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These changes form a new model of digital behavior. In this model, the speed and convenience of obtaining an answer come first.

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The AI Overview Ecosystem

After everything described above, the transformation of search systems in 2025 is obvious. However, you should not be misled by the fact that in the previous sections of this material we spoke only about Google. In fact, the AI Overview ecosystem also covers other major platforms. Thus, a new space for AI optimization is being formed.

Want to stay competitive in this new landscape? Then it’s crucial to understand how these formats work — and who the key players are.

Google AI Overviews in the Spotlight

Google holds the lead in the field of generative search. Statistics claim that search on this system exceeds search on the ChatGPT by 373 times.

This fact makes it the main channel for any content promotion strategy.

Despite its popularity among users, Google does not stop there. AI Overviews’ answers are becoming increasingly contextual. And preference in their formation is more and more often given to sources with clear structure and deep expertise.

How to optimize for AI overviews? Use a few tips:

✅ Create concise and informative content

✅ Use structured elements (lists, tables, subheadings, etc.)

✅ Work on E-E-A-T

✅ Monitor the relevance of data

We will dwell on AI Overview optimization in more detail later. For now, it is worth mentioning another important fact. Google uses the Gemini model to generate AI Overviews. Its feature is the ability to interpret not only text. It also works with video, images, and code. This opens new opportunities – this time for visual optimization.

AI Mode vs AI Overviews: What's the Difference?

AI Mode is an experimental search mode from Google that allows you to conduct a dialogue with AI. Developers claim that it ensures deeper search and generates detailed, personalized results.

Other features of AI Mode include the ability to search by photo or uploaded images. Users also have access to written and voice queries.

Here is a brief comparative characteristic of AI Overviews and AI Mode. We hope it will help you understand their capabilities and optimize content for AI search.

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As you can see, both tools use the capabilities of generative AI. Both rely on authoritative sources. However, they solve different tasks. And they approach their function differently. AI Overviews are suitable for obtaining short instant answers. Whereas AI Mode allows you to conduct a full-fledged dialogue with AI – to clarify details and adjust the direction of the search.

Other AI Search Engines: ChatGPT, Claude, Perplexity

Yes, in 2025 Google remains the dominant platform. However, recently competition from specialized search engines has intensified. Each of them offers a unique approach to answer generation and user interaction.

1️⃣ ChatGPT. In 2025 this AI tool has essentially become a search engine. It is capable of making real search queries through Bing thanks to close integration with this search engine.
Another fact is that more and more specialists are using ChatGPT for SEO: for generating snippets, semantic analysis, content auditing, etc. This makes it not just an alternative to Google. It is turning into a full-fledged assistant in developing SEO strategies.

2️⃣ Claude. This AI assistant is distinguished by its focus on safety, ethics, and interpretability. Its approach to answer generation can be described as more “cautious” compared to competitors.
This quality can be useful for industries with increased requirements for information reliability. For example, it is advisable to use it in jurisprudence, medicine, and finance.

3️⃣ Perplexity. This is a search engine and chatbot based on artificial intelligence. The tool provides users with concise answers and active links to the information source.
This is a big advantage for those who want to use search for educational or analytical purposes. Maximum transparency allows users to verify the reliability of the data.

By understanding the capabilities and specifics of different AI search engines, you will be able to build an effective cross-platform strategy.

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Content Optimization for AI Citations

The new goal isn’t just ranking — it’s getting cited in AI-generated answers. This requires new AI Overview optimization strategies. They should be focused not only on humans but also on AI algorithms. Let’s consider their specifics.

Content Types AI Prefers

Google AI Overviews, ChatGPT, and Perplexity have one common feature. They are all trained to find structured, reliable, and in-depth information. Here are the formats that most often appear in AI answers:

1️⃣ Original research and data. Priority is given to content with first-party data (own surveys, experiments, etc.). First, it is perceived as authoritative. Second, it has high uniqueness – it cannot be found in other sources.
2️⃣ Interviews and expert quotes. Expert opinions are another sign of authority. Especially valued is the design in the form of direct speech with detailed information about the speaker. This enhances the E-E-A-T factor.
3️⃣ Step-by-step instructions and how-to guides. The point is that this format is ideal for generating AI answers. Numbering, headings, and simple wording are important.
4️⃣ Thematic clusters. Content that covers a topic “broadly and deeply” is more likely to appear in AI Overviews. You can prepare a series of interconnected materials, use cross-links, and a unified semantic context.
5️⃣ Content in FAQ format. The question-answer format is intuitively understandable – both for people and AI. It is suitable for precise citation. Therefore, it is often used for logical, structured AI answers.

Content Structure Guidelines

Your content must be easy to parse and cite. To achieve this, follow these principles:

🟢 Use headings and subheadings. It is important to maintain a logical hierarchy of H1 – H2 – H3. This way AI can understand the structure of the text.

🟢 Formulate answers briefly and to the point. No filler — stick to the point, especially in parts that may be taken out of context.

🟢 Refer to authoritative sources. Provide statistics and facts with links to them. This is especially important for texts on YMYL topics.

🟢 Follow a logical structure. Adhere to the principle of question – explanation – conclusion. This facilitates the interpretation of information by AI systems.

Writing for AI Understanding

Content must be readable for people. This is obvious. However, it is no longer enough. Now it must also be understandable for NLP models. How to achieve this?

➡️ Mention entities. Use precise names, brands, geographical locations, dates, etc. This helps AI to “recognize” and link the context.

