Google AI Mode & AI Overviews: What They Mean for Your SEO in 2026

In 2026, zero-click searches have risen to 68%. Part of this is because of the evolving user behavior. But primarily, it can be attributed to the new AI search features.

 

People are still getting answers, but not via the traditional blue links anymore. AI mode has entered the equation, and it is here to change not just search but SEO as well. The search visibility doesn’t primarily lie in rankings now; it also centers on optimizing for AI search features as well.

 

We created this guide to help you stay visible in AI search. It covers:

 

• Google AI mode SEO & retrieval methods.

• The changes Google AI features are likely to bring to the search.

• How to optimize for better visibility in AI mode?

What is Google AI Mode?

AI mode is an AI-led search feature offering an end-to-end search experience. It works similarly to ChatGPT in practice. You search for something, and AI directly answers the query without you having to navigate through ten different URLs. Of course, the answer integrates inline links and citations for source references.

 

Recently, with the introduction of Gemini 3.5, the search box went through major changes. It was the first upgrade in 25 years and was led by the AI search features, including AI Mode. The most notable changes are:

 

• The search box now expands to allow longer queries. 

• You can also follow up on an AI Overview answer right from the SERPs.

• The search page transitions seamlessly into AI Mode with a follow-up post. 

Why was AI Mode introduced?

AI Mode started showing up in people’s search experiences in early 2025, the year Sundar Pichai encouraged his team to focus “on unlocking the benefits of this technology and solve real user problems.”

 

It was part of a plan to reclaim their position after LLMs like ChatGPT and Perplexity started claiming a big chunk of their traffic. Naturally, Google wanted to align its search experience with the evolving user behavior. And hence, they introduced AI Overviews and, shortly after, AI Mode. 

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

AI Mode is actually an extension of AI Overviews. When you search on Google, AI Overviews appear at the top of the results page, whereas AI Mode takes you to a different search window where you can continue a conversation via AIOs.

 

Here’s how it works in practice.

 

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Side-by-Side: AI Overviews vs. AI Mode

To put this difference into perspective, AI Mode reshapes the search session into a conversation, while AI Overviews replaces blue links with a synthesized answer above them.

How Does AI Mode Generate Answers?

Google’s AI features use two retrieval methods:

Retrieval Augmented Generation (RAG)

RAG technique is used to ensure answers are accurate and up-to-date. While Google’s AI Mode primarily relies on Gemini’s training data, it also integrates RAG technology to extract relevant pages from the search index in real time and use them as grounding material to generate responses. This is why your pages should be indexed and crawlable to earn citations.

 

Query fan-out 

When a user submits a query, Google’s AI doesn’t just search for that exact phrase. It retrieves from a set of concurrent, related queries to answer from a broader context window.

 

From Google’s own example: ‘..if the original user’s query is “how to fix a lawn that’s full of weeds”, fanout queries might include ‘”best herbicides for lawns”, “remove weeds without chemicals”, and “how to prevent weeds in lawn”.’

 

Simply put, it collects information from a number of related queries to synthesize an answer that serves the intent in a broader context. 

How AI Search Retrieval Differs From Organic Search

• Specific sections from content can be retrieved to answer a sub-question, independent of how the full page ranks.

• A single query fans out into numerous related searches behind the scenes before a response is generated.

• Content is pulled from multiple sources and synthesized into a single response.

• Individual search history and behavioral signals influence how the same query gets answered for two different users, while traditional results will almost always show the same listings.

• Being cited matters as much as being clicked. Content can influence a response without generating a measurable visit to the source page.

• Multi-modal system where queries can trigger text, images, videos, and audio in the same tab. 

How is Google AI Mode Impacting SEO?

With Google’s AI Mode getting a huge chunk of space in the SERPs, it’s safe to say organic search has been altered irrevocably. For brands to retain visibility in the new search era, it’s important to understand how Google’s AI features affect organic traffic so they can align their SEO decisions based on evolving search behaviors.

 

For reference, position one CTR has dropped by 34.5% for queries resulting in an AI Overview. Users are much less likely (8%) to click on a blue link for queries with an AI summary.

 

But all that is just scratching the surface. It’s also important to understand that Google’s AI features behave differently from traditional search ranking systems. While the core retrieval principles might be the same, SEO in the AI era has certainly evolved. 

Industry-Wise Impact

Here are some common stats to highlight the highest and lowest impact of Google AI Mode and AIOs on specific industries.

 

• AI Overviews show up for 82% of B2B tech queries.

• Healthcare queries get an 88% share of AI summaries.

• Education queries trigger AI features for 83% of the time

• AI Overviews trigger far less frequently for local searches and navigational queries

   

Source: SEO Sherpa

How To Appear In AI Mode & AI Overviews

Getting down to the important question, which SEO strategies should we adopt to get cited in Google AI Mode and AI Overviews? While the standard rules of quality content and brand authority apply here, some adaptations have to be made to conform to the new search landscape.

 

Some ranking factors in 2026 impact Google AI mode visibility more than others. Let’s review what they are.

The content side of things—what works and what doesn’t 

AI Mode rewards the same thing as traditional SERPs: good writing and helpful content that matches user intent. Here is a list of key practices when optimizing content for visibility in the AI search feature:

• Share real experience, genuine expertise, or a perspective that goes beyond the obvious. An expert’s review on a niche topic, an original research study, or a blog that doesn’t just provide information but integrates an element of personalization is a great way to get your content noticed. 

