<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-ads-content-exclusion.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" fetchpriority="high" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-ads-content-exclusion.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-ads-content-exclusion-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-ads-content-exclusion-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-ads-content-exclusion-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>Microsoft now lets advertisers block Audience Ads from appearing next to specific page titles, for more control over ad placement.

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-ads-content-exclusion.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-ads-content-exclusion.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-ads-content-exclusion-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-ads-content-exclusion-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-ads-content-exclusion-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>
<p class="wp-block-paragraph">Microsoft Advertising is rolling out Excluded content terms, a new brand safety control that lets advertisers stop Audience Ads from appearing alongside specific page titles.</p>



<p class="wp-block-paragraph">The feature gives marketers another way to protect brand reputation beyond website exclusions and sensitive content categories.</p>



<p class="wp-block-paragraph"><strong>What&#8217;s happening</strong>. Advertisers can now create lists of unwanted words or phrases that prevent their ads from showing next to page titles containing those terms.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="698" height="388" src="https://searchengineland.com/wp-content/seloads/2026/08/content-exclusion.png" alt="" class="wp-image-484356"/></figure>



<p class="wp-block-paragraph">Excluded content terms can be added at the account or campaign level, with support for up to 1,000 terms. Campaign-level exclusions are automatically applied across all campaigns in the account, reducing the need to recreate lists for future campaigns.</p>



<p class="wp-block-paragraph">The feature is managed through Tools &gt; Content suitability &gt; Excluded content terms and is rolling out gradually, so not all advertisers have access yet.</p>



<p class="wp-block-paragraph"><strong>Why we care</strong>. While website exclusion lists block specific domains and content exclusions filter broad sensitive categories, excluded content terms offer much more granular control. Brands can avoid appearing next to page titles that mention topics, products or phrases they consider unsuitable, even if the page itself doesn&#8217;t fall into a blocked content category.</p>



<p class="wp-block-paragraph"><strong>The bigger picture</strong>. Microsoft continues expanding its content suitability controls as advertisers place greater emphasis on brand safety. The new feature complements existing protections, including website exclusion lists and IAS-powered content exclusions that already filter ads away from high-risk categories such as adult content, gambling, hate speech and violence.</p>



<p class="wp-block-paragraph"><strong>Bottom line</strong>. <a href="https://help.ads.microsoft.com/#apex/ads/en/60234/0">Excluded content terms</a> give Microsoft Advertising users a more precise way to control where Audience Ads appear, helping brands avoid unwanted associations without relying solely on website or category-level exclusions.</p>


Microsoft Advertising is rolling out Excluded content terms, a new brand safety control that lets advertisers stop Audience Ads from appearing alongside specific page titles.
The feature gives marketers another way to protect brand reputation beyond website exclusions and sensitive content categories.
What’s happening. Advertisers can now create lists of unwanted words or phrases that prevent their ads from showing next to page titles containing those terms.




Excluded content terms can be added at the account or campaign level, with support for up to 1,000 terms. Campaign-level exclusions are automatically applied across all campaigns in the account, reducing the need to recreate lists for future campaigns.
The feature is managed through Tools > Content suitability > Excluded content terms and is rolling out gradually, so not all advertisers have access yet.
Why we care. While website exclusion lists block specific domains and content exclusions filter broad sensitive categories, excluded content terms offer much more granular control. Brands can avoid appearing next to page titles that mention topics, products or phrases they consider unsuitable, even if the page itself doesn’t fall into a blocked content category.
The bigger picture. Microsoft continues expanding its content suitability controls as advertisers place greater emphasis on brand safety. The new feature complements existing protections, including website exclusion lists and IAS-powered content exclusions that already filter ads away from high-risk categories such as adult content, gambling, hate speech and violence.
Bottom line. Excluded content terms give Microsoft Advertising users a more precise way to control where Audience Ads appear, helping brands avoid unwanted associations without relying solely on website or category-level exclusions.

Microsoft now lets advertisers block Audience Ads from appearing next to specific page titles, for more control over ad placement.

Microsoft Advertising adds excluded content terms for Audience Ads

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/08/Does-topical-focus-make-your-brand-more-visible-featured-image.png" class="attachment-large size-large wp-post-image" alt="Does topical focus make your brand more visible - featured-image" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Does-topical-focus-make-your-brand-more-visible-featured-image.png 1920w, https://searchengineland.com/wp-content/seloads/2026/08/Does-topical-focus-make-your-brand-more-visible-featured-image-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Does-topical-focus-make-your-brand-more-visible-featured-image-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Does-topical-focus-make-your-brand-more-visible-featured-image-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>New research reveals why AI cites brands across many topics but recommends them only where they've built repeat topical authority.


<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/08/Does-topical-focus-make-your-brand-more-visible-featured-image.png" class="attachment-large size-large wp-post-image" alt="Does topical focus make your brand more visible - featured-image" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Does-topical-focus-make-your-brand-more-visible-featured-image.png 1920w, https://searchengineland.com/wp-content/seloads/2026/08/Does-topical-focus-make-your-brand-more-visible-featured-image-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Does-topical-focus-make-your-brand-more-visible-featured-image-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Does-topical-focus-make-your-brand-more-visible-featured-image-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p class="wp-block-paragraph">Should you keep your content strategy focused on a few core topics, or can you go broad to really widen the “funnel”?</p>



<p class="wp-block-paragraph">In <a href="https://www.growth-memo.com/p/does-topical-authority-matter-in">Does topical authority matter in AI Search?</a>, I tested the core topical-authority claim in AEO by examining repeat presence across categories. I found that there is indeed a pattern of “category owners” who sustain their lead over months.&nbsp;</p>



