<div><img width="1536" height="1024" src="https://searchengineland.com/wp-content/seloads/2026/05/ChatGPT-ads-conversion-tracking.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" fetchpriority="high" srcset="https://searchengineland.com/wp-content/seloads/2026/05/ChatGPT-ads-conversion-tracking.png 1536w, https://searchengineland.com/wp-content/seloads/2026/05/ChatGPT-ads-conversion-tracking-768x512.png 768w" sizes="(max-width: 1536px) 100vw, 1536px" /></div>The latest OpenAI rollout brings ROI-focused campaign optimization and conversion tracking directly into ChatGPT ads.

<div><img width="1536" height="1024" src="https://searchengineland.com/wp-content/seloads/2026/05/ChatGPT-ads-conversion-tracking.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/05/ChatGPT-ads-conversion-tracking.png 1536w, https://searchengineland.com/wp-content/seloads/2026/05/ChatGPT-ads-conversion-tracking-768x512.png 768w" sizes="(max-width: 1536px) 100vw, 1536px" /></div>
<p>OpenAI confirmed it will begin rolling out conversion-optimized ad campaigns in early June, marking the clearest signal yet that the company is building a performance advertising ecosystem around ChatGPT.</p>



<p><strong>Why we care.</strong> The announcement validates reporting published <a href="https://searchengineland.com/openai-is-preparing-conversion-focused-ads-for-chatgpt-478738">yesterday by The Information that OpenAI was preparing conversion-focused ads</a>, tracking infrastructure and performance-based measurement tools for advertisers.</p>



<p><strong>What’s happening. </strong>In new communications sent to advertisers, OpenAI said early access to conversion-optimized campaigns will begin in June for accounts that set up either the OpenAI Pixel or Conversions API in advance.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="617" height="629" src="https://searchengineland.com/wp-content/seloads/2026/05/ChatGPT-conversion-tracking.png" alt="" class="wp-image-478844"/></figure>



<p>According to the company:</p>



<ul class="wp-block-list">
<li>advertisers who configure conversions by June 1 will receive early access by June 5,</li>



<li>and advertisers can already begin tracking conversions inside Ads Manager today.</li>
</ul>



<p>The system allows advertisers to measure actions driven by ads after users interact with campaigns.</p>



<p><strong>Between the lines. </strong>The rollout confirms OpenAI is building infrastructure that closely resembles traditional performance advertising platforms like Google and Meta.</p>



<p>The OpenAI <a href="http://JavaScript Pixel">Pixel</a> enables website activity tracking after ad interactions, while the Conversions API allows advertisers to send first-party conversion data directly back into OpenAI’s systems.</p>



<p>That setup gives OpenAI the ability to optimize campaigns toward measurable business outcomes rather than simple engagement metrics.</p>



<p><strong>What to watch.</strong> The success of OpenAI’s advertising ambitions may depend heavily on measurement accuracy and advertiser trust.</p>



<p>As browser restrictions and privacy changes continue weakening traditional tracking methods, <a href="https://developers.openai.com/ads/conversions-api">OpenAI’s Conversions API</a> could become increasingly important for proving campaign performance and attribution inside AI-driven ad experiences.</p>


OpenAI confirmed it will begin rolling out conversion-optimized ad campaigns in early June, marking the clearest signal yet that the company is building a performance advertising ecosystem around ChatGPT.
Why we care. The announcement validates reporting published yesterday by The Information that OpenAI was preparing conversion-focused ads, tracking infrastructure and performance-based measurement tools for advertisers.
What’s happening. In new communications sent to advertisers, OpenAI said early access to conversion-optimized campaigns will begin in June for accounts that set up either the OpenAI Pixel or Conversions API in advance.




According to the company:
advertisers who configure conversions by June 1 will receive early access by June 5,
and advertisers can already begin tracking conversions inside Ads Manager today.
The system allows advertisers to measure actions driven by ads after users interact with campaigns.
Between the lines. The rollout confirms OpenAI is building infrastructure that closely resembles traditional performance advertising platforms like Google and Meta.
The OpenAI Pixel enables website activity tracking after ad interactions, while the Conversions API allows advertisers to send first-party conversion data directly back into OpenAI’s systems.
That setup gives OpenAI the ability to optimize campaigns toward measurable business outcomes rather than simple engagement metrics.
What to watch. The success of OpenAI’s advertising ambitions may depend heavily on measurement accuracy and advertiser trust.
As browser restrictions and privacy changes continue weakening traditional tracking methods, OpenAI’s Conversions API could become increasingly important for proving campaign performance and attribution inside AI-driven ad experiences.

The latest OpenAI rollout brings ROI-focused campaign optimization and conversion tracking directly into ChatGPT ads.

OpenAI confirms conversion-focused ads are coming to ChatGPT

<div><img width="1920" height="1097" src="https://searchengineland.com/wp-content/seloads/2026/05/google-ai-boxes-1920.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/05/google-ai-boxes-1920.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/05/google-ai-boxes-1920-768x439.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/05/google-ai-boxes-1920-1536x878.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Google says these are "new ways to help you find high-quality content and firsthand perspectives."

<div><img width="1920" height="1097" src="https://searchengineland.com/wp-content/seloads/2026/05/google-ai-boxes-1920.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/05/google-ai-boxes-1920.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/05/google-ai-boxes-1920-768x439.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/05/google-ai-boxes-1920-1536x878.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Google is bringing the preferred sources feature to its AI search experiences, specifically AI Mode and AI Overviews. Plus, Google is also adding a perspectives carousel and the highly cited labels to the results.</p>



<p><strong>Preferred sources in AI Mode and AI Overviews. </strong>Google is bringing preferred sources to its AI search experiences, specifically AI Mode and AI Overviews. Duncan Osborn, Product Manager, Google Search, <a href="https://blog.google/products-and-platforms/products/search/original-high-quality-content-search">said</a>, &#8220;you’ll be able to easily spot links in AI responses from the sources you’ve already selected.&#8221; </p>



<p>We actually saw Google <a href="https://www.seroundtable.com/google-ai-mode-preferred-sources-label-41347.html">testing this</a> just about a week ago but here is the final version:</p>



<figure class="wp-block-image size-full"><img decoding="async" width="2048" height="1386" src="https://searchengineland.com/wp-content/seloads/2026/05/Zoos-scaled.png" alt="" class="wp-image-478781" srcset="https://searchengineland.com/wp-content/seloads/2026/05/Zoos-scaled.png 2048w, https://searchengineland.com/wp-content/seloads/2026/05/Zoos-768x520.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/Zoos-1536x1039.png 1536w" sizes="(max-width: 2048px) 100vw, 2048px" /></figure>



<p>There will be a preferred sources label within the AI results that make those links stand out more to users. </p>



<p><a href="https://searchengineland.com/google-search-tests-preferred-sources-for-top-stories-457640">Preferred sources</a> is now available <a href="https://searchengineland.com/google-preferred-sources-now-works-for-all-languages-476051">globally and in all languages</a>.  Google said users have selected over 345,000 unique sources and people are twice as likely to click through to a Preferred Source. For more details on how to enable preferred sources, see <a href="https://developers.google.com/search/docs/appearance/preferred-sources">this documentation</a>.</p>



<p><strong>Perspectives carousel. </strong> Google will show a new carousel for some searchers that Google thinks the searcher wants to dig deeper on a developing topic they are into. Google said there is a new prominent carousel, which will also highlight your Preferred Sources. This will make timely articles more visible on a wider range of queries, Google added.</p>



<figure class="wp-block-image size-full is-resized"><img decoding="async" width="924" height="1933" src="https://searchengineland.com/wp-content/seloads/2026/05/Super-El-Nino.png" alt="" class="wp-image-478782" srcset="https://searchengineland.com/wp-content/seloads/2026/05/Super-El-Nino.png 924w, https://searchengineland.com/wp-content/seloads/2026/05/Super-El-Nino-768x1607.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/Super-El-Nino-734x1536.png 734w" sizes="(max-width: 924px) 100vw, 924px" /></figure>



<p>Plus, searchers may also see a similar carousel with helpful perspectives from online discussions, forums, and social media.</p>



<figure class="wp-block-image size-full is-resized"><img decoding="async" width="924" height="1933" src="https://searchengineland.com/wp-content/seloads/2026/05/Chonkers.png" alt="" class="wp-image-478784" srcset="https://searchengineland.com/wp-content/seloads/2026/05/Chonkers.png 924w, https://searchengineland.com/wp-content/seloads/2026/05/Chonkers-768x1607.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/Chonkers-734x1536.png 734w" sizes="(max-width: 924px) 100vw, 924px" /></figure>



<p>This is rolling out in AI Mode and AI Overviews as well.</p>



<p><strong>Highly cited label. </strong><span>Google is also expanding the&nbsp;<a href="https://searchengineland.com/google-launches-new-highly-cited-label-in-search-and-improved-about-results-for-rapidly-evolving-topics-383306" target="_blank">highly cited label</a>&nbsp;to more web article links on the search results page, the company announced.</span> Plus, Google will indicate when an article explicitly references a Highly Cited source.  Google said, &#8220;makes it easy to spot articles that many other stories have cited, helping you find the primary reporting that other articles are referencing.&#8221;</p>



<p>This is expanding across Google Search and is not specific to AI Mode or AI Overviews.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="1920" height="527" src="https://searchengineland.com/wp-content/seloads/2026/05/Schoolboard.png" alt="" class="wp-image-478785" srcset="https://searchengineland.com/wp-content/seloads/2026/05/Schoolboard.png 1920w, https://searchengineland.com/wp-content/seloads/2026/05/Schoolboard-768x211.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/Schoolboard-1536x422.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></figure>


Google is bringing the preferred sources feature to its AI search experiences, specifically AI Mode and AI Overviews. Plus, Google is also adding a perspectives carousel and the highly cited labels to the results.
Preferred sources in AI Mode and AI Overviews. Google is bringing preferred sources to its AI search experiences, specifically AI Mode and AI Overviews. Duncan Osborn, Product Manager, Google Search, said, “you’ll be able to easily spot links in AI responses from the sources you’ve already selected.” 
We actually saw Google testing this just about a week ago but here is the final version:




There will be a preferred sources label within the AI results that make those links stand out more to users. 
Preferred sources is now available globally and in all languages.  Google said users have selected over 345,000 unique sources and people are twice as likely to click through to a Preferred Source. For more details on how to enable preferred sources, see this documentation.
Perspectives carousel.  Google will show a new carousel for some searchers that Google thinks the searcher wants to dig deeper on a developing topic they are into. Google said there is a new prominent carousel, which will also highlight your Preferred Sources. This will make timely articles more visible on a wider range of queries, Google added.




Plus, searchers may also see a similar carousel with helpful perspectives from online discussions, forums, and social media.




This is rolling out in AI Mode and AI Overviews as well.
Highly cited label. Google is also expanding the highly cited label to more web article links on the search results page, the company announced. Plus, Google will indicate when an article explicitly references a Highly Cited source.  Google said, “makes it easy to spot articles that many other stories have cited, helping you find the primary reporting that other articles are referencing.”
This is expanding across Google Search and is not specific to AI Mode or AI Overviews.

Google says these are "new ways to help you find high-quality content and firsthand perspectives."

