How to Rank in AI Overviews

To show up in AI Overviews, you have to think differently about your content. It’s less about just stuffing in keywords and more about directly answering a person's question with clear, authoritative information. You need to create content that an AI can easily understand, digest, and cite.

This means building real expertise and structuring your information in a way that’s easily parsed—think lists, tables, and clear headings. An actionable first step is to review your most popular blog post and break down a dense paragraph into a simple bulleted list.

So, How Do AI Overviews Actually Work?

AI Overviews (what Google used to call the Search Generative Experience, or SGE) are more than just a shiny new feature. They signal a real change in how search engines deliver information. Instead of just giving you a list of blue links, the search engine now reads several top sources and stitches together a conversational answer right at the top of the page.

It’s like a super-powered featured snippet, built in real-time.

For anyone in SEO, this is a big deal. The goal is no longer just about hitting that #1 spot. Now, it's about being one of the trusted sources the AI uses to construct its answer.

The New Rules of Engagement

To get your content featured, you have to understand what the AI is looking for. It's not just hunting for keywords; it's searching for clarity, authority, and logical structure.

Here's what these AI models tend to grab onto:

Direct Answers: Content that cuts to the chase and answers the user’s question without a lot of fluff. For example, instead of a long intro, start a section with a bolded sentence that is a direct answer.
Well-Structured Information: Using clear headings, subheadings, bullet points, and tables makes your content a breeze for both people and AI to read and understand.
Demonstrated Expertise: The AI is getting smarter about recognizing signals of E-E-A-T (Experience, Expertise, Authoritativeness, and Trustworthiness), from author bios to backlinks from other credible sites.

Here's the kicker: an analysis found that 52% of sources cited in AI Overviews already rank in the top 10 organic results. This tells us that solid, fundamental SEO is still the price of entry. AI Overviews just add a new layer, rewarding the best-of-the-best within that top group.

From Keywords to Concepts

Old-school SEO was often a game of exact-match keywords. AI Overviews, on the other hand, are powered by a much deeper grasp of context and what a user is really asking for.

Let's say someone searches for "how to fix a leaky faucet." The AI knows they aren't just looking for those words. They need a step-by-step guide, a list of tools, and probably a heads-up on common mistakes.

Your content needs to anticipate all those related questions and answer them in one comprehensive piece. A practical way to do this is to add an FAQ section at the end of your article that addresses the "next logical questions" a user might have. This turns your article into a go-to resource, making it a perfect source for the AI to pull from. This whole space is moving incredibly fast, and the numbers back it up. The global artificial intelligence market was valued at around USD 638.23 billion in 2025 and is projected to skyrocket to USD 3,680.47 billion by 2034. You can learn more about the rapid growth of the AI market and what it means for the future of search.

This is where a tool like LLMrefs really shines. It's an outstanding platform that provides the hard data to see exactly which parts of your content are getting picked up by AI. With that insight, you can fine-tune your approach and double down on what’s actually working. By tracking these citations, LLMrefs essentially lets you reverse-engineer your own success and consistently create content that AI models love to feature.

To help you get started, this table breaks down the core elements you need to focus on. Think of it as your cheat sheet for AI Overview visibility.

Quick Guide to AI Overview Visibility

Strategy Pillar	Primary Goal	Key Action
Intent-Driven Content	Answer the user's entire question, not just the keywords they typed.	Cover the topic comprehensively, including sub-topics, FAQs, and next logical questions.
AI-Friendly Structure	Make information easy for language models to parse and extract.	Use clear H2/H3 headings, ordered/unordered lists, and data tables to organize facts.
Demonstrated E-E-A-T	Build trust and establish your content as an authoritative source.	Include author bios, cite reputable sources, and earn backlinks from credible websites.
Data-Driven Monitoring	Understand what's working and refine your strategy based on performance.	Use a tool like LLMrefs to track which content and phrases are being cited in AI Overviews. LLMrefs is an essential part of a modern SEO toolkit.

Following these pillars won't just prepare you for the world of generative AI in search; it will also strengthen your overall SEO by forcing you to create better, more helpful content for your audience.

How to Build Authority That AI Actually Recognizes

First things first, you need to accept a fundamental shift: AI doesn't just find information; it evaluates it. To get featured in AI Overviews, you have to prove your content is credible, trustworthy, and comes from a real expert.