<p class="wp-block-paragraph">This memo asks a different question: Once a brand has proven authority in one topic or category, does that authority carry into adjacent or distant categories? And if so, does it still look like an LLM <em>recommendation</em> or only a <em>source</em> in a citation set?</p>



<p class="wp-block-paragraph">In this memo:</p>



<ul class="wp-block-list">
<li>Brands have good chances of getting cited outside their established expertise, but not mentioned.&nbsp;</li>



<li>A small but robust effect that suggests brands that “own” a category are more successful at expanding into other categories.</li>



<li>The topical authority effect in AI Search does not show up equally across industries.</li>



<li>A category is not won until the brand earns repeat mentions, not just citations.</li>
</ul>



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



<h2 id="h-the-data-behind-the-findings" class="wp-block-heading">The data behind the findings</h2>



<p class="wp-block-paragraph">To test the hypothesis, Semrush was kind enough to provide me with a broad sample of AI Visibility Toolkit data across about 1,000 categories. I ran 3 tests:</p>



<ul class="wp-block-list">
<li>The <strong>relatedness test </strong>compares a brand&#8217;s new category appearances with categories where it had already appeared in at least 3 of 5 prompts.</li>



<li>The <strong>future performance test</strong> traces brand mention and citation appearance across 6 months.</li>



<li>The <strong>breadth vs depth test</strong> compares whether brands that are cited or mentioned in many categories see any detriment in covering content topics in breadth vs depth.</li>
</ul>



<p class="wp-block-paragraph">Semrush provided the following U.S. ChatGPT data from the AI Visibility Toolkit: 1,094 categories, 5 prompt variants per category, January through June 2026.&nbsp;</p>



<ul class="wp-block-list">
<li>The breadth tests draw on 283,215 citations and 76,493 named-brand-mention observations, each paired with the following month&#8217;s outcome.&nbsp;</li>



<li>The relatedness test draws on 45,578 expansion appearances by 1,458 mapped brand entities.&nbsp;</li>



<li>Every number here is an association after controls, so the models cannot prove that publishing or category expansion caused the later result.</li>



<li>Full methodology, measures, models, and scope limits are at the end of this Memo.</li>
</ul>



<h2 id="h-1-topical-authority-is-different-for-mentions-vs-citations" class="wp-block-heading">1. Topical Authority is different for mentions vs citations</h2>



<p class="wp-block-paragraph">The <a href="https://www.growth-memo.com/p/how-to-measure-topical-authority">Topical Authority</a> concept in SEO says that brands cannot or should not try to rank in all sorts of topics, but instead focus on topics that are closest to their core expertise. There are exceptions. But is that also true in AI Search? To find out, I embedded the ~1,000 categories in the study data and matched them against the core expertise of the brands we examined.</p>



<p class="wp-block-paragraph">The results: Brands have good chances of getting cited outside their established expertise, but not mentioned. In distant categories from their core expertise (based on semantic similarity measurements), 50% appearances are citations and only 25% are mentions. Only 9% get both.&nbsp;</p>



<p class="wp-block-paragraph">In close categories that are more topically relevant to a brand, 74% are cited, 44% are named, and 34% get both.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="1680" height="1944" src="https://searchengineland.com/wp-content/seloads/2026/08/image-8.png" alt="" class="wp-image-484283" srcset="https://searchengineland.com/wp-content/seloads/2026/08/image-8.png 1680w, https://searchengineland.com/wp-content/seloads/2026/08/image-8-768x889.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/image-8-1327x1536.png 1327w" sizes="(max-width: 1680px) 100vw, 1680px" /></figure>



<p class="wp-block-paragraph">Citation-only presence barely changes across category relevance: 41% in distant categories versus 40% in close ones.&nbsp;</p>



<p class="wp-block-paragraph">In other words, you can be a source on pretty much any topic if it matches the regular criteria for source citations. But the AI <em>recommends</em> you in core topics.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="1680" height="1899" src="https://searchengineland.com/wp-content/seloads/2026/08/image-10.png" alt="" class="wp-image-484285" srcset="https://searchengineland.com/wp-content/seloads/2026/08/image-10.png 1680w, https://searchengineland.com/wp-content/seloads/2026/08/image-10-768x868.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/image-10-1359x1536.png 1359w" sizes="(max-width: 1680px) 100vw, 1680px" /></figure>



<h2 id="h-2-topical-authority-requires-depth" class="wp-block-heading">2. Topical Authority requires depth</h2>



<p class="wp-block-paragraph">A domain can surface once in 20 categories and own none of them.&nbsp;</p>



<ul class="wp-block-list">
<li>Presence in answers for the topic measures whether the brand appears at all.</li>



<li>Depth in the topic measures how many of the 5 prompt variants the brand appears in.</li>



<li>Category performance measures its share of the citations or brand mentions in the answers.</li>
</ul>



<p class="wp-block-paragraph">In <a href="https://www.growth-memo.com/p/does-topical-authority-matter-in">Does topical authority matter in AI search?</a>, we saw repeat presence as the early signal of topical authority. This Memo adds a constraint: The authority only carries brand recognition into categories that are close to the brand&#8217;s demonstrated expertise.</p>



<p class="wp-block-paragraph">Once again, I found no detriment when showing up across many categories <em>for citations</em>. The association rises from +0.012 when appearing in 1/5 category prompts to +0.062 when a domain appears in all 5. Being cited in many categories does not show a spread-thin effect in this sample.</p>



<p class="wp-block-paragraph">Brand mentions tell a different story. Being mentioned in 1/5 category prompts across the categories a brand appears in is associated with a lower mention share at -0.051.&nbsp;</p>



<p class="wp-block-paragraph">But at 5/5, it’s slightly positive. In plain words, we can see a small but robust effect that suggests brands that “own” a category are more successful at expanding into other categories.&nbsp;</p>