Google AI Overviews & AI Mode gain preferred sources, plus new perspectives carousel and highly cited labels

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/02/In-Google-Ads-automation-everything-is-a-signal-in-2026.jpg" class="attachment-large size-large wp-post-image" alt="In Google Ads automation, everything is a signal in 2026" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/02/In-Google-Ads-automation-everything-is-a-signal-in-2026.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/02/In-Google-Ads-automation-everything-is-a-signal-in-2026-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/02/In-Google-Ads-automation-everything-is-a-signal-in-2026-1536x864.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Google Ads will begin deleting over 37 months reporting data in June unless advertisers export it beforehand.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/02/In-Google-Ads-automation-everything-is-a-signal-in-2026.jpg" class="attachment-large size-large wp-post-image" alt="In Google Ads automation, everything is a signal in 2026" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/02/In-Google-Ads-automation-everything-is-a-signal-in-2026.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/02/In-Google-Ads-automation-everything-is-a-signal-in-2026-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/02/In-Google-Ads-automation-everything-is-a-signal-in-2026-1536x864.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Google is introducing a new Google Ads data retention policy that will limit how long advertisers can access historical reporting data inside the platform and APIs.</p>



<p><strong>Why we care.</strong> Advertisers relying on long-term historical performance data for reporting, forecasting or modeling may need to update their data storage strategies before older records become inaccessible.</p>



<p><strong>What’s happening. </strong>Beginning June 1st, Google Ads reporting data for periods shorter than one month — including hourly, daily and weekly reporting data — will only remain available for 37 months.</p>



<p>Monthly, quarterly and annual reporting data will remain accessible for 11 years.</p>



<p>After those retention windows expire, the data will no longer be accessible through either the Google Ads interface or APIs.</p>



<p><strong>Between the lines. </strong>Reach and frequency metrics will have even shorter retention limits.</p>



<p>Metrics including:</p>



<ul class="wp-block-list">
<li>unique users,</li>



<li>average impression frequency per user,</li>



<li>7-day and 30-day average impression frequency,</li>



<li>and frequency distribution metrics</li>
</ul>



<p>…will only remain available for three years.</p>



<p><strong>The bigger picture.</strong> The change could create new pressure for advertisers, agencies and analytics teams to export and warehouse historical Google Ads data before it expires.</p>



<p>Long-term trend analysis, benchmarking and media mix modeling often rely on years of granular historical data that may no longer remain accessible directly inside Google Ads.</p>



<p><strong>What to watch.</strong> Advertisers using external BI tools, internal dashboards or custom reporting systems may increasingly need automated data export pipelines to preserve reporting continuity before retention limits begin taking effect in 2026.</p>



<p><strong>Dig Deeper. </strong><a href="https://support.google.com/google-ads/answer/15188209?hl=en">Google Ads Data Retention Policy</a><br><br>


Google is introducing a new Google Ads data retention policy that will limit how long advertisers can access historical reporting data inside the platform and APIs.
Why we care. Advertisers relying on long-term historical performance data for reporting, forecasting or modeling may need to update their data storage strategies before older records become inaccessible.
What’s happening. Beginning June 1st, Google Ads reporting data for periods shorter than one month — including hourly, daily and weekly reporting data — will only remain available for 37 months.
Monthly, quarterly and annual reporting data will remain accessible for 11 years.
After those retention windows expire, the data will no longer be accessible through either the Google Ads interface or APIs.
Between the lines. Reach and frequency metrics will have even shorter retention limits.
Metrics including:
unique users,
average impression frequency per user,
7-day and 30-day average impression frequency,
and frequency distribution metrics
…will only remain available for three years.
The bigger picture. The change could create new pressure for advertisers, agencies and analytics teams to export and warehouse historical Google Ads data before it expires.
Long-term trend analysis, benchmarking and media mix modeling often rely on years of granular historical data that may no longer remain accessible directly inside Google Ads.
What to watch. Advertisers using external BI tools, internal dashboards or custom reporting systems may increasingly need automated data export pipelines to preserve reporting continuity before retention limits begin taking effect in 2026.
Dig Deeper. Google Ads Data Retention Policy

Google Ads will begin deleting over 37 months reporting data in June unless advertisers export it beforehand.

Google Ads will start deleting historical reporting data after set retention periods

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/02/Why-Google-Ads-auctions-now-run-on-intent-not-keywords.jpg" class="attachment-large size-large wp-post-image" alt="Why Google Ads auctions now run on intent, not keywords" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/02/Why-Google-Ads-auctions-now-run-on-intent-not-keywords.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/02/Why-Google-Ads-auctions-now-run-on-intent-not-keywords-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/02/Why-Google-Ads-auctions-now-run-on-intent-not-keywords-1536x864.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Google is introducing Real-Time Policy Reviews to speed up ad approvals with instant feedback during campaign creation.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/02/Why-Google-Ads-auctions-now-run-on-intent-not-keywords.jpg" class="attachment-large size-large wp-post-image" alt="Why Google Ads auctions now run on intent, not keywords" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/02/Why-Google-Ads-auctions-now-run-on-intent-not-keywords.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/02/Why-Google-Ads-auctions-now-run-on-intent-not-keywords-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/02/Why-Google-Ads-auctions-now-run-on-intent-not-keywords-1536x864.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Google is rolling out Real-Time Policy Reviews, a new system designed to dramatically speed up ad approvals by bringing policy checks directly into the ad creation process.</p>



<p><strong>What’s happening.</strong> The feature is currently available for Responsive Search Ads and will expand to additional campaign types later this year.</p>



<p>Instead of waiting for ads to enter a separate review queue after submission, advertisers now receive instant policy feedback while building ads inside Google Ads.</p>



<p>The system checks for issues in two stages.</p>



<p>During ad creation, advertisers receive real-time editorial checks for issues such as typos, capitalization problems or destination errors before saving the ad.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="640" height="568" src="https://searchengineland.com/wp-content/seloads/2026/05/checking-for-policy-issues-1.png" alt="" class="wp-image-478792"/></figure>



<p>Once the ad is saved, Google immediately provides a policy decision. Ads without issues can begin serving almost instantly, while ads with more complex violations are directed to a new post-save policy review page explaining the issue and available next steps.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="647" height="568" src="https://searchengineland.com/wp-content/seloads/2026/05/Real-time-check.png" alt="" class="wp-image-478790"/></figure>



<p><strong>Why we care. </strong>The update could significantly reduce campaign launch delays for advertisers, especially during time-sensitive promotions, product launches and live marketing moments.</p>



<p><strong>Between the lines.</strong> Google is separating policy issues into two categories.</p>



<p>Editable issues include straightforward problems advertisers can quickly fix within the workflow itself, such as formatting or destination errors.</p>



<p>Complex issues include violations requiring certifications, appeals or additional policy reviews.</p>



<p><strong>The bigger picture.</strong> The update reflects Google’s broader push to make campaign management faster, more automated and more integrated directly into advertiser workflows.</p>



<p>For advertisers running reactive or short-window campaigns, reducing review delays could improve speed-to-market and reduce missed traffic opportunities.</p>



<p><strong>What to watch.</strong> As Google expands <a href="https://business.google.com/us/accelerate/announcements/faster-ad-creation-with-real-time-policy-reviews/">Real-Time Policy Reviews</a> across more campaign types, advertisers may see fewer delays between campaign creation and delivery — but automated policy enforcement could also increase the importance of catching compliance issues earlier in the creative process.</p>


Google is rolling out Real-Time Policy Reviews, a new system designed to dramatically speed up ad approvals by bringing policy checks directly into the ad creation process.
What’s happening. The feature is currently available for Responsive Search Ads and will expand to additional campaign types later this year.
Instead of waiting for ads to enter a separate review queue after submission, advertisers now receive instant policy feedback while building ads inside Google Ads.
The system checks for issues in two stages.
During ad creation, advertisers receive real-time editorial checks for issues such as typos, capitalization problems or destination errors before saving the ad.




Once the ad is saved, Google immediately provides a policy decision. Ads without issues can begin serving almost instantly, while ads with more complex violations are directed to a new post-save policy review page explaining the issue and available next steps.




Why we care. The update could significantly reduce campaign launch delays for advertisers, especially during time-sensitive promotions, product launches and live marketing moments.
Between the lines. Google is separating policy issues into two categories.
Editable issues include straightforward problems advertisers can quickly fix within the workflow itself, such as formatting or destination errors.
Complex issues include violations requiring certifications, appeals or additional policy reviews.
The bigger picture. The update reflects Google’s broader push to make campaign management faster, more automated and more integrated directly into advertiser workflows.
For advertisers running reactive or short-window campaigns, reducing review delays could improve speed-to-market and reduce missed traffic opportunities.
What to watch. As Google expands Real-Time Policy Reviews across more campaign types, advertisers may see fewer delays between campaign creation and delivery — but automated policy enforcement could also increase the importance of catching compliance issues earlier in the creative process.

Google is introducing Real-Time Policy Reviews to speed up ad approvals with instant feedback during campaign creation.

Google launches Real-Time Policy Reviews for faster ad approvals

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/05/The-micro-macro-shift-How-to-measure-AI-visibility-now-that-precision-is-gone.png" class="attachment-large size-large wp-post-image" alt="The micro-macro shift- How to measure AI visibility now that precision is gone" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/05/The-micro-macro-shift-How-to-measure-AI-visibility-now-that-precision-is-gone.png 1920w, https://searchengineland.com/wp-content/seloads/2026/05/The-micro-macro-shift-How-to-measure-AI-visibility-now-that-precision-is-gone-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/The-micro-macro-shift-How-to-measure-AI-visibility-now-that-precision-is-gone-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/05/The-micro-macro-shift-How-to-measure-AI-visibility-now-that-precision-is-gone-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>AI visibility is now a macro measurement problem. Here’s how to build a defensible framework for tracking recommendation trends.

AI visibility is now a macro measurement problem. Here’s how to build a defensible framework for tracking recommendation trends.

The micro-macro shift: How to measure AI visibility now that precision is gone

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/05/The-SEO-GEO-gap-How-AI-search-traffic-differs-from-organic-traffic.png" class="attachment-large size-large wp-post-image" alt="The SEO-GEO gap- How AI search traffic differs from organic traffic" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/05/The-SEO-GEO-gap-How-AI-search-traffic-differs-from-organic-traffic.png 1920w, https://searchengineland.com/wp-content/seloads/2026/05/The-SEO-GEO-gap-How-AI-search-traffic-differs-from-organic-traffic-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/The-SEO-GEO-gap-How-AI-search-traffic-differs-from-organic-traffic-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/05/The-SEO-GEO-gap-How-AI-search-traffic-differs-from-organic-traffic-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Data from 10 websites shows why original research, tools, and answer-first content outperform generic educational articles in GEO.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/05/The-SEO-GEO-gap-How-AI-search-traffic-differs-from-organic-traffic.png" class="attachment-large size-large wp-post-image" alt="The SEO-GEO gap- How AI search traffic differs from organic traffic" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/05/The-SEO-GEO-gap-How-AI-search-traffic-differs-from-organic-traffic.png 1920w, https://searchengineland.com/wp-content/seloads/2026/05/The-SEO-GEO-gap-How-AI-search-traffic-differs-from-organic-traffic-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/The-SEO-GEO-gap-How-AI-search-traffic-differs-from-organic-traffic-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/05/The-SEO-GEO-gap-How-AI-search-traffic-differs-from-organic-traffic-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Some marketers argue <a href="https://searchengineland.com/what-is-generative-engine-optimization-geo-444418">GEO</a> replaces <a href="https://searchengineland.com/guide/what-is-seo">SEO</a>. Others claim strong SEO is enough for AI visibility.</p>



<p>To test both assumptions, we analyzed LLM referral traffic and organic traffic across 10 websites and 150,000 indexed pages. The results showed that AI search favors different content patterns than traditional organic search.</p>



<h2 class="wp-block-heading" id="h-3-key-findings-from-the-dataset">3 key findings from the dataset</h2>



<h3 class="wp-block-heading" id="h-1-traditional-seo-content-strategies-aren-t-best-for-geo">1. Traditional SEO content strategies aren&#8217;t best for GEO</h3>