➡️ Build the text on keyword research. Select synonyms, terms, and related concepts:

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➡️ Use signals of contextual relevance. These can be specific phrases, case studies. In other words, everything that helps AI understand: the text matches a specific query.

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Technical Implementation

Generative engine optimization uses not only text writing. For AI models to easily identify and cite your material, proper technical implementation is necessary. There are two key elements here: Schema.org markup and optimized page structure.

Markup for AI

Schema Markup is structured data in JSON-LD format. Its purpose is to provide search engines with additional information about the page content. The result — your content becomes more accessible for generative models.

What types of markup are useful for AI?

🟢 Article / BlogPosting. The main type for texts. Helps AI better understand the web page. For example, the essence of the content (blog article, news, etc.), who the author is, or what the title is.

🟢 FAQPage. Allows AI to correctly interpret and display the question-answer.

🟢 HowTo. Ideal for instructions and step-by-step guides.

🟢 MedicalWebPage / TechArticle / FinancialProduct. Relevant for YMYL.

Note: Do not implement markup mechanically. Make sure the content really corresponds to the structure. As well as the accuracy and uniqueness of the information.

Page Structure Optimization

Logical and predictable structure is the key to AI recognizing and citing your content. Here are some recommendations to follow:

1️⃣ Adhere to a unified heading hierarchy. Each block should be highlighted with a separate heading. For example, H1 – the article topic. H2 – the subtopic. H3 – details within the section.

2️⃣ Use tables and lists in the text. This increases the chances of being cited in AI Overviews.

3️⃣ Insert blocks with clear answers. Add short paragraphs that clearly answer a specific question.

4️⃣ Specify unique IDs and semantic tags. Use tags like <section>, <article>, <aside>. As well as logical identifiers. For example, id=”faq”. This will simplify AI navigation through the page.

5️⃣ Optimize page speed and mobile version. Fast loading and adaptability are also important. This minimizes the risk of content not being indexed or displayed. Which means it increases the chances of AI citation.

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AI-First Content Strategy

A modern content strategy is built on the AI-First principle. That is, it is initially focused on generative algorithms. Thus, your goal is to create content that AI can recognize, interpret, and use in its answers. What generative AI SEO techniques can and should be used for this?

Topic Authority Building

AI selects not individual pages, but authoritative sources on a given topic. If you want your site to be seen as a trusted source, focus on in-depth coverage, cite expert voices, and show their credentials.

Content Formats That Work

Priority is given to materials with educational and practical value. The most effective are detailed guides, studies, and a series of educational materials.

Avoiding AI Optimization Pitfalls

Don’t fall into the trap of writing solely for algorithms. Your strategy must be balanced. Be sure to consider the interests of users. And do not chase quantity. Remember: one in-depth, expert article is better than a dozen superficial pieces.

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Measuring AI Optimization Success

Due to the AI Overviews impact on SEO, the usual search optimization metrics no longer provide a complete picture. Positions in search results, CTR, and other indicators that all SEO specialists used to chase have faded.

New Metrics for AI Era

Now, to understand how well your content works, you need to use new approaches and metrics:

➡️ AI citation frequency. Helps track how often a page or brand appears in AI Overviews, ChatGPT, Perplexity, and other generative answers.
➡️ Brand mentions monitoring. AI may not directly link to a brand. However, its mention in a generated answer is also a positive signal. Monitoring such mentions helps assess brand coverage.
➡️ Cross-platform visibility. Do not focus solely on Google. Track how your content performs on all AI platforms via search feature.

Tools and Techniques

Specialized tools can help monitor the indicators mentioned above:

🟢 Perplexity Pages allows you to see cited sources.

🟢 Manual monitoring of AI Overviews is helpful for seed keywords.

🟢 Search Console + GA4 with special REGEX like this:

It is also important to evaluate brand authority growth through the increase in the mentions, engagement, and citations. This is a kind of capital in the genAI economy.

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Future of AI Search Optimization

Thanks to the emergence of generative search, we stand on the threshold of new opportunities. To make full use of them, it is important to adapt to the new essence of SEO. What awaits us and how to prepare for it? Read further.

Emerging Trends

The global transformation of search systems has already begun. And in the near future, all trends will only gain momentum. Namely:

1️⃣ Integration of AI answers into all channels. AI Overviews are becoming the default standard. And not only for web search. They are also used in mobile, voice, and visual interfaces.
2️⃣ Growth of personalization influence. AI takes details into account. For example, location, search history, user preferences. Therefore, AI results will become increasingly personalized.
3️⃣ Platform competition. Although Google remains the leader, it has long ceased to be the only player in the market. Alongside it, ChatGPT, Claude, Perplexity, and other AI search engines are developing. This requires cross-platform content optimization.

Preparing for Changes

To successfully adapt to new AI search trends, it is worth following some recommendations:

➡️ Create content that is cited. This means reliable, structured, expert content.

➡️ Get used to “silent” search. Users increasingly receive a ready-made answer and do not click on links. Therefore, focus on getting into AI Overviews.

➡️ Consider AI as part of your audience. Write so that AI can understand your text and integrate it into its answers.

The future of search is already here — and it demands a whole new playbook. The old SEO rules no longer apply. The winner will be the one who learns to create texts worthy of AI citation. Understandable, expert, reliable.

Want to stay up to date with all updates in this field? Explore our educational resources on SEO. There is a lot of useful information there!

Complete Guide to AI Overview Optimization 2025