<p class="wp-block-paragraph">Overall, this data shows trying to be everywhere is associated with fewer brand mentions; being in many categories you <em>actually</em> own may help slightly. The &#8220;spread too thin&#8221; penalty is really a penalty for shallow presence, not for breadth itself.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="1680" height="1824" src="https://searchengineland.com/wp-content/seloads/2026/08/image-9.png" alt="" class="wp-image-484284" srcset="https://searchengineland.com/wp-content/seloads/2026/08/image-9.png 1680w, https://searchengineland.com/wp-content/seloads/2026/08/image-9-768x834.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/image-9-1415x1536.png 1415w" sizes="(max-width: 1680px) 100vw, 1680px" /></figure>



<p class="wp-block-paragraph">Keep in mind that there is no defensible universal category limit. The data does not support the claim that a site can serve an unlimited number of categories, either.&nbsp;</p>



<p class="wp-block-paragraph">The other thing is that the associations here are <em>very</em> light, and we should be careful not to overvalue the effect on topical authority on overall visibility. Other factors, like <a href="https://www.growth-memo.com/p/the-science-of-how-ai-pays-attention">writing style</a>, overall <a href="https://www.growth-memo.com/p/how-you-can-track-brand-authority">brand authority</a>, and <a href="https://www.growth-memo.com/p/topics-matter-for-third-party-authority">third-party web mentions</a> might outweigh topical authority.</p>



<p class="wp-block-paragraph">A checklist beats a style opinion when 4 writers are shipping against the same standard. The <a href="https://www.growth-memo.com/p/the-science-of-how-ai-pays-attention?open=false#%C2%A7for-premium-subscribers-your-implementation-kit-is-below">AI Writing Implementation Kit</a> gives your team the audit criteria in writing. Premium subscribers get the kit <a href="https://www.growth-memo.com/p/exclusive-growth-premium-resources">plus 40+ other tools, checklists, and stakeholder decks</a>.</p>



<h2 id="h-3-not-all-industries-show-topical-authority-equally" class="wp-block-heading">3. Not all industries show Topical Authority equally</h2>



<p class="wp-block-paragraph">The topical authority effect in AI Search does not show up equally across industries.</p>



<p class="wp-block-paragraph">Finance and real estate show the strongest repeat-citation pattern:</p>



<ul class="wp-block-list">
<li>In finance, the citation-breadth association rises from +0.054 at 1 prompt variant to +0.139 at all 5.</li>



<li>Real estate rises from +0.021 to +0.135.</li>
</ul>



<p class="wp-block-paragraph">In those industries, broader repeated coverage is associated with stronger source visibility. That makes category expansion a viable citation strategy. That does not mean every finance or real estate brand can win every adjacent category.&nbsp;</p>



<p class="wp-block-paragraph">It means we don&#8217;t see an obvious “spread too thin” penalty for sources in these markets. When a domain appears repeatedly across a category’s prompt variants, it tends to hold more citation shares in the following month.</p>



<p class="wp-block-paragraph">Legal and healthcare place a tighter constraint on brand mentions:</p>



<ul class="wp-block-list">
<li>In legal, the mention-breadth association remains negative even at full 5-prompt coverage, -0.058.</li>



<li>Healthcare follows the same pattern at -0.037.</li>
</ul>



<p class="wp-block-paragraph">More consistent coverage can improve a domain’s citation position, but it does not reliably translate into more named-brand visibility. A likely explanation is that these topics involve higher-stakes choices, where being a credible source is not enough to make a brand the recommended answer.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="1680" height="1824" src="https://searchengineland.com/wp-content/seloads/2026/08/image-11.png" alt="" class="wp-image-484286" srcset="https://searchengineland.com/wp-content/seloads/2026/08/image-11.png 1680w, https://searchengineland.com/wp-content/seloads/2026/08/image-11-768x834.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/image-11-1415x1536.png 1415w" sizes="(max-width: 1680px) 100vw, 1680px" /></figure>



<p class="wp-block-paragraph"><em>Positive means wider breadth is associated with higher next-month share after controls; negative means lower share.</em>



<p class="wp-block-paragraph">The practical implication is simple: Finance and real-estate teams can test expansion into related categories with citations as an early success metric. Legal and healthcare teams should use a higher bar. A category is not won until the brand earns repeat mentions, not just citations.</p>



<h2 id="h-methodology" class="wp-block-heading">Methodology</h2>



<p class="wp-block-paragraph"><strong>Sample</strong>



<p class="wp-block-paragraph">The study uses Semrush&#8217;s U.S. ChatGPT dataset from the <a href="https://www.semrush.com/ai-seo/overview/">AI Visibility Toolkit</a> from January through June 2026:</p>



<ul class="wp-block-list">
<li>It includes 1,094 categories and 5 prompt variants per category in every monthly snapshot.</li>



<li>The breadth models use 283,215 citations and 76,493 named-brand-mention domain-category observations from January through May. Each current-month observation has a next-month outcome. A domain that disappears from the category receives a share of zero.</li>



<li>The relatedness analysis uses 45,578 expansion appearances by 1,458 mapped brand entities across all 1,094 categories. It has February through May, starting snapshots because each appearance needs prior history and a following-month outcome.</li>
</ul>



<p class="wp-block-paragraph"><strong>Measures</strong>



<p class="wp-block-paragraph">Citation share is a domain&#8217;s share of all source citations in a category&#8217;s answers. Brand-mention share is its share of all named brand mentions. The study does not combine them because ChatGPT produces more citations than named brand mentions.</p>