<p>Blog content theme predicted LLM traffic more reliably than almost any other variable. Educational “comprehensive” guides consistently underperformed compared to shorter posts built around unique data.</p>



<p>Trends and analysis posts attracted LLM citations 78% of the time.<strong> </strong>Data-based year-in-review posts sat at 61%. Posts with unique data consistently dominated the LLM citation pool.</p>



<p>Meanwhile, educational how-to content sat at just 12%.<strong> </strong>This includes the SEO workhorse content that fills most calendars: guides, how-to posts, and top-of-funnel FAQs.&nbsp;</p>



<p>If you produce authoritative, data-rich, measurement-oriented content, you are disproportionately likely to be in the LLM citation pool. If you produce generic educational content, odds are that you won’t be.</p>



<h3 class="wp-block-heading" id="h-2-organic-success-doesn-t-guarantee-llm-traffic">2. Organic success doesn’t guarantee LLM traffic</h3>



<p>The top 10 organic pages in this study captured 55% of organic sessions. Those same pages captured only 29% of LLM sessions.</p>



<p>Put another way: Your best-performing organic content and your best-performing LLM content are likely not the same content. Among the top 100 organic pages, 49 had zero LLM traffic whatsoever!</p>



<p>LLM traffic is correlated with organic performance, but it is <strong>not</strong> simply organic performance re-labeled.</p>



<h3 class="wp-block-heading" id="h-3-service-product-pages-punch-above-their-weight-class-for-llm-traffic">3. Service product pages punch above their weight class for LLM traffic</h3>



<p>By raw session count, articles and blog posts still generated the most LLM referrals. But when viewing LLM sessions per 1,000 organic sessions (a fairer measure of relative performance), service and product pages outperformed everything:</p>



<figure class="wp-block-table"><table class="has-fixed-layout"><tbody><tr><td><strong>Page type</strong></td><td class="has-text-align-left" data-align="left"><strong><strong>LLM sessions per 1,000 organic</strong></strong></td></tr><tr><td>Service/product</td><td class="has-text-align-left" data-align="left">29.4</td></tr><tr><td>Article/content</td><td class="has-text-align-left" data-align="left">23.4</td></tr><tr><td>FAQ/support</td><td class="has-text-align-left" data-align="left">14.0</td></tr><tr><td>Tool/demo</td><td class="has-text-align-left" data-align="left">9.8</td></tr><tr><td>Homepage</td><td class="has-text-align-left" data-align="left">5.6</td></tr></tbody></table></figure>



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<h2 class="wp-block-heading" id="h-the-methodology-behind-the-case-study">The methodology behind the case study</h2>



<p>This case study analyzed GA4 data from 10 websites, covering a combined 150,000 indexed pages across a one-month window in March 2026.</p>



<ul class="wp-block-list">
<li>The 10 domains deliberately span a range of industries, including healthcare, cybersecurity, technology, retail, education, economic development, and other B2B and B2C service verticals. The sampled domains were also selected for their relative consistency across key SEO metrics: strong Core Web Vitals, concerted content marketing efforts, and a consistent history of organic performance.</li>



<li>LLM-referral traffic was isolated using GA4 channel groupings and referrer path segmentation, capturing sessions originating from ChatGPT, Claude, Perplexity, Copilot, and other major conversational AI platforms. Organic sessions reflected traditional search engine visits, primarily from Google.</li>



<li>Blog content was further categorized by topic theme to compare LLM citation rates across content types. Engagement time comparisons used per-page averages as reported by GA4.</li>
</ul>



<p>There’s one additional methodological note worth flagging, as it&#8217;s a frequent point of confusion: LLM bot crawls (GPTBot, ClaudeBot, etc.) aren’t recorded by GA4; they make server-level HTTP requests before client-side JavaScript fires. The organic session counts in this study reflect human visitors only.</p>



<h2 class="wp-block-heading" id="h-what-llm-traffic-patterns-reveal">What LLM traffic patterns reveal</h2>



<h3 class="wp-block-heading" id="h-llm-referral-traffic-behaves-differently-than-organic-traffic">LLM referral traffic behaves differently than organic traffic</h3>



<p>At first glance, average engagement time per session between organic and LLM traffic appears nearly identical: 46.9 seconds for organic versus 47.1 for LLM. But that average hides an interesting statistical artifact.</p>



<p>On 71% of LLM-receiving pages, LLM sessions were notably <strong>shorter</strong> than organic. On 27% of pages, LLM sessions were dramatically <strong>longer</strong>, often three to 10x the organic average.</p>



<p>The split makes more sense when viewed by page type:</p>



<figure class="wp-block-table"><table class="has-fixed-layout"><tbody><tr><td><strong>Page type</strong></td><td><strong>Organic avg. time</strong></td><td><strong>LLM avg. time</strong></td></tr><tr><td>Tool/demo</td><td>101 seconds</td><td>146 seconds</td></tr><tr><td>Homepage</td><td>36 seconds</td><td>82 seconds</td></tr><tr><td>Service/product</td><td>69 seconds</td><td>63 seconds</td></tr><tr><td>Article/content</td><td>56 seconds</td><td>40 seconds</td></tr></tbody></table></figure>



<p>LLM users appear more engaged on tools, homepages, and service/product pages —&nbsp;but less engaged on articles.&nbsp;</p>



<p>One possible explanation is that LLM users arrive at articles to verify or extract a specific piece of information before leaving, while tools and service pages give them something more actionable to evaluate.</p>



<h3 class="wp-block-heading" id="h-interactive-tools-are-an-underappreciated-llm-traffic-category">Interactive tools are an underappreciated LLM traffic category</h3>



<p>Among all page-type categories, interactive tools showed the highest <em>per-page </em>LLM citation rates in the study. Nearly all interactive tools were gathering at least some LLM sessions. </p>



<p>LLMs actively recommend specific tools by name when users ask about assessments, screeners, or evaluations. Any site with a functional, named tool (e.g., a calculator, screener, or quiz) should expect LLMs to route relevant queries directly to it.</p>



<h3 class="wp-block-heading" id="h-a-new-category-worth-watching-llm-only-traffic">A new category worth watching: LLM-only traffic</h3>



<p>Interestingly, 14% of all LLM-receiving pages in this study had zero organic clicks during the study window.</p>



<p>It&#8217;s tempting to interpret this as evidence of some new discovery mechanism unique to LLMs. A more likely explanation is that these pages either rank poorly in organic search or lose clicks because AI Overviews answer the query directly in the SERP. AI Overview citations <a href="https://searchengineland.com/ai-overview-citations-clicks-what-to-do-462389">consistently underperform blue links</a> on click-through rate, even compared to results near the bottom of the SERP.</p>



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<h2 class="wp-block-heading" id="h-geo-tactics-supported-by-the-data">GEO tactics supported by the data</h2>



<p>Based on these findings, here&#8217;s what the evidence indicates for effective GEO.</p>



<h3 class="wp-block-heading" id="h-prioritize-content-that-answers-questions-llms-can-t-answer-themselves">Prioritize content that answers questions LLMs can&#8217;t answer themselves</h3>



<p>Generic educational content likely underperforms in LLM citations because LLMs are perfectly capable of producing it themselves.</p>



<p>Original data, proprietary research, and owned insights are the strongest differentiators for LLM citation. If you have a data asset, make it the centerpiece of your content.&nbsp;</p>



<p>Even better, if budget allows, allocate resources to generating studies and identifying new, verifiable data.</p>



<h3 class="wp-block-heading" id="h-use-answer-capsules-on-every-page-you-want-cited">Use answer capsules on every page you want cited</h3>



<p>In <a href="https://searchengineland.com/how-to-get-cited-by-chatgpt-the-content-traits-llms-quote-most-464868">prior research across 15 domains and nearly 2 million sessions</a>, answer capsules were the single strongest structural predictor of ChatGPT citations. An answer capsule is a concise, direct response to the core question of the page. It is placed early, written in clean prose, free of internal links, and gives the LLM a clean, extractable unit to quote.</p>



<p>LLMs pattern-match for the easiest, most direct answers. Give them what they want! The pages in this study that punched well above their organic weight class on LLM traffic tended to answer a specific question with specific data rather than explore a topic broadly.</p>



<h3 class="wp-block-heading" id="h-build-or-surface-a-named-interactive-tool">Build (or surface) a named interactive tool</h3>



<p>If your site has a calculator, screener, assessment, or configurator, it is one of your best GEO assets and potentially more valuable per page than your entire blog archive.</p>



<p>Make sure it:&nbsp;</p>



<ul class="wp-block-list">
<li>Has a clear, searchable name grounded in keyword research.&nbsp;</li>



<li>Answers a specific question when someone arrives cold.</li>



<li>Provides a useful service.</li>
</ul>



<h3 class="wp-block-heading" id="h-track-organic-and-llm-performing-pages-separately-and-treat-the-difference-seriously">Track organic and LLM-performing pages separately and treat the difference seriously</h3>



<p>Of the top 100 organic pages in this study, 49 pages had zero LLM traffic. That doesn&#8217;t mean those pages are failing. It just means LLM citation and organic visibility aren’t a 1:1 correlation.</p>



<p>A page that ranks No. 1 in the organic results for &#8220;best practices for X&#8221; may never get LLM traffic if nobody is asking an LLM about best practices for X. Content mapping for GEO means asking a different question than content mapping for SEO: Not, &#8220;What do people search for?&#8221; but, &#8220;What do people ask an AI?&#8221;</p>



<p>If you have pages that already receive LLM sessions with no organic clicks, don&#8217;t dismiss them as noise. In this study, the engagement quality on those pages was among the highest recorded. Those users were specifically directed to you by an AI, and they showed up ready to engage.</p>



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<h2 class="wp-block-heading" id="h-geo-and-seo-same-strategies-different-tactics">GEO and SEO: Same strategies, different tactics</h2>



<p>The overall picture derived from this data isn’t that GEO is replacing SEO, but that GEO is rewarding a slightly different set of on-page tactics. Additionally, the gap between the two may be widening as zero-click search accelerates.</p>



<p>The sites that performed best with LLM traffic built content that answers precise questions with original information, while keeping the page useful as a destination, not just a click. That has always been a good strategy. The difference now is that two separate systems are evaluating your content according to two separate sets of criteria, and optimizing for one no longer guarantees performance in the other.</p>

Some marketers argue GEO replaces SEO. Others claim strong SEO is enough for AI visibility.
To test both assumptions, we analyzed LLM referral traffic and organic traffic across 10 websites and 150,000 indexed pages. The results showed that AI search favors different content patterns than traditional organic search.
3 key findings from the dataset
1. Traditional SEO content strategies aren’t best for GEO
Blog content theme predicted LLM traffic more reliably than almost any other variable. Educational “comprehensive” guides consistently underperformed compared to shorter posts built around unique data.
Trends and analysis posts attracted LLM citations 78% of the time. Data-based year-in-review posts sat at 61%. Posts with unique data consistently dominated the LLM citation pool.
Meanwhile, educational how-to content sat at just 12%. This includes the SEO workhorse content that fills most calendars: guides, how-to posts, and top-of-funnel FAQs. 
If you produce authoritative, data-rich, measurement-oriented content, you are disproportionately likely to be in the LLM citation pool. If you produce generic educational content, odds are that you won’t be.
2. Organic success doesn’t guarantee LLM traffic
The top 10 organic pages in this study captured 55% of organic sessions. Those same pages captured only 29% of LLM sessions.
Put another way: Your best-performing organic content and your best-performing LLM content are likely not the same content. Among the top 100 organic pages, 49 had zero LLM traffic whatsoever!
LLM traffic is correlated with organic performance, but it is not simply organic performance re-labeled.
3. Service product pages punch above their weight class for LLM traffic
By raw session count, articles and blog posts still generated the most LLM referrals. But when viewing LLM sessions per 1,000 organic sessions (a fairer measure of relative performance), service and product pages outperformed everything:

Page typeLLM sessions per 1,000 organic
Service/product29.4
Article/content23.4
FAQ/support14.0
Tool/demo9.8
Homepage5.6






  
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The methodology behind the case study
This case study analyzed GA4 data from 10 websites, covering a combined 150,000 indexed pages across a one-month window in March 2026.
The 10 domains deliberately span a range of industries, including healthcare, cybersecurity, technology, retail, education, economic development, and other B2B and B2C service verticals. The sampled domains were also selected for their relative consistency across key SEO metrics: strong Core Web Vitals, concerted content marketing efforts, and a consistent history of organic performance.
LLM-referral traffic was isolated using GA4 channel groupings and referrer path segmentation, capturing sessions originating from ChatGPT, Claude, Perplexity, Copilot, and other major conversational AI platforms. Organic sessions reflected traditional search engine visits, primarily from Google.
Blog content was further categorized by topic theme to compare LLM citation rates across content types. Engagement time comparisons used per-page averages as reported by GA4.
There’s one additional methodological note worth flagging, as it’s a frequent point of confusion: LLM bot crawls (GPTBot, ClaudeBot, etc.) aren’t recorded by GA4; they make server-level HTTP requests before client-side JavaScript fires. The organic session counts in this study reflect human visitors only.
What LLM traffic patterns reveal
LLM referral traffic behaves differently than organic traffic
At first glance, average engagement time per session between organic and LLM traffic appears nearly identical: 46.9 seconds for organic versus 47.1 for LLM. But that average hides an interesting statistical artifact.
On 71% of LLM-receiving pages, LLM sessions were notably shorter than organic. On 27% of pages, LLM sessions were dramatically longer, often three to 10x the organic average.
The split makes more sense when viewed by page type:

Page typeOrganic avg. timeLLM avg. time
Tool/demo101 seconds146 seconds
Homepage36 seconds82 seconds
Service/product69 seconds63 seconds
Article/content56 seconds40 seconds





LLM users appear more engaged on tools, homepages, and service/product pages — but less engaged on articles. 
One possible explanation is that LLM users arrive at articles to verify or extract a specific piece of information before leaving, while tools and service pages give them something more actionable to evaluate.
Interactive tools are an underappreciated LLM traffic category
Among all page-type categories, interactive tools showed the highest per-page LLM citation rates in the study. Nearly all interactive tools were gathering at least some LLM sessions. 
LLMs actively recommend specific tools by name when users ask about assessments, screeners, or evaluations. Any site with a functional, named tool (e.g., a calculator, screener, or quiz) should expect LLMs to route relevant queries directly to it.
A new category worth watching: LLM-only traffic
Interestingly, 14% of all LLM-receiving pages in this study had zero organic clicks during the study window.
It’s tempting to interpret this as evidence of some new discovery mechanism unique to LLMs. A more likely explanation is that these pages either rank poorly in organic search or lose clicks because AI Overviews answer the query directly in the SERP. AI Overview citations consistently underperform blue links on click-through rate, even compared to results near the bottom of the SERP.
Get the newsletter search marketers rely on.
 
				
				
			
See terms.
		
GEO tactics supported by the data
Based on these findings, here’s what the evidence indicates for effective GEO.
Prioritize content that answers questions LLMs can’t answer themselves
Generic educational content likely underperforms in LLM citations because LLMs are perfectly capable of producing it themselves.
Original data, proprietary research, and owned insights are the strongest differentiators for LLM citation. If you have a data asset, make it the centerpiece of your content. 
Even better, if budget allows, allocate resources to generating studies and identifying new, verifiable data.
Use answer capsules on every page you want cited
In prior research across 15 domains and nearly 2 million sessions, answer capsules were the single strongest structural predictor of ChatGPT citations. An answer capsule is a concise, direct response to the core question of the page. It is placed early, written in clean prose, free of internal links, and gives the LLM a clean, extractable unit to quote.
LLMs pattern-match for the easiest, most direct answers. Give them what they want! The pages in this study that punched well above their organic weight class on LLM traffic tended to answer a specific question with specific data rather than explore a topic broadly.
Build (or surface) a named interactive tool
If your site has a calculator, screener, assessment, or configurator, it is one of your best GEO assets and potentially more valuable per page than your entire blog archive.
Make sure it: 
Has a clear, searchable name grounded in keyword research. 
Answers a specific question when someone arrives cold.
Provides a useful service.
Track organic and LLM-performing pages separately and treat the difference seriously
Of the top 100 organic pages in this study, 49 pages had zero LLM traffic. That doesn’t mean those pages are failing. It just means LLM citation and organic visibility aren’t a 1:1 correlation.
A page that ranks No. 1 in the organic results for “best practices for X” may never get LLM traffic if nobody is asking an LLM about best practices for X. Content mapping for GEO means asking a different question than content mapping for SEO: Not, “What do people search for?” but, “What do people ask an AI?”
If you have pages that already receive LLM sessions with no organic clicks, don’t dismiss them as noise. In this study, the engagement quality on those pages was among the highest recorded. Those users were specifically directed to you by an AI, and they showed up ready to engage.

  
complete picture of your search visibility.
      
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GEO and SEO: Same strategies, different tactics
The overall picture derived from this data isn’t that GEO is replacing SEO, but that GEO is rewarding a slightly different set of on-page tactics. Additionally, the gap between the two may be widening as zero-click search accelerates.
The sites that performed best with LLM traffic built content that answers precise questions with original information, while keeping the page useful as a destination, not just a click. That has always been a good strategy. The difference now is that two separate systems are evaluating your content according to two separate sets of criteria, and optimizing for one no longer guarantees performance in the other.

Data from 10 websites shows why original research, tools, and answer-first content outperform generic educational articles in GEO.

The SEO-GEO gap: How AI search traffic differs from organic traffic

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/05/How-to-get-your-Google-Ads-seen-in-AI-Overviews.png" class="attachment-large size-large wp-post-image" alt="How to get your Google Ads seen in AI Overviews" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/05/How-to-get-your-Google-Ads-seen-in-AI-Overviews.png 1920w, https://searchengineland.com/wp-content/seloads/2026/05/How-to-get-your-Google-Ads-seen-in-AI-Overviews-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/How-to-get-your-Google-Ads-seen-in-AI-Overviews-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/05/How-to-get-your-Google-Ads-seen-in-AI-Overviews-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Here's how feeds, landing pages, and audience signals help Shopping, Performance Max, and AI Max campaigns appear in AI Overviews.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/05/How-to-get-your-Google-Ads-seen-in-AI-Overviews.png" class="attachment-large size-large wp-post-image" alt="How to get your Google Ads seen in AI Overviews" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/05/How-to-get-your-Google-Ads-seen-in-AI-Overviews.png 1920w, https://searchengineland.com/wp-content/seloads/2026/05/How-to-get-your-Google-Ads-seen-in-AI-Overviews-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/How-to-get-your-Google-Ads-seen-in-AI-Overviews-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/05/How-to-get-your-Google-Ads-seen-in-AI-Overviews-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p><a href="https://searchengineland.com/guide/google-ai-overviews">AI Overviews</a> are changing how paid ads appear in Google Search. As more searches are answered directly in the SERP, you have fewer opportunities to earn clicks and more pressure to appear inside AI-generated responses.</p>



<p>Google is already signaling which campaign types are best positioned for this shift: Shopping, <a href="https://searchengineland.com/google-performance-max-431821">Performance Max</a>, and <a href="https://searchengineland.com/ai-max-for-search-everything-you-need-to-know-462923">AI Max for Search</a>. But campaign selection alone isn’t enough. Feed quality, contextual landing page content, audience signals, and conversational creative all influence whether your ads appear.</p>



<h2 class="wp-block-heading" id="h-enable-google-recommended-campaigns-to-sync-with-ai-overviews">Enable Google-recommended campaigns to sync with AI Overviews</h2>



<p>Google has been fairly transparent about which campaign opportunities offer the best chance to appear in AI Overviews. Interestingly, these are the same opportunities that seasoned marketers seem reluctant to adopt because of a lack of control.&nbsp;</p>



<p>However, the right mix of control, data, and understanding of intent will assist both the advertiser and the searcher in the long run. This strategy involves more than just advocating for specific campaign types. AI Overviews are won through contextual alignment, fully optimized feed data, and robust on-page content.</p>



<p>One of the first steps toward increased visibility within the AI Overviews is to enable the campaigns Google recommends for syncing with this new feature. Specifically, these campaigns are Shopping, Performance Max, and AI Max for Search, with the latter being coupled with broad match keywords and smart bidding and utilizing final URL expansion. </p>



<p>Google recommends these campaigns in particular because of how they interact with search terms, using keyword flexibility to determine when to show ads.</p>



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<h3 class="wp-block-heading" id="h-shopping-campaigns-nbsp">Shopping campaigns&nbsp;</h3>



<p>They are the original keywordless campaign. How well they perform is the product of many factors, but primarily the quality of your data feed. Make sure your product data feed is well-built and optimized, with high-quality images of your product. Ensure your titles and descriptions are thorough and, if possible, even populate the optional feed attributes. </p>



<p>The product data feed is the essential indicator of whether an ad will show for a specific query. When a user asks a high-intent question, the AI Overview can generate a product carousel at the top or bottom of the summary in addition to the shopping results in the SERP.</p>



<h3 class="wp-block-heading" id="h-performance-max-campaigns">Performance Max campaigns</h3>



<p>Performance Max is a keywordless campaign that utilizes a combination of page content, data feed, and audience insights to determine how it will serve ads. Together, these inputs help determine when and where ads appear for specific queries.</p>



<p>Opting into Final URL expansion will enable your ad to appear for more searches as Google leans into page content to determine relevance to the user’s query.</p>



<h3 class="wp-block-heading" id="h-ai-max-for-search-campaigns">AI Max for Search campaigns</h3>



<p>AI Max for Search uses the existing keywords as a jumping-off point. However, it expands beyond them to find the right means to serve the ads. This flexibility turns the keyword into an intent signal rather than a specific indicator of when the ads will serve. </p>



<p>Note that AI Max uses both search term matching and asset optimization to reach more of these queries that wouldn’t be covered under traditional keyword targeting searches.</p>



<h2 class="wp-block-heading" id="h-6-best-practices-when-setting-up-your-ad-campaigns">6 best practices when setting up your ad campaigns</h2>



<p>To increase your chance of having your ad chosen as a featured section in an AI Overview, make sure you’re optimizing your campaign across creative, copy, schema, and link building tactics that strengthen brand authority.</p>



<h3 class="wp-block-heading" id="h-1-diversify-your-assets">1. Diversify your assets</h3>



<p>An important factor to consider when utilizing campaigns like AI Max and Performance Max is the creative you’re using. Make sure you have a diverse variety of informative assets. </p>



<p>Include varied headlines and descriptions alongside descriptive and informational video and image assets within Performance Max. </p>



<p>When using images and video, provide assets in square (1:1), landscape (1.91:1), and vertical (4:5 or 9:16) orientations to allow placement across many different response iterations. </p>



<h3 class="wp-block-heading" id="h-2-use-a-conversational-tone-in-your-messaging">2. Use a conversational tone in your messaging </h3>



<p>Google <a href="https://support.google.com/google-ads/answer/16297775?hl=en" target="_blank" rel="noopener">indicates</a> that “ads in AI Overview are matched to their understanding of the user intent based on not just the user query, but also the content of the AI Overview. </p>