• Structure it so that it’s easier for a human to read. Clear headings, logical flow, and well-written paragraphs combined with other content formats (images, videos, etc.) when they are helpful.

• Don’t try to cover every search variation. Writing a separate page for every way someone might phrase a query is against Google’s spam policies, and it doesn’t work. A single, yet thoroughly written page on a topic will outperform a dozen thin ones any day.

• Don’t misuse AI tools to mass-produce low-quality pages that offer no real value to users. Any content produced using AI should conform to Google’s standards for helpful, reliable, and people-first content. 

• Remove any duplication across the site to make sure similar pages do not dilute page authority or waste crawl budget. 

What doesn’t work

Two things that don’t work according to Google’s official guidelines on AI optimization:

• Content Chunking – Breaking content into shorter paragraphs or sentences. Google doesn’t need bite-sized pieces to understand your page. The content length should reflect your topic and your audience’s capability to comprehend it.

• Rewriting content for AI – Changing tone, structure, or topics solely to help AI understand it is not a smart strategic move. Google explicitly mentions, “You don’t need to write in a specific way just for generative AI search.” 

The importance of E-E-A-T and original research

Google’s AI prefers quality content, and its algorithm system assesses quality based on EEAT. Ahrefs confirms this with the statement:

“EEAT is an acronym of a framework Google uses to evaluate content quality.”

Any content demonstrating Experience, Expertise, Authoritativeness, and Trustworthiness automatically has a higher likelihood of getting featured in the SERPs. And that includes AI features as well. It can pick up on signals that a human wrote something from lived experience, not just from research.

Here are some tactics that increase citation likelihood:

• Named authors with verified credentials.

• Original data and proprietary research. 

• Specific, verifiable claims. 

• Community and platform authority. 

What significance do communities carry in this regard? Reddit holds 21% of AIO citations. AI overviews and AI mode also frequently cite LinkedIn and other communities, making this strategy critical when optimizing for AI mode. 

Leverage Images & Videos

Google’s generative AI search features actively pull in relevant images and videos alongside web page links, which means your visuals now have their own shot at surfacing in search results. Google also pointed this out in its AI optimization guide.

 

“…our generative AI search features can bring in relevant images and video, which means more opportunities for your website to appear beyond web page links.”

 

And if you’re already following Google’s image SEO best practices and video SEO guidelines, you might just be optimizing for generative AI search as well. So supporting written content with strong visuals isn’t extra work; it’s more content for AI to cite.

Redirect Focus to Brand Mentions

Mentions from authentic sources are critical and help amplify a brand’s voice across various search surfaces, including AI-generated responses. A study by AirOps highlights that 85% of AI mentions come from external domains, while only 13.2% of mentions come directly from the brand’s domain. The study offers a clear correlation between AI search visibility and brand mentions.

 

There’s one condition, though. The mentions should come from authentic sites that wish to link to you because of the quality of your content. Inauthentic mentions have no value for AI search visibility. Google addresses this in the following words:

 

“...seeking inauthentic “mentions” across the web isn’t as helpful as it might seem.”

 

Note that earning brand mentions differs from traditional PR or link building, as it involves naturally earning recognition across the web without a direct link placement.

Technical SEO: a good hack for AI SEO 

When most people think about optimizing for Google’s AI features, they jump straight to content. However, no amount of great writing will help if Google can’t find, crawl, and index your pages in the first place. 

Technical SEO determines whether your content is even eligible for AI citations.

And here’s how you can optimize for it.

• Start with indexability. A page must be crawlable and indexable, the two basic eligibility criteria to appear in Google Search, before it can even be considered for generative AI features. Also, make sure your pages aren’t blocked by robots.txt.

• Apply proper semantic HTML as it helps screen readers and other tools navigate your pages. It’s a good practice, but there’s no need to overdo it because Google crawlers can also read invalid HTML. 

• If your site relies on JavaScript frameworks, follow established JavaScript SEO best practices. Google can process JavaScript content as long as it isn’t blocked, but JS-heavy sites do add a layer of technical complexity worth addressing. Ensure critical content is pre-rendered or server-side rendered. Client-side rendering adds delays to indexing.

• Page experience remains relevant. Factors such as fast speed, mobile-friendly design, and a clean layout where users can easily identify your main content all contribute to how Google evaluates your pages.

Bonus Point

Schema markup helps in specific cases (reviews, FAQs, how-tos), but it’s not required for AI citation. Focus on foundational SEO first: crawlability, indexability, and quality content. If you have resources remaining, implement schema for rich results.

How to Measure AI Data on GSC

Google confirmed in a June 2026 report that you can now view search data for AI Overviews and AI Mode via Google Search Console. This gives you direct visibility into how often your content is being cited and how many impressions it’s earning through these AI-powered features.

To isolate AI search data, follow these steps:

1. Open the Performance report in GSC.

2. Under Search Results, find Generative AI. This will isolate data for AI Overviews and AI Mode only. 

3. At the moment, you can only view impressions. Clicks, ranks, and CTR are not part of this report. 

4. You can narrow down your search by pages, devices, countries, and dates. 

Note that this feature is only in the testing phase and may take some time to be widely available. However, if it pans out, the data is quite promising and will provide a whole new analytics stream for AI mode and AI overviews. 

It will provide critical visibility into AI citation performance: a measurement gap that currently exists. 

And that’s all there is to know about Google AI mode and AI overview optimization at the moment. The foundation stays the same: quality content, technical excellence, and authentic authority. Focus there first, then adapt as Google’s AI features change.

 

As the strategies evolve, make sure you’re staying updated and following through for best results.