<p class="wp-block-paragraph">Depth measures the number of a category&#8217;s 5 prompt variants where a domain appears. Breadth measures the number of categories where it appears in the current month. The sensitivity test defines a breadth category using 1one through 5five prompt appearances.</p>



<p class="wp-block-paragraph">For the relatedness analysis, demonstrated expertise means appearing in at least 3three prompt variants in a category before the target-month appearance. An expansion appearance is a brand showing up in a target category where it had not previously reached that depth. Category relationship comes from multilingual semantic similarity between the target category&#8217;s title and prompts and the brand&#8217;s prior expert categories.</p>



<p class="wp-block-paragraph"><strong>Models and controls</strong>



<p class="wp-block-paragraph">The breadth models estimate the relationship between current breadth and next-month citation or mention share within the same category. They control for current share, current depth, the other signal&#8217;s share, Authority Score, organic traffic, branded search demand, and category-month differences.</p>



<p class="wp-block-paragraph">The relatedness model compares close and distant expansion appearances while controlling for current citation and mention depth, current citation and mention share, breadth, Authority Score, organic traffic, branded search demand, same-industry status, and category-month differences.</p>



<p class="wp-block-paragraph"><strong>Entity matching and scope boundaries</strong>



<p class="wp-block-paragraph">Citations are domains, and named brands are text entities. Semrush maps both to a first-party brand entity where possible. The relatedness results, therefore, describe mapped brands, not every raw citation or name in the source data.</p>



<p class="wp-block-paragraph">The design measures associations, not a randomized expansion program. It cannot establish that publishing, brand strategy, or category expansion caused the later outcomes. It also does not produce a reliable maximum number of categories a site can serve.</p>



<p class="wp-block-paragraph"><em>This post first appeared on the author’s website and is republished here with permission.</em>


Should you keep your content strategy focused on a few core topics, or can you go broad to really widen the “funnel”?
In Does topical authority matter in AI Search?, I tested the core topical-authority claim in AEO by examining repeat presence across categories. I found that there is indeed a pattern of “category owners” who sustain their lead over months. 
This memo asks a different question: Once a brand has proven authority in one topic or category, does that authority carry into adjacent or distant categories? And if so, does it still look like an LLM recommendation or only a source in a citation set?
In this memo:
Brands have good chances of getting cited outside their established expertise, but not mentioned. 
A small but robust effect that suggests brands that “own” a category are more successful at expanding into other categories.
The topical authority effect in AI Search does not show up equally across industries.
A category is not won until the brand earns repeat mentions, not just citations.
View embedded content



The data behind the findings
To test the hypothesis, Semrush was kind enough to provide me with a broad sample of AI Visibility Toolkit data across about 1,000 categories. I ran 3 tests:
The relatedness test compares a brand’s new category appearances with categories where it had already appeared in at least 3 of 5 prompts.
The future performance test traces brand mention and citation appearance across 6 months.
The breadth vs depth test compares whether brands that are cited or mentioned in many categories see any detriment in covering content topics in breadth vs depth.
Semrush provided the following U.S. ChatGPT data from the AI Visibility Toolkit: 1,094 categories, 5 prompt variants per category, January through June 2026. 
The breadth tests draw on 283,215 citations and 76,493 named-brand-mention observations, each paired with the following month’s outcome. 
The relatedness test draws on 45,578 expansion appearances by 1,458 mapped brand entities. 
Every number here is an association after controls, so the models cannot prove that publishing or category expansion caused the later result.
Full methodology, measures, models, and scope limits are at the end of this Memo.
1. Topical Authority is different for mentions vs citations
The Topical Authority concept in SEO says that brands cannot or should not try to rank in all sorts of topics, but instead focus on topics that are closest to their core expertise. There are exceptions. But is that also true in AI Search? To find out, I embedded the ~1,000 categories in the study data and matched them against the core expertise of the brands we examined.
The results: Brands have good chances of getting cited outside their established expertise, but not mentioned. In distant categories from their core expertise (based on semantic similarity measurements), 50% appearances are citations and only 25% are mentions. Only 9% get both. 
In close categories that are more topically relevant to a brand, 74% are cited, 44% are named, and 34% get both.




Citation-only presence barely changes across category relevance: 41% in distant categories versus 40% in close ones. 
In other words, you can be a source on pretty much any topic if it matches the regular criteria for source citations. But the AI recommends you in core topics.




2. Topical Authority requires depth
A domain can surface once in 20 categories and own none of them. 
Presence in answers for the topic measures whether the brand appears at all.
Depth in the topic measures how many of the 5 prompt variants the brand appears in.
Category performance measures its share of the citations or brand mentions in the answers.
In Does topical authority matter in AI search?, we saw repeat presence as the early signal of topical authority. This Memo adds a constraint: The authority only carries brand recognition into categories that are close to the brand’s demonstrated expertise.
Once again, I found no detriment when showing up across many categories for citations. The association rises from +0.012 when appearing in 1/5 category prompts to +0.062 when a domain appears in all 5. Being cited in many categories does not show a spread-thin effect in this sample.
Brand mentions tell a different story. Being mentioned in 1/5 category prompts across the categories a brand appears in is associated with a lower mention share at -0.051. 
But at 5/5, it’s slightly positive. In plain words, we can see a small but robust effect that suggests brands that “own” a category are more successful at expanding into other categories. 
Overall, this data shows trying to be everywhere is associated with fewer brand mentions; being in many categories you actually own may help slightly. The “spread too thin” penalty is really a penalty for shallow presence, not for breadth itself.