<p>In your Responsive Search Ads, shift from generic sales pitches to a more conversational tone. Avoid overused phrases like “Buy now” and use assistive language for the user. </p>



<h3 class="wp-block-heading" id="h-3-be-clear-and-informative">3. Be clear and informative</h3>



<p>Attempt to answer the who, what, how, and why of a query. Include at least 3-5 headlines that are phrased as answers or helpful summaries. This clarity will give your ad a better chance of being selected as the featured selection in an AI overview. </p>



<p>Because final URL expansion relies so heavily on landing page content, utilizing information-first copy alongside a context-rich landing page is especially important. It appears that the more content the final URL expansion has to draw from, the more opportunities your ad has to appear in the AI overviews for specific queries users are asking. </p>



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<h3 class="wp-block-heading" id="h-4-check-schema-markup-and-links">4. Check schema markup and links</h3>



<p>In addition to on-page content, make sure the schema markup is thorough and aligned to verify the content. If you’re able to link back to reputable sources from your landing page, do so to build authority. Work closely with your SEO team to implement these best practices.</p>



<h3 class="wp-block-heading" id="h-5-guide-the-automation-through-strong-audience-signals">5. Guide the automation through strong audience signals</h3>



<p>One thing that all of these campaigns have in common is a perceived lack of control over what the advertiser is actually bidding on. It’s important to guide the automation with strong audience signals and the strategic use of exclusions and negative keywords. </p>



<p>Your audience signals are strong hints to Google about who’s most likely to convert. A strong audience strategy that leverages first-party signals helps the system learn and optimize quickly toward intent-based conversions.</p>



<h3 class="wp-block-heading" id="h-6-regularly-monitor-your-campaigns-for-brand-alignment">6. Regularly monitor your campaigns for brand alignment</h3>



<p>As in all campaigns, brand safety and profitability are still of utmost importance. It’s vital to regularly monitor the search terms report, landing pages stemming from final URL expansion, and any automatically created assets. </p>



<p>Utilize account-level exclusions, negative keywords, and ad copy optimization often to ensure that your message remains aligned with your landing page and offer.</p>



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<h2 class="wp-block-heading" id="h-adapt-your-approach-for-ai-overviews">Adapt your approach for AI Overviews</h2>



<p>The fundamental shift toward conversational AI Overviews means marketers must pivot from driving clicks to maximizing visibility directly on the SERP.&nbsp;</p>



<p>Winning in this new environment requires a strategic, holistic approach that leverages Google’s recommended campaign types — Shopping, Performance Max, and AI Max for Search — by prioritizing data feed quality and contextual alignment.&nbsp;</p>



<p>By focusing on robust, information-first landing page content, diverse and intent-signaling creative assets, and thorough schema markup, you can ensure your offerings are chosen as the featured selection in an AI Overview, turning this disruption into a powerful new channel for growth.</p>

AI Overviews are changing how paid ads appear in Google Search. As more searches are answered directly in the SERP, you have fewer opportunities to earn clicks and more pressure to appear inside AI-generated responses.
Google is already signaling which campaign types are best positioned for this shift: Shopping, Performance Max, and AI Max for Search. But campaign selection alone isn’t enough. Feed quality, contextual landing page content, audience signals, and conversational creative all influence whether your ads appear.
Enable Google-recommended campaigns to sync with AI Overviews
Google has been fairly transparent about which campaign opportunities offer the best chance to appear in AI Overviews. Interestingly, these are the same opportunities that seasoned marketers seem reluctant to adopt because of a lack of control. 
However, the right mix of control, data, and understanding of intent will assist both the advertiser and the searcher in the long run. This strategy involves more than just advocating for specific campaign types. AI Overviews are won through contextual alignment, fully optimized feed data, and robust on-page content.
One of the first steps toward increased visibility within the AI Overviews is to enable the campaigns Google recommends for syncing with this new feature. Specifically, these campaigns are Shopping, Performance Max, and AI Max for Search, with the latter being coupled with broad match keywords and smart bidding and utilizing final URL expansion. 
Google recommends these campaigns in particular because of how they interact with search terms, using keyword flexibility to determine when to show ads.
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Shopping campaigns 
They are the original keywordless campaign. How well they perform is the product of many factors, but primarily the quality of your data feed. Make sure your product data feed is well-built and optimized, with high-quality images of your product. Ensure your titles and descriptions are thorough and, if possible, even populate the optional feed attributes. 
The product data feed is the essential indicator of whether an ad will show for a specific query. When a user asks a high-intent question, the AI Overview can generate a product carousel at the top or bottom of the summary in addition to the shopping results in the SERP.
Performance Max campaigns
Performance Max is a keywordless campaign that utilizes a combination of page content, data feed, and audience insights to determine how it will serve ads. Together, these inputs help determine when and where ads appear for specific queries.
Opting into Final URL expansion will enable your ad to appear for more searches as Google leans into page content to determine relevance to the user’s query.
AI Max for Search campaigns
AI Max for Search uses the existing keywords as a jumping-off point. However, it expands beyond them to find the right means to serve the ads. This flexibility turns the keyword into an intent signal rather than a specific indicator of when the ads will serve. 
Note that AI Max uses both search term matching and asset optimization to reach more of these queries that wouldn’t be covered under traditional keyword targeting searches.
6 best practices when setting up your ad campaigns
To increase your chance of having your ad chosen as a featured section in an AI Overview, make sure you’re optimizing your campaign across creative, copy, schema, and link building tactics that strengthen brand authority.
1. Diversify your assets
An important factor to consider when utilizing campaigns like AI Max and Performance Max is the creative you’re using. Make sure you have a diverse variety of informative assets. 
Include varied headlines and descriptions alongside descriptive and informational video and image assets within Performance Max. 
When using images and video, provide assets in square (1:1), landscape (1.91:1), and vertical (4:5 or 9:16) orientations to allow placement across many different response iterations. 
2. Use a conversational tone in your messaging 
Google indicates that “ads in AI Overview are matched to their understanding of the user intent based on not just the user query, but also the content of the AI Overview. 
In your Responsive Search Ads, shift from generic sales pitches to a more conversational tone. Avoid overused phrases like “Buy now” and use assistive language for the user. 
3. Be clear and informative
Attempt to answer the who, what, how, and why of a query. Include at least 3-5 headlines that are phrased as answers or helpful summaries. This clarity will give your ad a better chance of being selected as the featured selection in an AI overview. 
Because final URL expansion relies so heavily on landing page content, utilizing information-first copy alongside a context-rich landing page is especially important. It appears that the more content the final URL expansion has to draw from, the more opportunities your ad has to appear in the AI overviews for specific queries users are asking. 
Get the newsletter search marketers rely on.
 
				
				
			
See terms.
		
4. Check schema markup and links
In addition to on-page content, make sure the schema markup is thorough and aligned to verify the content. If you’re able to link back to reputable sources from your landing page, do so to build authority. Work closely with your SEO team to implement these best practices.
5. Guide the automation through strong audience signals
One thing that all of these campaigns have in common is a perceived lack of control over what the advertiser is actually bidding on. It’s important to guide the automation with strong audience signals and the strategic use of exclusions and negative keywords. 
Your audience signals are strong hints to Google about who’s most likely to convert. A strong audience strategy that leverages first-party signals helps the system learn and optimize quickly toward intent-based conversions.
6. Regularly monitor your campaigns for brand alignment
As in all campaigns, brand safety and profitability are still of utmost importance. It’s vital to regularly monitor the search terms report, landing pages stemming from final URL expansion, and any automatically created assets. 
Utilize account-level exclusions, negative keywords, and ad copy optimization often to ensure that your message remains aligned with your landing page and offer.
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Adapt your approach for AI Overviews
The fundamental shift toward conversational AI Overviews means marketers must pivot from driving clicks to maximizing visibility directly on the SERP. 
Winning in this new environment requires a strategic, holistic approach that leverages Google’s recommended campaign types — Shopping, Performance Max, and AI Max for Search — by prioritizing data feed quality and contextual alignment. 
By focusing on robust, information-first landing page content, diverse and intent-signaling creative assets, and thorough schema markup, you can ensure your offerings are chosen as the featured selection in an AI Overview, turning this disruption into a powerful new channel for growth.

Here's how feeds, landing pages, and audience signals help Shopping, Performance Max, and AI Max campaigns appear in AI Overviews.

How to get your Google Ads seen in AI Overviews

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/05/featured-image-Users-behave-differently-in-AI-Overviews-vs-AI-Mode.png" class="attachment-large size-large wp-post-image" alt="Users behave differently in AI Overviews vs AI Mode" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/05/featured-image-Users-behave-differently-in-AI-Overviews-vs-AI-Mode.png 1920w, https://searchengineland.com/wp-content/seloads/2026/05/featured-image-Users-behave-differently-in-AI-Overviews-vs-AI-Mode-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/featured-image-Users-behave-differently-in-AI-Overviews-vs-AI-Mode-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/05/featured-image-Users-behave-differently-in-AI-Overviews-vs-AI-Mode-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>New clickstream data shows AI Overviews reshape user behavior, from reverse scrolling to longer SERP evaluation across search intents.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/05/featured-image-Users-behave-differently-in-AI-Overviews-vs-AI-Mode.png" class="attachment-large size-large wp-post-image" alt="Users behave differently in AI Overviews vs AI Mode" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/05/featured-image-Users-behave-differently-in-AI-Overviews-vs-AI-Mode.png 1920w, https://searchengineland.com/wp-content/seloads/2026/05/featured-image-Users-behave-differently-in-AI-Overviews-vs-AI-Mode-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/featured-image-Users-behave-differently-in-AI-Overviews-vs-AI-Mode-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/05/featured-image-Users-behave-differently-in-AI-Overviews-vs-AI-Mode-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>The average Netflix user spends 18 minutes browsing the home screen before picking what to watch. They scroll past tiles, hover for trailers, scroll back to a show they almost picked, then circle back to the row they started in. The browse is the experience.</p>



<p>Search isn&#8217;t that different anymore. We just lacked the data to see it until now.</p>



<p><strong>This week:</strong>



<ul class="wp-block-list">
<li>Four behavioral shifts that show up when an AI Overview is on the page, measured across 846,000 real Google sessions.</li>



<li>Why brand-name searches no longer give you the shortcut they used to.</li>



<li>One finding that should change how you write title tags and meta descriptions this quarter.</li>
</ul>



<p>Eric Van Buskirk of <a href="https://clickstream.cc/" target="_blank" rel="noopener">Clickstream Solutions</a> analyzed anonymized clickstream data provided by <a href="https://surferseo.com/" target="_blank" rel="noopener">Surfer SEO</a>, drawing findings from approximately 846,000 U.S.-based Google search sessions collected in February and March 2026.&nbsp;</p>



<p>It&#8217;s the fifth user-behavior study on Google&#8217;s AI features in the last 12 months. The <a href="https://www.growth-memo.com/p/the-first-ever-ux-study-of-googles" target="_blank" rel="noopener">70-user UX study from May 2025</a> used think-aloud and screen recording. The <a href="https://www.growth-memo.com/p/what-our-ai-mode-user-behavior-study" target="_blank" rel="noopener">250-session AI Mode study from October 2025</a> captured how users behave inside AI Mode itself. This one trades qualitative depth for the scale to find behavioral patterns the smaller studies couldn&#8217;t see.</p>



<p><a href="https://www.growth-memo.com/embed?transparent=1" rel="noopener noreferrer">View embedded content</a>



<p>For context: Prior public Google SERP mouse-tracking studies measured dozens of people. The largest had a few thousand tasks. This study analyzed queries from a panel of tens of thousands of Google Search users.</p>