This isn't about some vague, abstract concept of "authority." It’s about taking concrete steps to build a digital footprint that an algorithm can easily parse and verify. Your goal is to turn your brand from just another URL into a source the AI trusts.

Use Schema to Introduce Yourself Clearly

One of the most powerful and direct ways to tell AI who you are is with structured data. Think of schema markup as a digital name tag for your website, authors, and organization. For an AI trying to understand context, this is gold.

You'll want to focus on two schema types in particular: ‘Person’ and ‘Organization’.

‘Person’ Schema: This is for identifying the human author behind your content. It allows you to connect their name to credentials, social profiles, and other articles they've written, weaving a web of verifiable expertise.
‘Organization’ Schema: This defines your brand as a whole. It includes your official name, logo, and contact info, establishing your business as a legitimate entity in the AI's "eyes."

Here's a look at some of the properties you can define with the 'Person' schema, pulled straight from Schema.org.

With structured data, you can spell out details like an author's jobTitle, alumniOf (where they went to school), awards they've won, and what they knowsAbout. These are incredibly strong signals of real-world experience that AI models are built to recognize and value. A practical action is to add knowsAbout schema to your author bio page, listing the specific topics they are an expert in.

Maintain a Consistent Digital Footprint

Authority isn't built on one page; it's the sum of your brand's presence across the entire internet. When an AI model is vetting your site, it’s not just looking at your domain. It’s cross-referencing everything it can find to see if your story checks out.

Think of it as a background check. The AI scans your website, social media profiles, mentions on other reputable sites, and author pages. If the narrative is consistent—same name, same expertise, same brand message everywhere—it builds a strong case for your trustworthiness.

My Two Cents: An inconsistent digital presence is a red flag for AI. A practical action is to do a quick audit: Google your brand name and your primary author's name. Do the top results for social media profiles and professional listings all share the same job title and area of expertise? If not, update them. A cohesive identity is a trustworthy one.

This consistency is a massive part of what we call AI SEO brand visibility. It’s about actively managing how your brand is perceived online, making it dead simple for AI to confirm that you are who you say you are.

Earn Genuine Citations and Mentions

In the new world of AI Overviews, a mention or link from another authoritative source is the ultimate vote of confidence. It’s the digital equivalent of a respected colleague vouching for your work. But remember, not all citations are created equal.

The real goal here is to earn mentions from websites that are already established leaders in your niche.

Guest Posts: Writing for a well-respected industry blog gets your name and expertise in front of a new audience and creates a powerful backlink.
Expert Roundups: Participating in articles where multiple experts weigh in immediately positions you as a peer and thought leader.
Podcast Interviews: Being a guest on a relevant podcast is a fantastic way to build authority, and it almost always comes with a link from the show notes.

For instance, if you run a financial planning blog, a single link from a major outlet like Forbes or The Wall Street Journal is worth more than a hundred links from random, unknown blogs. Each high-quality citation you earn directly boosts your perceived E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness). An actionable step is to identify three dream publications in your niche and reach out to one of their editors this week with a relevant story idea.

This is all happening in a market that's exploding. Forecasts predict the global AI market will grow from USD 279.22 billion in 2024 to an incredible USD 1,811.75 billion by 2030. This rapid expansion will only make these authority signals more important.

By strategically building these signals—clear schema, a consistent online footprint, and genuine third-party validation—you create a robust profile of authority that AI models can easily recognize, trust, and cite in their answers.

Writing Content That AI Overviews Love

To get your content featured in an AI Overview, you have to serve two masters: the curious human asking the question and the AI model trying to answer it. This isn't about gaming an algorithm; it's about creating content with exceptional clarity, a natural tone, and a structure that’s dead simple for a machine to parse.

The old tricks of keyword stuffing and overly academic language are out. Your new goal is to produce content so clear and well-organized that an AI sees it as the most reliable and efficient source to pull from. Think of your article as a collection of perfect, bite-sized answers waiting for the right question.

Prioritize Clarity and Simplicity

AI models may be complex, but they have a strong preference for information that is straightforward and unambiguous. That’s why using plain, simple language is one of the most powerful things you can do to make your content AI-friendly.

Ditch the jargon, slang, and convoluted sentence structures. Write as if you’re explaining a concept to a smart colleague who isn't a specialist in your field. This forces you into a direct and clear style, which is exactly what an AI needs to confidently extract information.