Keep in mind that there is no defensible universal category limit. The data does not support the claim that a site can serve an unlimited number of categories, either. 
The other thing is that the associations here are very light, and we should be careful not to overvalue the effect on topical authority on overall visibility. Other factors, like writing style, overall brand authority, and third-party web mentions might outweigh topical authority.
A checklist beats a style opinion when 4 writers are shipping against the same standard. The AI Writing Implementation Kit gives your team the audit criteria in writing. Premium subscribers get the kit plus 40+ other tools, checklists, and stakeholder decks.
3. Not all industries show Topical Authority equally
The topical authority effect in AI Search does not show up equally across industries.
Finance and real estate show the strongest repeat-citation pattern:
In finance, the citation-breadth association rises from +0.054 at 1 prompt variant to +0.139 at all 5.
Real estate rises from +0.021 to +0.135.
In those industries, broader repeated coverage is associated with stronger source visibility. That makes category expansion a viable citation strategy. That does not mean every finance or real estate brand can win every adjacent category. 
It means we don’t see an obvious “spread too thin” penalty for sources in these markets. When a domain appears repeatedly across a category’s prompt variants, it tends to hold more citation shares in the following month.
Legal and healthcare place a tighter constraint on brand mentions:
In legal, the mention-breadth association remains negative even at full 5-prompt coverage, -0.058.
Healthcare follows the same pattern at -0.037.
More consistent coverage can improve a domain’s citation position, but it does not reliably translate into more named-brand visibility. A likely explanation is that these topics involve higher-stakes choices, where being a credible source is not enough to make a brand the recommended answer.




Positive means wider breadth is associated with higher next-month share after controls; negative means lower share.



The practical implication is simple: Finance and real-estate teams can test expansion into related categories with citations as an early success metric. Legal and healthcare teams should use a higher bar. A category is not won until the brand earns repeat mentions, not just citations.
Methodology
Sample



The study uses Semrush’s U.S. ChatGPT dataset from the AI Visibility Toolkit from January through June 2026:
It includes 1,094 categories and 5 prompt variants per category in every monthly snapshot.
The breadth models use 283,215 citations and 76,493 named-brand-mention domain-category observations from January through May. Each current-month observation has a next-month outcome. A domain that disappears from the category receives a share of zero.
The relatedness analysis uses 45,578 expansion appearances by 1,458 mapped brand entities across all 1,094 categories. It has February through May, starting snapshots because each appearance needs prior history and a following-month outcome.
Measures



Citation share is a domain’s share of all source citations in a category’s answers. Brand-mention share is its share of all named brand mentions. The study does not combine them because ChatGPT produces more citations than named brand mentions.
Depth measures the number of a category’s 5 prompt variants where a domain appears. Breadth measures the number of categories where it appears in the current month. The sensitivity test defines a breadth category using 1one through 5five prompt appearances.
For the relatedness analysis, demonstrated expertise means appearing in at least 3three prompt variants in a category before the target-month appearance. An expansion appearance is a brand showing up in a target category where it had not previously reached that depth. Category relationship comes from multilingual semantic similarity between the target category’s title and prompts and the brand’s prior expert categories.
Models and controls



The breadth models estimate the relationship between current breadth and next-month citation or mention share within the same category. They control for current share, current depth, the other signal’s share, Authority Score, organic traffic, branded search demand, and category-month differences.
The relatedness model compares close and distant expansion appearances while controlling for current citation and mention depth, current citation and mention share, breadth, Authority Score, organic traffic, branded search demand, same-industry status, and category-month differences.
Entity matching and scope boundaries



Citations are domains, and named brands are text entities. Semrush maps both to a first-party brand entity where possible. The relatedness results, therefore, describe mapped brands, not every raw citation or name in the source data.
The design measures associations, not a randomized expansion program. It cannot establish that publishing, brand strategy, or category expansion caused the later outcomes. It also does not produce a reliable maximum number of categories a site can serve.
This post first appeared on the author’s website and is republished here with permission.

New research reveals why AI cites brands across many topics but recommends them only where they've built repeat topical authority.

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<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/08/10-SEO-use-cases-for-auditing-your-accessibility-tree-for-AI-search.png" class="attachment-large size-large wp-post-image" alt="10 SEO use cases for auditing your accessibility tree for AI search" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/10-SEO-use-cases-for-auditing-your-accessibility-tree-for-AI-search.png 1920w, https://searchengineland.com/wp-content/seloads/2026/08/10-SEO-use-cases-for-auditing-your-accessibility-tree-for-AI-search-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/10-SEO-use-cases-for-auditing-your-accessibility-tree-for-AI-search-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/10-SEO-use-cases-for-auditing-your-accessibility-tree-for-AI-search-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Go beyond HTML with practical workflows to uncover rendering issues, weak site structure, and other obstacles to AI understanding.

Have you ever checked what your website looks like to something that can’t see it?
AI agents don’t admire your hero image or your brand colors. They read the accessibility tree.
The accessibility tree is the structured, semantic layer your browser builds from the DOM, the same layer screen readers have used for decades.
OpenAI’s Publishers and Developers FAQ confirms that ChatGPT Atlas interprets page structure and interactive elements through ARIA roles and labels, and that making your site more accessible makes it easier for the agent to understand. 
Microsoft’s Playwright MCP, one of the most widely adopted frameworks for agent browsing, is built around accessibility snapshots instead of screenshots for the same reason.
The only reason SEOs are suddenly discussing the accessibility tree in 2026 is that AI agents now read that exact layer, and WebMCP is on track to let those agents act on websites, not just read them.
Here’s how to put your website’s accessibility tree to work with these 10 SEO use cases.