<p>The most significant pattern shown: Users behave in opposite ways in AI Overviews and AI Mode. AI Mode is autoplay. AI Overviews is the Netflix browse.</p>



<p>This article covers four findings from the new study (full methodology <a href="https://clickstream.cc/methodology-measuring-how-users-move-pause-and-reconsider-on-google-search/" target="_blank" rel="noopener">here</a>) and what they mean for how you write title tags and meta descriptions in 2026. </p>



<figure class="wp-block-image size-full"><img decoding="async" width="2048" height="359" src="https://searchengineland.com/wp-content/seloads/2026/05/image-246.png" alt="" class="wp-image-478658" srcset="https://searchengineland.com/wp-content/seloads/2026/05/image-246.png 2048w, https://searchengineland.com/wp-content/seloads/2026/05/image-246-768x135.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/image-246-1536x269.png 1536w" sizes="(max-width: 2048px) 100vw, 2048px" /></figure>



<p><strong>Complete brand visibility: Whether you’re a global brand or nationwide nonprofit</strong>


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<p>Good Guys SEO secured buy-in and built an end-to-end search strategy for one of the US&#8217;s most recognized nonprofits using Semrush for Enterprise.</p>



<p>The result: +37% AI share of voice for homelessness services, with visibility connected directly to campaign traffic and donations.</p>



<p>Complete SEO and AI search capabilities in one platform. The outcomes speak for themselves, whatever your industry or business model.</p>



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<figure class="aligncenter size-full"><img decoding="async" width="2048" height="359" src="https://searchengineland.com/wp-content/seloads/2026/05/image-246.png" alt="" class="wp-image-478657" srcset="https://searchengineland.com/wp-content/seloads/2026/05/image-246.png 2048w, https://searchengineland.com/wp-content/seloads/2026/05/image-246-768x135.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/image-246-1536x269.png 1536w" sizes="(max-width: 2048px) 100vw, 2048px" /></figure>
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<figure class="aligncenter size-full"><img decoding="async" width="1200" height="1231" src="https://searchengineland.com/wp-content/seloads/2026/05/headline-graphic-new.png" alt="846,000 search sessions - AI Overview vs AI Mode" class="wp-image-478673" srcset="https://searchengineland.com/wp-content/seloads/2026/05/headline-graphic-new.png 1200w, https://searchengineland.com/wp-content/seloads/2026/05/headline-graphic-new-768x788.png 768w" sizes="(max-width: 1200px) 100vw, 1200px" /></figure>
</div>


<h2 class="wp-block-heading" id="h-1-same-user-opposite-behaviors">1. Same user, opposite behaviors</h2>



<p>In AI Mode, users often accept the answer while continuing to evaluate the SERP in AI Overviews.</p>



<p>The <a href="https://www.growth-memo.com/p/how-consumers-navigate-high-stakes" target="_blank" rel="noopener">April 2026 study of 185 high-stakes purchases</a> found that in 88% of AI Mode tasks, users took the AI’s shortlist as-is, 74% picked the item ranked first, and 64% clicked nothing at all. AI Mode often behaves like a closed loop: The user reads the answer, picks from inside the answer, and moves on.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="2040" height="1208" src="https://searchengineland.com/wp-content/seloads/2026/05/ai-mode-vs-ai-overview-behavior-contrast.png" alt="AI Mode vs AI Overview Behavior Contrast" class="wp-image-478674" srcset="https://searchengineland.com/wp-content/seloads/2026/05/ai-mode-vs-ai-overview-behavior-contrast.png 2040w, https://searchengineland.com/wp-content/seloads/2026/05/ai-mode-vs-ai-overview-behavior-contrast-768x455.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/ai-mode-vs-ai-overview-behavior-contrast-1536x910.png 1536w" sizes="(max-width: 2040px) 100vw, 2040px" /></figure>



<p><strong>Note:</strong> N/A means the behavior doesn&#8217;t apply to that surface. AI Overviews don&#8217;t deliver shortlists like AI Mode does, and cursor/scroll metrics were only measured in AI Overview comparison environments.</p>



<p>New cursor tracking data on AI Overviews shows a different behavior pattern. Cursor positions spread across the equivalent of 83% of a viewport, compared with 66% when no AI Overview appeared. Users kept their cursors still 44% of the time, compared with 29% without an AIO. And in the median session, reverse-direction scrolling accounted for nearly half of scroll movement.</p>



<p>Taken together, this suggests that AI Overviews turn the SERP into more of a comparison environment. The user reads, pauses, weighs, returns to earlier content, and reconsiders before clicking.</p>



<p>The implication for strategy: AI Mode optimization and AI Overview optimization are not the same job. Showing up in an AI Mode shortlist is a visibility problem at the model layer. Showing up in an AI Overview is a comparison problem on the SERP itself.</p>



<h2 class="wp-block-heading" id="h-2-half-of-all-scrolling-now-goes-backward">2. Half of all scrolling now goes backward</h2>



<p>Among users who reverse direction in an AI Overview SERP, the median user spends 47.5% of total scrolling going back up the page. Without an AI Overview present, that figure is 27%.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1680" height="1824" src="https://searchengineland.com/wp-content/seloads/2026/05/median-back-scroll-share-almost-doubles-with-aios.png" alt="Median back scroll share almost doubles with AIOs" class="wp-image-478676" srcset="https://searchengineland.com/wp-content/seloads/2026/05/median-back-scroll-share-almost-doubles-with-aios.png 1680w, https://searchengineland.com/wp-content/seloads/2026/05/median-back-scroll-share-almost-doubles-with-aios-768x834.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/median-back-scroll-share-almost-doubles-with-aios-1415x1536.png 1415w" sizes="(max-width: 1680px) 100vw, 1680px" /></figure>
</div>


<p>The cursor data shows scrolling isn’t a one-way trip. On AI Overview SERPs, scrolling is roughly a 50/50 split between going down and going back up. That&#8217;s the behavior of someone re-reading, not someone scanning.</p>



<p>The 70-user study from May 2025 found this pattern qualitatively. <a href="https://www.growth-memo.com/i/163392865/insight">38% of AI Overview sessions in that study</a> showed reassurance-seeking clicks where users opened a second link &#8220;just to be sure.&#8221; The new clickstream data shows that the validation work has now moved onto the SERP itself. Users used to leave Google to validate a result. Now they validate by reversing back over results they already saw.</p>



<p>This is exactly the Netflix browse pattern. You hover on a tile. You scroll past it. Something pulls you back, so you scroll up to read the description again. The decision happens during the reversal, not the first pass.</p>



<p>For e-commerce and high-consideration decision categories, this is the most consequential finding in the study. Your listing in an AI Overview SERP isn&#8217;t getting one impression anymore. It&#8217;s getting 2 or 3, and the second impression is when comparison happens.</p>



<h2 class="wp-block-heading" id="h-3-search-type-no-longer-predicts-behavior">3. Search type no longer predicts behavior</h2>



<p>For 2 decades, search intent has been the foundational segmentation framework in SEO. You could predict how long a user would stay on a Google SERP by knowing what kind of search they did. The cursor data shows that&#8217;s no longer true when an AI Overview is on the page.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="2040" height="1208" src="https://searchengineland.com/wp-content/seloads/2026/05/ai-overviews-keep-searchers-on-serps-longer.png" alt="AI Overviews keep searchers on SERPs longer" class="wp-image-478677" srcset="https://searchengineland.com/wp-content/seloads/2026/05/ai-overviews-keep-searchers-on-serps-longer.png 2040w, https://searchengineland.com/wp-content/seloads/2026/05/ai-overviews-keep-searchers-on-serps-longer-768x455.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/ai-overviews-keep-searchers-on-serps-longer-1536x910.png 1536w" sizes="(max-width: 2040px) 100vw, 2040px" /></figure>
</div>


<p>At 21 seconds into a session without an AIO, only 12% of navigational searchers are still on the page. 32% of local searchers are. In classic search, time-on-page has always followed intent: navigational users leave fast because they know where they&#8217;re going, local users stay because the SERP is dense with maps and listings, informational users fall somewhere in between. That 20-point spread is what every SEO mental model is built around.</p>



<p>With an AI Overview present, the spread compresses to barely 6 points. All five intent types (informational, local, navigational, transactional, video) cluster between 41.9% and 48.5% time-on-page at 21 seconds. <strong>Intent stops predicting how long users will stay in the search results.</strong>



<p>This is the most novel finding in the study. Nothing in prior research has shown AI Overview collapses time-on-page differences between intent types into a single band. The 70-user UX study segmented by query risk, the 250-session AI Mode study by task type. Both showed intent matters for engagement. The new clickstream data says intent stops predicting how long users stay on the SERP once an AI Overview appears.</p>



<p>The scoping matters. This is a time-on-page finding, not a &#8220;behavior&#8221; finding. Scroll depth still varies by intent under AIO, and it actually reshuffles: local jumps from third deepest to first, video falls from first to third. That part of the story is in the next section.</p>



<p>The practical implication is uncomfortable. Most SEO playbooks recommend different optimization patterns by intent. Local pages get one treatment, transactional pages another, informational pages a third. However, our time-on-page data suggests that when an AI Overview is on the SERP, users stay for similar amounts of time regardless of why they searched. </p>



<p>The main takeaway here is that intent-based segmentation still matters for what content you write, but it matters less for predicting how long users will stick around on the SERP itself.</p>



<h2 class="wp-block-heading" id="h-4-brand-searches-lost-their-shortcut">4. Brand searches lost their shortcut</h2>



<p>Cursor activity for navigational queries (someone typing a brand name into Google) increased 40% when an AI Overview is on the page. Even users who came knowing where they wanted to go are sweeping the page first.</p>



<p>Without an AIO, navigational searchers were the most focused group in the study. They scored 19.7 on the cursor scatter measure (essentially, how much people bounce around the page), the lowest of any intent type. Only 12% were still active at 21 seconds. They came to Google with a destination, found it, and left.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="2040" height="1209" src="https://searchengineland.com/wp-content/seloads/2026/05/aios-increase-scrutiny-for-brand-searches.png" alt="AIOs increase scrutiny for brand searches" class="wp-image-478678" srcset="https://searchengineland.com/wp-content/seloads/2026/05/aios-increase-scrutiny-for-brand-searches.png 2040w, https://searchengineland.com/wp-content/seloads/2026/05/aios-increase-scrutiny-for-brand-searches-768x455.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/aios-increase-scrutiny-for-brand-searches-1536x910.png 1536w" sizes="(max-width: 2040px) 100vw, 2040px" /></figure>
</div>


<p>With an AI Overview present, that profile changes completely. Cursor scatter for navigational searchers jumps to 27.5. 45.8% are still active at 21 seconds. The brand-name shortcut, the fastest path through Google search for the past 20 years, no longer works the way it used to.</p>



<p>The 70-user study from May 2025 found that brand and authority is the first gate users apply when reading a SERP. They check who&#8217;s cited before they check what&#8217;s said. The new clickstream data shows that the gate now fires even when there&#8217;s nothing to gate against. A user who typed &#8220;Lenovo&#8221; is still doing the authority check on the AI Overview content first.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="2048" height="1317" src="https://searchengineland.com/wp-content/seloads/2026/05/Attention_scatter_by_intent_09-4-scaled.png" alt="AI Overviews compress attention" class="wp-image-478679" srcset="https://searchengineland.com/wp-content/seloads/2026/05/Attention_scatter_by_intent_09-4-scaled.png 2048w, https://searchengineland.com/wp-content/seloads/2026/05/Attention_scatter_by_intent_09-4-768x494.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/Attention_scatter_by_intent_09-4-1536x987.png 1536w" sizes="(max-width: 2048px) 100vw, 2048px" /></figure>
</div>


