How To Track Ai Mode in GSC

Google Search Console for AI Search Tracking

The current version of Google Search Console provides aggregated data about impressions, clicks, and position data in one place.

What an AI Search Console Could Look Like

It will tell us what GSC already does, but also integrate advanced analytics to answer questions like:

• Which URLs on your website are indexed for AI search?
• What type of prompts or follow-up prompts is your website ranking for?
• How many times has your website been quoted, referenced, or cited in the AI answers?

While ASC is merely a manifestation at the moment, GSC remains a reality. And we can use it to extract AI search analytics.

How to Find AI Queries in Google Search Console

We’ve already established that it’s important to track your AI visibility to create a sound optimization strategy. But GSC doesn’t have a direct feature that separates your AI queries from traditional ones.

No need to fret, though, because there’s a way around that.

But first, What Makes AI Prompts Different?

There are a number of characteristics of AI prompts that distinguish them from traditional search terms.

For example:

• They’re generally longer (mostly over 10 words).
• Most start with a question.
• They are conversational queries carrying a higher probability of follow-up searches.

So, how to analyze search queries in GSC using the roundabout route? Here are a few techniques.

Filter AI Queries by Question Type

According to multiple sources, 8% of search queries are questions. A big chunk of the searchers asking these questions use AI search tools, as LLMs offer a more dynamic experience and customize answers based on your historical interactions.

Narrowing down your queries by question type is a great way to tap into possible questions your audience is asking on AI search engines.

Here’s what you have to do.

• Go to the Performance Report in the Google Search Console dashboard.
• Click on the “Add Filter” option in the top left corner, and select “Query.”
• From the drop-down menu, select Custom (regex), and make sure the tab on the left says “matches regex.”
• Filter for queries containing words that begin with question terms like how, what, why, who, can, is, or does. For this, use the following regex code.
• Click “Apply” to generate a list of question-based search terms.

With this step, you’re essentially isolating questions your potential audience is already asking.

Filter AI Search Queries by Word Count

AI prompts aren’t like your standard search queries that almost never go over 10 words.

So, if you think about it, filtering queries containing more than ten words is data redirecting from alternative search sources, aka, AIOs, AI Mode, or generative AI engines.

Here’s a step-by-step breakdown on how to track AI search prompts using word count as a reference:

• In the GSC Performance Report, find the “Add Filter” option.
• Select “Query,” and pick Custom (regex) from the drop-down menu.

Plug in this regex code: 

^(?:\S+\s+){9,}\S+$

• Click Apply to see search queries that contain more than ten words.

This process helps identify long-tail queries in GSC, which often overlaps with the conversational style in AI prompts. Once extracted, you can use the data for AI prompt engineering, creating content ideas, or generating topic clusters.

Filter Transactional AI Queries in GSC

AI isn’t just a search engine divulging information to people searching for answers; it’s also a decision driver. Yes, it can influence consumer preferences and purchase decisions.

A report by the University of Virginia highlights that nearly 60% of consumers use AI to help them shop.

So, your potential customers are probably using generative AI tools to search for products you sell. And knowing what type of prompts they use could help tap into more traffic and revenue opportunities.

To filter out just the transactional queries in Google Search Console, use the same method we did above when filtering for questions. But instead of sorting by how, when, where, you’ll filter for terms like buy, purchase, price, cost, quote, and order. Use this regex code.

Can You Really See AI Mode and AI Overview Data in GSC?

The performance report in Google Search Console combines all clicks from organic listings, AI Overviews, and AI Mode.

The Google documentation confirmed in the latest update that you can review three search factors in the GSC performance report:

• Your impressions
• Your clicks
• And ranking positions

And this data isn’t relevant to traditional blue links only; it also merges Google’s AI search features. So, the clicks and impressions you see on your dashboard include any clicks or impressions from AI Mode and AI Overviews as well.

While AI Mode follows the same methodology for positions as traditional search, AIO positions are all considered the same, and there are no rankings allocated.

The document mentions:

“An AI Overview occupies a single position in search results, and all links in the AI Overview are assigned that same position.”

The Problem: There Is Now a Blind Spot in Google Search Console

Google Search Console Merges AI Overview Impressions

An AI Overview will be included in your total count when it shows up on your keyword, and it will not be separated into the category of AI impressions.