No.Use casePlugs into

1Agent readiness audit on money pagesTechnical audits
2Diagnose JavaScript rendering gapsRendering audits
3Audit conversion paths for WebMCPCRO and agent commerce prep
4Benchmark competitor machine legibilityCompetitive analysis
5Validate heading and landmark hierarchyContent structure
6Fix anchor text through accessible namesInternal linking
7Audit images and alt text for AI extractionContent extraction and AI citations
8ARIA snapshots in CIMonitoring and regression testing
9Before/after tree diffs for migrationsMigration QA
10Prioritize accessibility fixes by SEO valueRoadmapping






Don’t skip: Read this accessibility warning first
Before you touch a single ARIA attribute for SEO reasons, remember what this layer is actually for.
The accessibility tree exists so people with disabilities can use the web. Everything in the W3C’s Web Content Accessibility Guidelines, including the WCAG 3.0 draft that restructures conformance around outcomes rather than checkpoints, was written for people using assistive technology.
That means the stakes of getting it wrong are higher than a lost citation. Sloppy ARIA doesn’t just confuse an agent. It actively misleads a screen reader user who has no way to know they’re being misled.
It can also get you sued. Some law firms run automated accessibility audits at scale to identify potential lawsuit targets. More than 8,600 accessibility lawsuits were filed in 2025 alone.
Professionals specifically qualified for this work, called certified accessibility specialists, can help. If your site serves a large audience or operates in a regulated industry, bring one in.
Treat SEO benefits as a side effect of doing accessibility correctly, never the other way around.
Now that we’ve covered the important part, let’s get to the workflows.
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Two ways to view your accessibility tree
Every use case below starts with the same step: Look at the tree. You have one easy method and another that’s almost as easy, with a few more steps.
The easiest method
I built a free tool called the AXray Extractor that captures the full accessibility tree of any live URL using a real headless browser. Paste in a URL, capture the tree, filter to the nodes that matter, and copy or download the entire tree as JSON.
No DevTools knowledge or account is required, and the JSON export makes several of the workflows below much faster.




The easy method with a few more steps
Chrome DevTools has a full-page accessibility tree view. To start:
Open DevTools.
Go to the Elements panel (usually open by default).
Open the Accessibility pane in the right sidebar (or, in some layouts, the bottom pane).
Enable Full-page accessibility tree.
The DOM view switches to the accessibility tree, where you can inspect each node’s role, name, and state.




TL;DR




Use the extractor when you want speed or a shareable export.
Use DevTools when you need to trace a specific broken node back to the exact markup causing it.
SEO use cases for auditing accessibility trees
1. Run an agent readiness audit on your money pages
This is the foundational workflow. Everything else builds on it.
The workflow




Pull your top 10 to 20 pages by revenue or conversions from analytics.
Capture the accessibility tree for each one (extractor or DevTools).
For every page, answer these questions:

What are the most important user actions on this page?
Does every important action appear as a node with the correct role and a clear accessible name?
Score each page against this pass/fail checklist:

Primary CTA exposed as a button or link with a descriptive name.
Every form input has a programmatically associated label.
Navigation wrapped in a navigation landmark.
Main content wrapped in a main landmark.
Key content, including pricing, product details, and contact info, present in the tree as readable text.
Log the results in a sheet, one row per page, one column per check.
What good looks like: Every interactive element on the page has a role that isn’t generic and a name a stranger could act on without seeing the screen.
What to fix when it fails: Unnamed or generic nodes almost always trace back to div-based controls, icon-only buttons without labels, or inputs missing labels. Fix with native HTML first, a real <button>, a real <label>, and reach for ARIA only when native elements can’t do the job.
2. Diagnose JavaScript rendering gaps
You already audit JavaScript rendering. The tree gives that audit a new inspection surface:
Old method: “Did the content render?”
New method: “Did the content reach the layer agents actually read, and when?”
The workflow




Go to the AXray Extractor.
Select Capture JS Diff.
Scroll down to view the differences.
What good looks like: Your core content, headings, and primary links exist in both captures. Enhancement can hydrate late. Substance can’t.
What to fix when it fails: Content that never reaches the tree without client-side JavaScript is invisible to any agent that doesn’t fully execute your scripts, and it’s exactly the content most at risk with traditional crawlers, too. 
Run this on a typical client-side rendered ecommerce category page, and the usual finding is that the product grid, the filters, and sometimes the H1 all live exclusively in the post-hydration tree. Server-side render or pre-render anything that fits that description.




3. Audit conversion paths for WebMCP
Agents are moving from reading websites to transacting on them. WebMCP, the W3C draft standard co-authored by Google and Microsoft engineers and now in a Chrome origin trial, lets a website expose its functions directly to agents. 
But as of this writing, most sites won’t have WebMCP tooling for a while, which means we have time to prepare our websites for the future.
The workflow




Pick one revenue flow, such as checkout, lead form, or signup.
Walk it step by step in the tree view, one screen at a time.
At each step, flag four failure types: unnamed buttons, div-based click handlers, unlabeled inputs, and state that never updates (an accordion that expanded never flips, a submit button that disabled never releases).
File each flag as a ticket with the exact node and the markup fix.
Here’s the classic before and after:


<div class="btn btn-primary" onclick="submitOrder()">Complete purchase</div>

<button class="btn btn-primary" type="submit">Complete purchase</button>





Same pixels for the human. Night and day for the machine.
What good looks like: An agent could complete the entire flow using only roles, names, and states, with zero guessing.
What to fix when it fails: Replace div handlers with native buttons and links, associate every input with a <label>, and make sure JS actually updates ARIA states when the UI changes. An aria-expanded="false" that stays false while the panel visibly opens is worse than no attribute at all, because it confidently lies.
4. Benchmark your competitors’ machine legibility
If agents mediate a growing share of discovery and purchase decisions, machine legibility is a competitive metric rather than a compliance metric. Unlike backlinks, your competitors’ accessibility trees are right there in public.
The workflow




Pick your most important template (product page, service page, or pricing page) and the equivalent URL on three to five competitors.
Capture each tree. Playwright makes this scriptable with a one-liner per page: await page.ariaSnapshot() returns a YAML representation of the entire tree (see the ARIA snapshots documentation). The AXray Extractor works well for a handful of URLs.
For each capture, count four things:
Total meaningful nodes.
Named versus unnamed interactive nodes.
Landmarks present.
Headings exposed with the correct levels.
Build a scorecard, one row per site.
What good looks like: A simple table you can put in front of a stakeholder.