<p>This is the same Netflix pattern again. You open a show you&#8217;ve already decided to watch, but you pause first to read the synopsis and check the rating. The brand recall got you to the page. The browse decides whether you click through.</p>



<p>The implication for branded search: Brand recall is no longer enough on its own. Even users who searched for you specifically are now evaluating what&#8217;s around you on the SERP before they click through.</p>



<p><em><em>This post first appeared on the author’s website and is republished here with permission.</em></em>


The average Netflix user spends 18 minutes browsing the home screen before picking what to watch. They scroll past tiles, hover for trailers, scroll back to a show they almost picked, then circle back to the row they started in. The browse is the experience.
Search isn’t that different anymore. We just lacked the data to see it until now.
This week:




Four behavioral shifts that show up when an AI Overview is on the page, measured across 846,000 real Google sessions.
Why brand-name searches no longer give you the shortcut they used to.
One finding that should change how you write title tags and meta descriptions this quarter.
Eric Van Buskirk of Clickstream Solutions analyzed anonymized clickstream data provided by Surfer SEO, drawing findings from approximately 846,000 U.S.-based Google search sessions collected in February and March 2026. 
It’s the fifth user-behavior study on Google’s AI features in the last 12 months. The 70-user UX study from May 2025 used think-aloud and screen recording. The 250-session AI Mode study from October 2025 captured how users behave inside AI Mode itself. This one trades qualitative depth for the scale to find behavioral patterns the smaller studies couldn’t see.
View embedded content



For context: Prior public Google SERP mouse-tracking studies measured dozens of people. The largest had a few thousand tasks. This study analyzed queries from a panel of tens of thousands of Google Search users.
The most significant pattern shown: Users behave in opposite ways in AI Overviews and AI Mode. AI Mode is autoplay. AI Overviews is the Netflix browse.
This article covers four findings from the new study (full methodology here) and what they mean for how you write title tags and meta descriptions in 2026. 




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1. Same user, opposite behaviors
In AI Mode, users often accept the answer while continuing to evaluate the SERP in AI Overviews.
The April 2026 study of 185 high-stakes purchases found that in 88% of AI Mode tasks, users took the AI’s shortlist as-is, 74% picked the item ranked first, and 64% clicked nothing at all. AI Mode often behaves like a closed loop: The user reads the answer, picks from inside the answer, and moves on.




Note: N/A means the behavior doesn’t apply to that surface. AI Overviews don’t deliver shortlists like AI Mode does, and cursor/scroll metrics were only measured in AI Overview comparison environments.
New cursor tracking data on AI Overviews shows a different behavior pattern. Cursor positions spread across the equivalent of 83% of a viewport, compared with 66% when no AI Overview appeared. Users kept their cursors still 44% of the time, compared with 29% without an AIO. And in the median session, reverse-direction scrolling accounted for nearly half of scroll movement.
Taken together, this suggests that AI Overviews turn the SERP into more of a comparison environment. The user reads, pauses, weighs, returns to earlier content, and reconsiders before clicking.
The implication for strategy: AI Mode optimization and AI Overview optimization are not the same job. Showing up in an AI Mode shortlist is a visibility problem at the model layer. Showing up in an AI Overview is a comparison problem on the SERP itself.
2. Half of all scrolling now goes backward
Among users who reverse direction in an AI Overview SERP, the median user spends 47.5% of total scrolling going back up the page. Without an AI Overview present, that figure is 27%.




The cursor data shows scrolling isn’t a one-way trip. On AI Overview SERPs, scrolling is roughly a 50/50 split between going down and going back up. That’s the behavior of someone re-reading, not someone scanning.
The 70-user study from May 2025 found this pattern qualitatively. 38% of AI Overview sessions in that study showed reassurance-seeking clicks where users opened a second link “just to be sure.” The new clickstream data shows that the validation work has now moved onto the SERP itself. Users used to leave Google to validate a result. Now they validate by reversing back over results they already saw.
This is exactly the Netflix browse pattern. You hover on a tile. You scroll past it. Something pulls you back, so you scroll up to read the description again. The decision happens during the reversal, not the first pass.
For e-commerce and high-consideration decision categories, this is the most consequential finding in the study. Your listing in an AI Overview SERP isn’t getting one impression anymore. It’s getting 2 or 3, and the second impression is when comparison happens.
3. Search type no longer predicts behavior
For 2 decades, search intent has been the foundational segmentation framework in SEO. You could predict how long a user would stay on a Google SERP by knowing what kind of search they did. The cursor data shows that’s no longer true when an AI Overview is on the page.




At 21 seconds into a session without an AIO, only 12% of navigational searchers are still on the page. 32% of local searchers are. In classic search, time-on-page has always followed intent: navigational users leave fast because they know where they’re going, local users stay because the SERP is dense with maps and listings, informational users fall somewhere in between. That 20-point spread is what every SEO mental model is built around.
With an AI Overview present, the spread compresses to barely 6 points. All five intent types (informational, local, navigational, transactional, video) cluster between 41.9% and 48.5% time-on-page at 21 seconds. Intent stops predicting how long users will stay in the search results.



This is the most novel finding in the study. Nothing in prior research has shown AI Overview collapses time-on-page differences between intent types into a single band. The 70-user UX study segmented by query risk, the 250-session AI Mode study by task type. Both showed intent matters for engagement. The new clickstream data says intent stops predicting how long users stay on the SERP once an AI Overview appears.
The scoping matters. This is a time-on-page finding, not a “behavior” finding. Scroll depth still varies by intent under AIO, and it actually reshuffles: local jumps from third deepest to first, video falls from first to third. That part of the story is in the next section.
The practical implication is uncomfortable. Most SEO playbooks recommend different optimization patterns by intent. Local pages get one treatment, transactional pages another, informational pages a third. However, our time-on-page data suggests that when an AI Overview is on the SERP, users stay for similar amounts of time regardless of why they searched. 
The main takeaway here is that intent-based segmentation still matters for what content you write, but it matters less for predicting how long users will stick around on the SERP itself.
4. Brand searches lost their shortcut
Cursor activity for navigational queries (someone typing a brand name into Google) increased 40% when an AI Overview is on the page. Even users who came knowing where they wanted to go are sweeping the page first.
Without an AIO, navigational searchers were the most focused group in the study. They scored 19.7 on the cursor scatter measure (essentially, how much people bounce around the page), the lowest of any intent type. Only 12% were still active at 21 seconds. They came to Google with a destination, found it, and left.




With an AI Overview present, that profile changes completely. Cursor scatter for navigational searchers jumps to 27.5. 45.8% are still active at 21 seconds. The brand-name shortcut, the fastest path through Google search for the past 20 years, no longer works the way it used to.
The 70-user study from May 2025 found that brand and authority is the first gate users apply when reading a SERP. They check who’s cited before they check what’s said. The new clickstream data shows that the gate now fires even when there’s nothing to gate against. A user who typed “Lenovo” is still doing the authority check on the AI Overview content first.




This is the same Netflix pattern again. You open a show you’ve already decided to watch, but you pause first to read the synopsis and check the rating. The brand recall got you to the page. The browse decides whether you click through.
The implication for branded search: Brand recall is no longer enough on its own. Even users who searched for you specifically are now evaluating what’s around you on the SERP before they click through.
This post first appeared on the author’s website and is republished here with permission.

New clickstream data shows AI Overviews reshape user behavior, from reverse scrolling to longer SERP evaluation across search intents.

Users behave differently in AI Overviews vs. AI Mode

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/11/How-to-get-cited-by-ChatGPT-The-content-traits-LLMs-quote-most.png" class="attachment-large size-large wp-post-image" alt="How to get cited by ChatGPT: The content traits LLMs quote most" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/11/How-to-get-cited-by-ChatGPT-The-content-traits-LLMs-quote-most.png 1920w, https://searchengineland.com/wp-content/seloads/2025/11/How-to-get-cited-by-ChatGPT-The-content-traits-LLMs-quote-most-768x432.png 768w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>OpenAI is expanding ChatGPT into performance advertising with conversion-focused ads, tracking tools and pay-for-results pricing.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/11/How-to-get-cited-by-ChatGPT-The-content-traits-LLMs-quote-most.png" class="attachment-large size-large wp-post-image" alt="How to get cited by ChatGPT: The content traits LLMs quote most" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/11/How-to-get-cited-by-ChatGPT-The-content-traits-LLMs-quote-most.png 1920w, https://searchengineland.com/wp-content/seloads/2025/11/How-to-get-cited-by-ChatGPT-The-content-traits-LLMs-quote-most-768x432.png 768w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>OpenAI is preparing to expand its advertising ambitions beyond brand awareness and into performance marketing, with new conversion-oriented ad formats designed to drive measurable actions.</p>



<p>The move positions OpenAI more directly against Google and Meta by targeting the massive market of small and mid-sized businesses focused on leads, bookings and sales — not just impressions.</p>



<p><strong>What’s happening.</strong> According to The Information, OpenAI has been telling advertisers and ad tech firms that it wants to attract smaller local businesses, including companies like dry cleaners, car washes and appointment-based services.</p>



<p>The company is also preparing ad formats designed to encourage direct actions such as:</p>



<ul class="wp-block-list">
<li>purchases,</li>



<li>appointment bookings,</li>



<li>and contact form submissions.</li>
</ul>



<p>Advertisers testing the formats would reportedly only pay when those actions occur, bringing ChatGPT advertising closer to traditional performance marketing models.</p>



<p><strong>Why we care. </strong>OpenAI is moving beyond experimental AI ads and building a performance advertising ecosystem designed to compete more directly with Google and Meta. The addition of conversion-based pricing, pixels and API tracking signals that ChatGPT could soon become a serious channel for lead generation, bookings and ecommerce-driven advertising.</p>



<p><strong>Between the lines.</strong> OpenAI is also building out the infrastructure needed to prove ad performance.</p>



<p>To test the campaigns, advertisers will need to install OpenAI’s ad pixel on their websites to track user activity after ad interactions. The company is additionally encouraging advertisers to connect internal systems through its API, allowing businesses to send conversion and customer action data back into OpenAI’s systems.</p>



<p>That creates a more familiar ad-tech setup resembling the measurement ecosystems long used by Google, Meta and other performance advertising platforms.</p>



<p><strong>The bigger picture. </strong>OpenAI’s push into conversion-focused advertising signals a broader evolution of AI platforms from information tools into transactional ecosystems.</p>



<p>If successful, ChatGPT could become more than a discovery surface — it could become a lead generation and commerce platform competing directly for performance ad budgets.</p>



<p><strong>What to watch. </strong>Measurement accuracy may quickly become one of the biggest challenges for OpenAI’s ad ambitions. Pixels remain vulnerable to browser restrictions and ad blockers, meaning API-based conversion tracking may become increasingly important for advertisers looking to prove ROI inside AI-driven ad experiences.</p>



<p><strong>First seen.</strong> Digital Marketer Glenn Gabe shared an excerpt from the The Information article, on <a href="https://x.com/glenngabe/status/2059314982282563938">X</a>.</p>



<p><strong>Dig Deeper. </strong><a href="https://www.theinformation.com/articles/openais-next-ad-move-going-small-scale-big">OpenAI Targets Smaller Advertisers With New ChatGPT Ads</a> (subscription needed)</p>