This combined data is also available in the Search Console API, so when you query the number of impressions, you get a figure that combines both the traditional results with AI Overview appearances.

This poses difficulties to SEO professionals who produce reports. The dashboards indicate 10,000 impressions but cannot determine the number that dealt with AI Overviews.

Why SEOs Cannot Isolate AI Overview Visibility

AI Overview presence is not a dimension in Search Console. You can filter by query, page, country, and device, but not by the presence of an AI Overview.

More importantly, when your content is mentioned as a source in an AI Overview, it is not tracked in Search Console. The content you provide might be the first reference point of the AI in Google, and it might be the one that causes brand awareness and authority cues, yet you would never find out about it in Search Console data.

According to the industry reports, AI Overviews refer to three to five sources on average. These citations are a precious real estate in search results that Search Console does not consider.

This Introduces Reporting Loopholes to Agencies and In-house Teams. ROI Analysis is Incomplete.

AI Search Optimization Is Becoming a Two-Track SEO Strategy

In 2026, SEO and keyword research could be a two-track sport. We continue to have the old-fashioned clicks and conversions in organic search, and we are keeping pace with AI-generated prompts to know what people are asking so we can retain any gaps in our content and hopefully, be listed in AI answers, as well.

Google has rolled out AI Mode, a new feature which is set to become the default search engine. We’ve all read about how Google AI Mode applies advanced reasoning and a query fan-out algorithm to rank web pages and generate detailed answers in their AI-powered reply.

But what is it, how do we look in these AI-generated answers? The best place to begin is to determine how people are searching in these tools.

Whether you like it or not, a lot of individuals are utilizing Google AI Mode to find information, pose follow-up questions and receive the answers that they require. This includes finding products and services to book.

The big question? So, what exactly are people asking AI Mode and other generative AI tools like ChatGPT?

Naturally, there are SEO tools that imitate AI prompts to discover whether your site is present.

Using Google Search Console to Discover AI Prompt Queries

The only tool that can give you real search queries that led to clicks and impressions on your site is Google Search Console.

In this post, I will provide a basic Query Filter formula that you can use to view the actual search queries and discussions that elicited AI Overview or AI Mode results, with your site being shown.

Quick Method to Filter AI Queries in GSC

To the SEO-savvy marketers who desire the trimmed version. Here’s what you need to do.

Filter your Google Search Console keyword queries for 10+ words. These are the longer terms on which you will find AI-driven searches that are full of context, and are linked to clicks and impressions your site already appears on in Google.

• Open the Search results report.
• Add filter, Query.
• Choose Custom (regex).
• Copy and paste the following formula. (\b\w+\b\s){10,}
• Apply, and look through the longer searches.

Step-by-Step Guide to Tracking AI Search Prompts

Step 1: Open the Search Results Report

Open your browser and sign into the Google account that has access to your site’s Search Console property.

In the left navigation, find the Search Results report.

Click it.

Now you’re looking at your search performance report that includes:

• Total clicks
• Total impressions
• Average CTR
• Average position

We want to focus on the Queries table.

This table is a goldmine. These are the exact keyword searches that led to real clicks and impressions on your site.

At this point, you might see a lot of short-tail keyword queries. Totally normal. These are the keywords you’re ranking for in traditional search results.

Now we need to add a filter.

Step 2: Apply a Regex Filter for Long Queries

Look near the top of the report for the filter controls.

Now do this:

• Select Add filter.
• Choose Query.
• In the match type options, select Custom (regex)
• Paste in this custom formula that filters for queries with at least 10 words.

(\b\w+\b\s) {10,}

• Hit Apply.

That’s it.

Once you apply it, your query list updates, and now you’re seeing longer searches with at least 10 words. These are the detailed, conversational queries that people have asked Google’s AI Mode, and where your website appeared!

Step 3: Analyze AI-Driven Search Queries

The custom regex filter shows us queries with 10 words or more. These are longer queries that include more context and information. If your website showed up in an AI Mode response, there would be impressions and click data here.

Personally, I’m fascinated by how detailed these prompts are.

These are full questions filled with intent.

Like “claire is analyzing her website’s core web vitals and notices that lcp is occurring at 10 seconds, which is much longer than what google recommends. which of the following elements could be contributing to slowing down claire’s page?”