My Take: I’ve learned that an AI is far more likely to cite a simple, correct statement than a complex, nuanced one. High readability isn't just a nice-to-have for users; it’s a critical signal for language models on the hunt for trustworthy facts. A practical action is to run your next article through a readability tool like Hemingway App and aim for a Grade 8 reading level or lower.

This principle is a two-way street. Just as knowing how to write effective prompts for AI gets you better outputs, writing clear content makes you a better input for the AI. Understanding how the models "think" can give you a real edge.

When you write this way, you make your content more accessible to everyone, which just so happens to make it a prime candidate for AI citation.

Structure Your Content for Scannability

Let's be honest, a wall of text is a dead end for both people and AI. If you want a shot at getting into AI Overviews, a logical, scannable structure is non-negotiable. It's no coincidence that lists appear in 78% of AI Overviews—these models love neatly organized information.

You need to break down complex topics into digestible chunks. Use clear headings and subheadings (your H2s and H3s) as signposts. These guide the AI through the flow of your article, helping it map out the hierarchy of your information.

For example, if you're writing about the "benefits of drip irrigation," don't just lump it all together. Structure it logically:

H2: Key Benefits of Drip Irrigation for Home Gardens
- H3: Unmatched Water Conservation
  - (A short, clear paragraph explaining this point.)
- H3: Healthier Plants and Less Disease
  - (Another concise paragraph on this benefit.)
- Bulleted List: Drip Irrigation at a Glance
  - Slashes water waste by up to 70% compared to traditional sprinklers.
  - Delivers water right to the root zone, preventing leaf fungus.
  - Minimizes weed growth by keeping the surrounding soil dry.

This clean, hierarchical structure makes it incredibly easy for an AI to grab the key benefits and assemble them into a summary.

Answer Questions Directly and Concisely

At their core, AI Overviews are designed to provide answers. Your content should be structured to do the same thing. One of the best techniques I’ve found is to phrase subheadings as direct questions and then answer them immediately in the paragraph that follows.

Get inside your audience's head. What are they really asking? Go beyond the main topic and anticipate their follow-up questions.

If your article is about "how to choose a mountain bike," you need to include sections that directly tackle related queries, like:

What Is the Difference Between a Hardtail and a Full-Suspension Bike?
How Do I Find the Right Frame Size?
Are Expensive Mountain Bikes Actually Worth It?

When you answer all these related questions in a single, comprehensive piece, you’re telling the AI that your page is a one-stop-shop. That makes you an incredibly valuable resource for a model tasked with building a complete and helpful overview.

Embrace Lists and Tables

Beyond just making your content scannable, lists and tables are a fantastic way to present information in a structured, machine-readable format. When an AI encounters a well-formatted list or table, it can parse the data and instantly understand the relationships between the items.

Here’s how to use them strategically:

Numbered Lists: These are perfect for sequences or step-by-step instructions. Think recipes or how-to guides. The numbers signal a clear order of operations.
Bulleted Lists: Use these for features, benefits, or key takeaways that don't have a specific order. They’re quick and easy to digest.
Tables: Nothing beats a table for comparing different options. A table comparing three software plans is far more useful to an AI (and a human!) than a dense paragraph trying to describe them.

By building your content with these elements, you’re doing more than just writing an article—you’re creating a structured database of information that AI models are designed to access. This is how you rank in AI Overviews and secure that coveted top spot.

Using Structured Data to Gain an Edge

AI models are incredibly powerful, but at their core, they’re information processors. To really stand out in AI-generated overviews, you need a mental shift. Stop thinking of your content as just words on a page and start treating it as a clean, organized data source for machines.

The better your information is structured, the easier it is for an AI to understand, trust, and ultimately cite in its answers.

This is where you go beyond just writing great prose. You need to actively translate your content into a language that machines speak fluently, and your best tool for that is structured data, specifically Schema.org markup. Think of it as adding clear, descriptive labels to your content that tell search engines exactly what each piece of information is and how it relates to everything else.

Making Your Content Machine-Readable with Schema

Without structured data, an AI is left to guess the context of your content. When you add it, you’re spelling everything out, removing any ambiguity and making your page a far more reliable source.

For instance, you could just write out a series of steps in a paragraph. Or, you could wrap them in HowTo schema. This explicitly tells the AI, "Hey, this is a step-by-step process designed to achieve a specific result." Suddenly, your instructions aren't just text; they're a structured, actionable guide that’s easy to process.

The same idea applies to questions and answers. By implementing FAQPage schema, you clearly separate your questions from their corresponding answers. This formatting makes your content a prime candidate for being pulled into an AI overview that directly addresses those user queries. Our guide on do rich snippets help seo explains how this can really boost your visibility.