SiteInteractive nodesNamedUnnamedLandmarksHeadings exposed

You4231113 of 514
Competitor A383805 of 518
Competitor B5122291 of 59






What to fix when it fails: If a competitor’s tree is dramatically cleaner than yours, its pages are cheaper and more reliable for agents to parse. 
Remember, there’s no “right number” of interactive nodes, and more doesn’t equal better. This is simply a spot check.
5. Validate heading and landmark hierarchy as agents receive it
Heading audits usually happen in a crawler export, which reports what’s in the HTML. The tree reports what’s actually consumed. Those two things disagree more often than you’d hope.
The workflow




Capture the tree for your key content templates.
Extract every heading node and check the levels in sequence. Look for skips (H1 to H3), duplicates (two H1s), and reversals.
Check for “visual headings”: text styled to look like a heading but exposed to the tree as plain text because it’s a styled div.
Check for the inverse: aria-level overrides or role=”heading” on random elements that scramble the real order.
Confirm every meaningful content block sits inside a landmark (main, navigation, complementary). Content floating outside any landmark loses its context for extraction.
What good looks like: One H1, sequential heading levels beneath it, and every heading in the tree matching a heading a person would identify by looking at the page.
What to fix when it fails: Restyle real heading elements rather than promoting styled divs with ARIA, and remove aria-level overrides unless there’s a genuine accessibility reason for them. 
Agents use your heading hierarchy to segment and extract content. A scrambled hierarchy turns your carefully structured article into an undifferentiated blob.
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6. Fix anchor text through accessible names
Internal linking audits usually mean crawling anchor text. The tree does something a crawler can’t: It shows every link’s accessible name, which is what agents and screen readers actually receive, in one view.
Three problems become instantly visible:
Generic names: “Read more,” “Click here,” “Learn more,” repeated 40 times per page
Empty names: Icon-only links (social icons, arrow buttons, logo links) with no name at all
Silent overrides: An aria-label that replaces perfectly good visible anchor text with something worse
That last one is the sneaky one. If your visible anchor says “Compare enterprise pricing plans,” but someone slapped aria-label="Link" on it, the tree says “Link.” The agent reads “Link.” Your carefully written anchor text may as well not exist.
The workflow




Capture an ARIA snapshot of the page (Playwright’s ariaSnapshot() or the extractor’s JSON).
Extract all nodes with the link role.
Sort by accessible name.
Fix in priority order: empty names first, then generic names, then overrides.
What good looks like: Every link name describes its destination well enough that someone reading only the list of names could navigate your site.
What to fix when it fails: Give icon links an aria-label that describes the destination, rewrite generic anchors to be descriptive, and delete ARIA labels that override good visible text. Your internal linking strategy only works if those names survive the trip into the tree.
7. Audit images and alt text for AI extraction
Filter your tree capture to nodes with the image role, and you’ll get an instant inventory of what your images contribute to machine understanding. Usually, the answer is “less than you think.”
The workflow




Capture the tree for your top image-heavy templates.
Filter to image nodes and review each name (the exposed alt text).
Flag three failure types: missing names (empty alt on meaningful images), noise (decorative images exposed to the tree instead of hidden with empty alt), and useless names (“image,” “chart,” “photo123”).
Rewrite against best practices.
The goal here isn’t compliance. It’s extraction and citation. An image with no accessible name contributes nothing when an AI system decides whether your page answers a question.
To optimize images for AI search: 
Compose images as single logical blocks without visual noise.
Keep text in images legible instead of crushing it with compression.
Place images next to their supporting text inside semantic markup, such as <figure> and <figcaption>.
Write alt text that includes spatial context (what’s left, right, foreground, and background).
Put explicit labels directly on data visualizations instead of relying on legends.
What good looks like: Every meaningful image has a name that could stand in for the image, and every decorative image is absent from the tree entirely.
What to fix when it fails: Use empty alt text (alt="") on decorative images to remove noise, and descriptive, spatially aware alt text on everything that conveys information.
8. Put ARIA snapshots in continuous integration (CI) to catch regressions before deployment
This is my favorite workflow because it’s the only one on this list that works while you sleep.
Everything above is a point-in-time audit. The problem with point-in-time audits is that the next deployment can quietly undo them. A refactor swaps a button component, an accessible name disappears, and nobody notices until an agent, or a screen reader user, hits the wall.
Playwright’s toMatchAriaSnapshot assertion turns your accessibility tree into a versioned test baseline. Here’s how it works:
Capture a YAML snapshot of a template’s tree and commit it to the repository.
During every build, Playwright recaptures the tree and compares it against the baseline.
If a deployment strips a name, drops a landmark, or demotes a heading, the build fails before it ships.
The implementation is about 15 lines:

import { test, expect } from '@playwright/test';
const templates = [
  { name: 'homepage', url: '/' },
  { name: 'product', url: '/products/example' },
  { name: 'checkout', url: '/checkout' },
];
for (const t of templates) {
  test(`accessibility tree: ${t.name}`, async ({ page }) => {
    await page.goto(t.url);
    await expect(page.locator('body')).toMatchAriaSnapshot({
      name: `${t.name}.aria.yml`,
    });
  });
}