Or “raquel is working on a technical seo audit for a new client who recently decided to move their website from http to https. when starting her audit, raquel notices that some http pages were never redirected to the https pages, which is now causing issues for the site in search. however, this client is very resistant to the idea of implementing more redirects, since they’ve heard that this can lead to a drop in their search performance. how should raquel approach this situation with her client?”

Step 4: Improve Content Using AI Query Insights

This is an opportunity to create new content pages, or to beef up your existing content!

• Add an FAQ section: Take the best long questions and answer them directly on the page that already ranks for the topic.
• Rewrite headings to match real phrasing: If people keep searching a specific way, mirror that language in an H2 or H3.
• Expand a thin section: If a long query asks about a subtopic, you barely mention, beef up that section.
• Create a supporting blog post: If the query is too specific to squeeze into an existing page, it might deserve its own focused article.

Why Traditional Keyword Research Is No Longer Enough

Over the years, search engine optimization experts have been optimizing content based on exact-match keywords and short-tail phrases. However, AI search behavior is different.

The search engines have become conversational with the users. They pose follow-up questions, narrow searches intuitively, and demand context-specific and detailed answers.

AI Search Queries Contain More Context

In contrast to the old-fashioned searches, AI suggestions can include:

• Full sentences
• Multiple conditions
• Specific problems
• Comparative intent
• Contextual explanations.

For example, instead of searching:

“Best CRM software”

Users may now ask:

What is the most recommended CRM software to use in a small agency with remote sales teams, with a small budget?

This opens up completely new possibilities of content optimization.

Conversational queries are longer and show more search intent, which assists marketers to know precisely what users want to resolve.

AI Queries Reveal User Intent More Clearly

Among the largest advantages of monitoring AI prompts is that they reveal very narrow-purpose intent.

The old-fashioned data of keywords can inform you that somebody has searched on technical SEO audit.

However, the real issue is shown in AI-style queries:

What is the best way to conduct a technical SEO audit when switching HTTP to HTTPS without rankings loss?

Such detailing assists content teams to develop more practical, focused pages that are closer to the real-life user issues.

The Rise of AI Visibility Optimization

SEO is no longer just about ranking in blue links.

Brands now need to optimize for AI visibility.

This involves producing content in a form that can be easily comprehended, summarized, and referenced by AI systems in generated responses.

AI Visibility Is Becoming a New SEO Metric

Marketers will probably measure in the near future:

• AI citation frequency
• AI Overview appearances
• Conversational query coverage
• Follow-up prompt visibility
• AI-assisted conversion paths

The problem is that the current tools still do not provide detailed reporting of these metrics.

The current state of Google Search Console combines AI-related impressions with conventional organic data, which leaves significant gaps in the eyes of marketers who want to accurately gauge performance.

Due to this shortcoming, long-tail query analysis and regex filtering have become significant workarounds to find AI-based searches.

How AI Prompt Tracking Improves Content Strategy

AI prompts tracking is not only handy in analytics. It also enhances the creation and optimization of content directly.

Discover New Content Opportunities

Long conversational questions tend to reveal the questions that your site is hardly answering.

These loopholes are avenues to:

• Create new landing pages
• Expand blog content
• Add FAQs
• Improve topical authority
• Construct topic clusters in support.

The better your content can respond to real conversational questions, the more likely it is to be cited in AI-generated responses.

Improve Existing Pages

Existing content can also be reinforced by AI query insights.

As an example, when users are searching with some phrasing repeatedly, you can:

• Rewrite headings using natural language
• Add direct-answer sections
• Include more contextual examples
• Expand weak sections
• Improve semantic relevance

This will make your pages more in line with the way modern users will use AI-powered search engines.

The Future of SEO Will Be Conversational

The replacement of SEO by AI search is not happening. It’s expanding it.

The old-fashioned organic rankings are not disappearing, yet conversational visibility is gaining significance.

With the adoption of AI search steadily increasing, companies that comprehend how users formulate queries, pose follow-up questions, and engage with generative search engines will have a significant edge over their rivals who use only the old-fashioned methods of using keywords.

The earlier marketers start monitoring AI queries in Google Search Console, the quicker they can adjust their search engine optimization strategies to the future of search.