I always tell people to start with FAQPage schema on their most important pages. It’s one of the easiest markups to get started with and often has a high payoff, since AI models are fundamentally built to answer questions. A practical example is to identify the top three questions your sales team gets and add an FAQ section with schema markup to your main product page answering them.

The Power of Unique Data and Clear Citations

Beyond schema, presenting unique data is a fantastic way to make your content indispensable. AI models synthesize information from many sources, so when they find a unique statistic or a compelling case study on your page, you become an essential piece of the puzzle.

But just having the data isn't enough—presentation is key. Tables are phenomenal for this. A well-organized table comparing features, pricing, or key metrics is infinitely more valuable to an AI than a dense paragraph trying to explain the same information.

Properly citing your sources is also non-negotiable. When you reference external data, link out to the original, authoritative source. It’s a powerful trust signal that shows the AI your information is well-researched and credible. This all starts with solid data hygiene, which you can learn more about in these best practices for data management.

Impact of Content Formatting on AI Visibility

The way you format your content has a direct impact on how easily an AI can parse and use it. A simple shift from unstructured text to a more organized format can make all the difference.

Content Format	Unstructured Example	Structured (AI-Friendly) Example	Likelihood of Inclusion
Lists	"Our services include SEO, content marketing, and PPC..."	Search Engine Optimization Content Marketing Pay-Per-Click Advertising	High
FAQs	"People often ask about our pricing. We offer three tiers..."	Q: What are your pricing plans? A: We offer three tiers...	Very High
Data/Stats	"The market grew significantly last year, reaching a new high."	"The market grew by 15% in 2023, reaching $1.2 billion in value."	High
Instructions	"First you need to open the app, then you go to settings..."	1. Open the application. 2. Navigate to the 'Settings' menu.	Very High

As you can see, even small formatting changes that provide clarity and structure can significantly improve your chances of being featured.

Why Data Signals Matter for AI Overviews

Integrating strong data points like adoption rates and financial investments provides powerful signals of topical authority. These numbers show that a topic has real-world relevance and impact.

For example, noting that as of 2024, about 35% of businesses have adopted some form of AI, or that global AI investments are projected to hit USD 200 billion by 2025, grounds your content in reality. Including statistics like these proves you have your finger on the market's pulse, making your content more authoritative and trustworthy.

By combining specific Schema.org markups with unique, well-presented data, you create content that’s not only valuable for people but also perfectly tuned for AI. You’re giving the models exactly what they need: clear, structured, and credible information that’s easy to understand and even easier to cite.

You can't optimize for AI Overviews without data. Doing so is really just taking an educated guess and hoping for the best. To actually know what's working, you need a solid feedback loop—a way to connect the dots between your content efforts and what happens in the real world. This is where a specialized tool stops being a "nice-to-have" and becomes absolutely essential.

This is exactly the gap LLMrefs was built to fill. It's an exceptional tool that helps you move from theory to practice by showing you precisely which of your pages are being cited, for which specific queries, and in what context. This data gives you the actionable insights you need to refine your strategy and start winning more visibility.

Turning Data into Actionable Insights

LLMrefs gives you a clear dashboard that basically serves as your command center for generative engine optimization. It pulls back the curtain on the "black box" of AI citations, giving you a direct line of sight into your performance.

The main dashboard gives you that top-level view of your visibility across different AI models, like this:

From here, you can quickly get a pulse on your overall performance, see which AI models seem to like your content, and spot trends over time. It’s the perfect starting point for digging deeper into your citation data.

Let's say you notice a competitor is constantly getting cited for a high-value keyword you're targeting. With a tool like LLMrefs, you can see the exact snippet of their content that the AI is pulling. This is your roadmap for outranking them.

You can then go back to your own content and create something more comprehensive, better structured, and clearer—all specifically designed to claim that spot.

LLMrefs provides the feedback loop that modern SEOs have been missing. It's an invaluable asset that bridges the gap between creating AI-friendly content and actually knowing if that content is being used. That clarity is what turns a one-off win into a repeatable, scalable strategy.

Without this kind of data, you're flying blind. You can update content and add structured data all day long, but you'll have no idea which of those changes are actually moving the needle.

Monitoring Your Key Performance Indicators

To know if you're succeeding, you have to track the right metrics. The core data points you should be monitoring are all interconnected and form the foundation of your performance analysis.