OpenAI is preparing to expand its advertising ambitions beyond brand awareness and into performance marketing, with new conversion-oriented ad formats designed to drive measurable actions.
The move positions OpenAI more directly against Google and Meta by targeting the massive market of small and mid-sized businesses focused on leads, bookings and sales — not just impressions.
What’s happening. According to The Information, OpenAI has been telling advertisers and ad tech firms that it wants to attract smaller local businesses, including companies like dry cleaners, car washes and appointment-based services.
The company is also preparing ad formats designed to encourage direct actions such as:
purchases,
appointment bookings,
and contact form submissions.
Advertisers testing the formats would reportedly only pay when those actions occur, bringing ChatGPT advertising closer to traditional performance marketing models.
Why we care. OpenAI is moving beyond experimental AI ads and building a performance advertising ecosystem designed to compete more directly with Google and Meta. The addition of conversion-based pricing, pixels and API tracking signals that ChatGPT could soon become a serious channel for lead generation, bookings and ecommerce-driven advertising.
Between the lines. OpenAI is also building out the infrastructure needed to prove ad performance.
To test the campaigns, advertisers will need to install OpenAI’s ad pixel on their websites to track user activity after ad interactions. The company is additionally encouraging advertisers to connect internal systems through its API, allowing businesses to send conversion and customer action data back into OpenAI’s systems.
That creates a more familiar ad-tech setup resembling the measurement ecosystems long used by Google, Meta and other performance advertising platforms.
The bigger picture. OpenAI’s push into conversion-focused advertising signals a broader evolution of AI platforms from information tools into transactional ecosystems.
If successful, ChatGPT could become more than a discovery surface — it could become a lead generation and commerce platform competing directly for performance ad budgets.
What to watch. Measurement accuracy may quickly become one of the biggest challenges for OpenAI’s ad ambitions. Pixels remain vulnerable to browser restrictions and ad blockers, meaning API-based conversion tracking may become increasingly important for advertisers looking to prove ROI inside AI-driven ad experiences.
First seen. Digital Marketer Glenn Gabe shared an excerpt from the The Information article, on X.
Dig Deeper. OpenAI Targets Smaller Advertisers With New ChatGPT Ads (subscription needed)

OpenAI is expanding ChatGPT into performance advertising with conversion-focused ads, tracking tools and pay-for-results pricing.

OpenAI is preparing conversion-focused ads for ChatGPT

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/05/google-agent-future.png" class="attachment-large size-large wp-post-image" alt="Google agent future" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/05/google-agent-future.png 1920w, https://searchengineland.com/wp-content/seloads/2026/05/google-agent-future-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/google-agent-future-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/05/google-agent-future-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Google CEO says AI will reshape Search into a task-running system, even as Google insists it will keep linking users to the open web.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/05/google-agent-future.png" class="attachment-large size-large wp-post-image" alt="Google agent future" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/05/google-agent-future.png 1920w, https://searchengineland.com/wp-content/seloads/2026/05/google-agent-future-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/google-agent-future-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/05/google-agent-future-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Google CEO Sundar Pichai said Google’s AI search box, app-building tools, and agent products will eventually converge.</p>



<p>Pichai also rejected publisher fears that Google will stop sending traffic to the web in an interview with Nilay Patel, editor-in-chief of The Verge. </p>



<ul class="wp-block-list">
<li>“Through it all, we are very committed to both meeting user expectations and also connecting them to what’s out on the web,” Pichai said.</li>
</ul>



<p>However, Pichai&#8217;s comments showed why those fears are growing: Google is moving Search toward conversations, agents, and AI tools that can answer questions or complete tasks for users without requiring a click.</p>



<p><strong>Why we care.</strong> Many people worried AI Mode would become the default Search experience at I/O. It didn’t, and many people were relieved. AI Mode still isn’t the default Search experience, but Pichai outlined a future where Search, Gemini, and agents merge into a single AI layer for finding information, creating content, and completing tasks.</p>



<p><strong>Agents are the future.</strong> AI agents are the next major change for Search and the web, Pichai said:</p>



<ul class="wp-block-list">
<li>“I look at agents, and that is the next evolution of the web. I think it will evolve the web pretty profoundly.”</li>
</ul>



<p>Google is building agentic tools across Search, Gemini, Spark, and Antigravity. Pichai said those products should eventually come together for users. Pichai has previously said that he sees <a href="https://searchengineland.com/sundar-pichai-google-search-agent-manager-473842">Google Search evolving into an ‘agent manager’</a>.</p>



<p><strong>One product. </strong>Asked whether Google’s AI search box, app-building tools and agent products should become one product, Pichai said: “It will.” </p>



<p>Pichai said agents should work in the background when users plan trips, build things or complete tasks. Pichai said Google is still building the pieces needed for that shift.</p>



<ul class="wp-block-list">
<li>“We are laying a lot of the primitives of what we need for agents to work end to end, and more importantly, for AI to work,” he said.</li>
</ul>



<p><strong><em>Dig deeper. <a href="https://searchengineland.com/google-search-gemini-converge-diverge-471012">Google’s Liz Reid: Search and Gemini may converge, or diverge further</a></em></strong>



<p><strong>Google rejects Google Zero. </strong>Patel asked Pichai about Condé Nast CEO Roger Lynch’s recent comment that the publisher was <a href="https://searchengineland.com/conde-nast-search-single-digit-traffic-477358">planning as if search traffic would fall to zero.</a>



<ul class="wp-block-list">
<li>“That is <a href="https://searchengineland.com/google-zero-misses-real-problem-473050">Google Zero</a>” Patel said. “Condé Nast is saying, ‘We’re assuming that search will go to zero.’ How would you respond to that?”</li>
</ul>



<p>The information market has changed far beyond Google, Pichai said:</p>



<ul class="wp-block-list">
<li>“The information ecosystem is so much broader beyond Google, by far. We see it in the data, you see it everywhere,” Pichai said.</li>
</ul>



<p>Pichai said publishers have spent years adjusting to new formats, platforms, and user habits.</p>



<ul class="wp-block-list">
<li>“It’s exceptionally dynamic, and so it makes sense to me every publisher is adapting to this new world.”</li>
</ul>



<p><strong>Google says some clicks are going away. </strong>Patel pressed Pichai on whether publishers should plan for a future where search traffic falls to zero, citing Lynch’s comment that his teams were told to “assume there is no search.”</p>



<p>Pichai declined to tell publishers how to run their businesses.</p>



<ul class="wp-block-list">
<li>“I’m not in a position to tell such an iconic publisher what they should think about their business or plan,” Pichai said. “If they are building content that is high-quality and people like it, I expect us to reflect that in our products. That much I can commit to them.”</li>
</ul>



<p>He also said Search is already filtering out some visits.</p>



<ul class="wp-block-list">
<li>“As the technology improves, low-quality clicks get filtered out,” he said. “That’s a natural evolution we see. We see it in our metrics. Bounce clicks are going down.”</li>
</ul>



<p><strong>Google points to subscriptions. </strong>Subscriptions are one way Google is adapting to publisher business models, Pichai said.</p>



<ul class="wp-block-list">
<li>“One of the small features we have done, but very important I think, is if you’ve subscribed to something, we reflect that as a preferred source for you as a user.&#8221;</li>



<li>“We are adapting to the fact that publishers are increasingly turning to subscription offerings, too.”</li>
</ul>



<p>The interview didn&#8217;t address why many publishers moved harder into subscriptions: Because they could no longer rely on search traffic the way they once did.</p>



<p id="h-search-had-to-move-faster"><strong>Search had to move faster. </strong>Pichai said Google reorganized Search because the product needed to move faster in the AI era.</p>



<ul class="wp-block-list">
<li>“Search needed to move faster, and Search was split across many leaders,” he said.</li>
</ul>



<p>Google put Search under Elizabeth Reid, with Nick Fox leading the broader area. Josh Woodward also helped lead Labs and later Gemini work. The goal was to make Google “set up well for this moment where we need to move faster as a company, which means we need to make faster decisions,” Pichai said.</p>



<p><strong>The interview. </strong><a href="https://www.theverge.com/podcast/936445/sundar-pichai-ai-search-google-zero-youtube-web" target="_blank" rel="noopener">Sundar Pichai on AI, the future of search, and what’s happening to the web</a>


Google CEO Sundar Pichai said Google’s AI search box, app-building tools, and agent products will eventually converge.
Pichai also rejected publisher fears that Google will stop sending traffic to the web in an interview with Nilay Patel, editor-in-chief of The Verge. 
“Through it all, we are very committed to both meeting user expectations and also connecting them to what’s out on the web,” Pichai said.
However, Pichai’s comments showed why those fears are growing: Google is moving Search toward conversations, agents, and AI tools that can answer questions or complete tasks for users without requiring a click.
Why we care. Many people worried AI Mode would become the default Search experience at I/O. It didn’t, and many people were relieved. AI Mode still isn’t the default Search experience, but Pichai outlined a future where Search, Gemini, and agents merge into a single AI layer for finding information, creating content, and completing tasks.
Agents are the future. AI agents are the next major change for Search and the web, Pichai said:
“I look at agents, and that is the next evolution of the web. I think it will evolve the web pretty profoundly.”
Google is building agentic tools across Search, Gemini, Spark, and Antigravity. Pichai said those products should eventually come together for users. Pichai has previously said that he sees Google Search evolving into an ‘agent manager’.
One product. Asked whether Google’s AI search box, app-building tools and agent products should become one product, Pichai said: “It will.” 
Pichai said agents should work in the background when users plan trips, build things or complete tasks. Pichai said Google is still building the pieces needed for that shift.
“We are laying a lot of the primitives of what we need for agents to work end to end, and more importantly, for AI to work,” he said.
Dig deeper. Google’s Liz Reid: Search and Gemini may converge, or diverge further



Google rejects Google Zero. Patel asked Pichai about Condé Nast CEO Roger Lynch’s recent comment that the publisher was planning as if search traffic would fall to zero.




“That is Google Zero” Patel said. “Condé Nast is saying, ‘We’re assuming that search will go to zero.’ How would you respond to that?”
The information market has changed far beyond Google, Pichai said:
“The information ecosystem is so much broader beyond Google, by far. We see it in the data, you see it everywhere,” Pichai said.
Pichai said publishers have spent years adjusting to new formats, platforms, and user habits.
“It’s exceptionally dynamic, and so it makes sense to me every publisher is adapting to this new world.”
Google says some clicks are going away. Patel pressed Pichai on whether publishers should plan for a future where search traffic falls to zero, citing Lynch’s comment that his teams were told to “assume there is no search.”
Pichai declined to tell publishers how to run their businesses.
“I’m not in a position to tell such an iconic publisher what they should think about their business or plan,” Pichai said. “If they are building content that is high-quality and people like it, I expect us to reflect that in our products. That much I can commit to them.”
He also said Search is already filtering out some visits.
“As the technology improves, low-quality clicks get filtered out,” he said. “That’s a natural evolution we see. We see it in our metrics. Bounce clicks are going down.”
Google points to subscriptions. Subscriptions are one way Google is adapting to publisher business models, Pichai said.
“One of the small features we have done, but very important I think, is if you’ve subscribed to something, we reflect that as a preferred source for you as a user.”
“We are adapting to the fact that publishers are increasingly turning to subscription offerings, too.”
The interview didn’t address why many publishers moved harder into subscriptions: Because they could no longer rely on search traffic the way they once did.
Search had to move faster. Pichai said Google reorganized Search because the product needed to move faster in the AI era.
“Search needed to move faster, and Search was split across many leaders,” he said.
Google put Search under Elizabeth Reid, with Nick Fox leading the broader area. Josh Woodward also helped lead Labs and later Gemini work. The goal was to make Google “set up well for this moment where we need to move faster as a company, which means we need to make faster decisions,” Pichai said.
The interview. Sundar Pichai on AI, the future of search, and what’s happening to the web

Google CEO says AI will reshape Search into a task-running system, even as Google insists it will keep linking users to the open web.

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