Here’s a practical breakdown of what you should be watching:

Citation Frequency: How often are your pages being cited? Seeing this number trend upward is a clear sign your strategy is paying off.
Share of Voice: What percentage of AI Overviews for your target keywords feature your brand? This is a fantastic metric for benchmarking your progress against competitors.
Query Context: For which specific questions or prompts is your content being used as a source? This tells you exactly what user intents you're successfully answering.
Cited Content Snippets: Which exact sentences or paragraphs are being pulled into the AI Overview? This is gold. It gives you invaluable insight into the phrasing and formatting the AI prefers.

A Practical Scenario for Growth

Let's walk through a real-world example to see how this works.

Imagine you run a blog about sustainable gardening. Using LLMrefs, you discover that your big article on "how to compost at home" is getting cited, but only for the query "what can you put in a compost bin?"

This is an incredibly powerful insight. It tells you that the section of your article listing compostable materials is perfectly optimized. The AI loves it. But the other parts of the article aren't getting any love.

Suddenly, your action plan is crystal clear:

Analyze the Successful Snippet: First, look closely at the part that's working. Is it a bulleted list? Is the language simple and direct? Take note of its structure.
Replicate That Structure: Now, apply that same successful formatting to other sections of the article, like your instructions on "how to start your compost pile."
Expand on Related Queries: Finally, add a new H3 for a related topic, like "Common Composting Mistakes to Avoid," and write the answer in a similarly concise and clear paragraph.

By using the data from LLMrefs, you can systematically improve your content based on what's already proven to work, not just on assumptions. This iterative process—track, analyze, optimize, repeat—is the most reliable way to consistently grow your footprint in AI-generated answers and secure your visibility for the long haul.

Common Questions About Ranking in AI Overviews

As you start fine-tuning your strategy for how to rank in AI Overviews, you're going to have questions. This is a new frontier, and a lot of the old SEO rules have new twists. Let’s walk through some of the most common questions I hear and give you some straight answers.

How Quickly Can I Get My Content Featured?

Honestly, it can happen a lot faster than climbing the traditional search rankings, but there are no guarantees. If you’ve got a site with solid authority and you publish a perfectly structured answer for a low-competition query, you might get cited surprisingly fast. These are the quick wins.

But the real game is about building sustainable visibility over the long haul. That means consistently boosting your site's E-E-A-T and establishing yourself as a go-to source for your entire topic area. Think of it as a two-speed process: quick features are great, but lasting success is what you're really after. This is exactly why a tool like LLMrefs is so useful—it helps you track those appearances from day one, providing immediate feedback on what's working so you can double down on successful tactics.

Do Backlinks Still Matter for AI Overviews?

Absolutely. In fact, the quality of your backlinks might matter more than ever before. A high-authority backlink is a huge signal of trust for AI models. A single link from a respected expert or a top-tier publication in your industry is worth more than a hundred low-quality links from sites nobody's ever heard of.

Think of it this way: quality links are a critical vote of confidence. They tell the AI that your content isn't just well-written, but that it's also trusted and validated by others in your field. This is the kind of foundational authority that AI models lean on when deciding which sources to cite in an overview.

The biggest mistake I see people make is ignoring structure. They write fantastic content, but they bury the key takeaways in long, dense paragraphs. AI models need clear signposts. If you don't use proper headings, lists, and Schema markup, you’re making it much harder for them to parse your content and feature it.

Should I Focus on Updating Old Content or Creating New Stuff?

Why not both? A balanced approach is almost always the most effective path forward.

Start with your existing winners—the cornerstone articles and pages that already pull in consistent traffic. This is your low-hanging fruit. Go back and update these pieces with structured data, sharpen the clarity, and drop in direct answers to common questions. You can get surprisingly fast results this way.

At the same time, you should be creating new content that targets conversational, long-tail queries. This lets you build articles that are perfectly optimized for AI Overviews right from the start. A good rule of thumb is to prioritize updating your most important articles first, then create new content to expand your authority. For a much deeper look at this strategy, check out our guide to Answer Engine Optimization.

This hybrid strategy ensures you're squeezing every bit of value from your current assets while also building a strong foundation for the future.

Ready to stop guessing and start winning in AI search? LLMrefs provides the critical data you need to see what's working, analyze competitor strategies, and systematically improve your visibility in AI Overviews. Get started with LLMrefs for free and turn insights into rankings.