Run npx playwright test --update-snapshots once to generate the baselines, commit the .aria.yml files, and you’re monitoring. 
When a legitimate redesign changes the structure, rerun with the update flag and review the YAML diff in the pull request. That diff is human-readable. A reviewer sees - button "Submit" become – button "" and knows exactly what broke.
What good looks like: Structural regressions fail CI rather than surfacing during a quarterly audit three months after the damage started.
What to fix when it fails: Whatever the diff says. That’s the whole point.
9. QA migrations and redesigns with before-and-after tree diffs
Migration checklists cover redirects, metadata, canonical tags, and internal links. I’ve never seen one that covers the accessibility tree, which is a problem because a redesign can preserve every URL and title tag while silently destroying the structure agents read.
Picture the standard scenario: A site replatforms to a new JavaScript framework. Every redirect resolves, every meta tag survives, and the migration is declared a success. Meanwhile, the new component library ships every CTA as a div, the landmark structure evaporates, and the tree goes from a clean hierarchy to generic soup.
Nothing in a traditional migration QA checklist would catch it.
The workflow




Capture ARIA snapshots of your top 10-20 templates before the migration and store them in a safe place. (If you’ve already completed use case 8, this step is done.)
After launch, capture the same templates on the new site.
Diff each pair.
Triage the results: Missing landmarks and unnamed interactive elements are launch blockers. Renamed nodes and reordered sections are review items.
What good looks like: The post-migration tree preserves every landmark, every named control, and the heading hierarchy of the old site, or deliberately improves on them.
What to fix when it fails: Work through the diff exactly as you would a redirect audit, starting with the highest-traffic templates. Then add “tree diff” as a standing line item in your migration checklist so you never have to do this reactively again.
10. Prioritize accessibility fixes by SEO value
Most accessibility backlogs are sorted by WCAG severity, which is correct for compliance but useless for getting the work resourced. Nobody funds “347 contrast errors.” People fund revenue.
The workflow




Take your tree failures from use cases 1 through 9 and group them by template.
Pull three data points for each template:

GSC clicks.
Conversion value.
AI citation presence (whatever visibility tracking you use for LLM mentions).
Cross-reference the data. A missing accessible name on your pricing page CTA outranks 50 issues on your 2019 blog archive.
Resort the backlog based on that combined value, and hand your development team a top-10 list instead of a 400-row export.
What good looks like: Accessibility work framed as revenue protection, with the highest-value templates fixed first, while maintaining the WCAG severity view in parallel for compliance (because the legal risk from the warning section hasn’t gone away).
What to fix when it fails: This is less about fixing markup and more about fixing prioritization. It’s also what turns the previous nine workflows from isolated tactics into an operating model your team can actually run.
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Where to start
Don’t try to run all 10 workflows this week. Start with use case 1 on your top 10 pages. It surfaces the most damage per hour invested. Then implement use case 8 so the gains you make can’t silently regress. Fold use cases 2, 3, and 9 into the audit and migration checklists you already use, and let the rest enter the rotation as the need arises.
Agents account for a growing share of the traffic hitting your site, and they’re only becoming more capable of acting on what they read. The sites that win that traffic will be the ones that are most legible to them. Now you know how to measure that.
Good luck, and happy auditing.

Go beyond HTML with practical workflows to uncover rendering issues, weak site structure, and other obstacles to AI understanding.

10 SEO use cases for auditing your accessibility tree for AI search

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/Google-tightens-Ads-policy-for-government-document.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Google-tightens-Ads-policy-for-government-document.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/Google-tightens-Ads-policy-for-government-document-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Google-tightens-Ads-policy-for-government-document-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Google-tightens-Ads-policy-for-government-document-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>Advertisers now need to prove explicit government authorisation before promoting government documents through Google Ads.

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/Google-tightens-Ads-policy-for-government-document.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Google-tightens-Ads-policy-for-government-document.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/Google-tightens-Ads-policy-for-government-document-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Google-tightens-Ads-policy-for-government-document-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Google-tightens-Ads-policy-for-government-document-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>
<p class="wp-block-paragraph">Google is tightening its Government documents and services policy, introducing stricter requirements for advertisers that promote government-issued documents and administrative services.</p>



<p class="wp-block-paragraph">The changes, which take effect on October 5th, are designed to ensure only explicitly authorised providers can advertise these services through Google Ads.</p>



<p class="wp-block-paragraph"><strong>What&#8217;s changing</strong>. Under the updated policy, advertisers will need to demonstrate that they have explicit government authorisation to provide the specific document or service they advertise.</p>



<p class="wp-block-paragraph">To qualify, a provider&#8217;s domain must be linked from an official government website and clearly identified as an authorised provider for that document or service. Government-managed directories of approved partners and official regulatory portals will qualify, while business licences, commercial contracts, company registrations and government-hosted blog posts will not.</p>



<p class="wp-block-paragraph">Google will also require authorised providers to advertise only the services covered by their authorisation and restrict ad targeting to the relevant geographic regions, except for inherently cross-border services such as electronic travel authorisations, border entry documents and U.S. Trusted Traveler programs.</p>



<p class="wp-block-paragraph"><strong>Why we care</strong>. Advertisers operating in government services, visa assistance and administrative support may need to review their eligibility before the policy takes effect. Businesses that cannot demonstrate the required government authorisation could lose the ability to advertise these services on Google Ads.</p>



<p class="wp-block-paragraph"><strong>The bigger picture</strong>. The update reflects Google&#8217;s continued effort to reduce misleading advertising in sensitive categories. By raising the certification threshold, Google is placing greater emphasis on official government recognition rather than general business credentials or commercial relationships.</p>



<p class="wp-block-paragraph"><strong>Bottom line</strong>. <a href="https://support.google.com/adspolicy/answer/17260489?hl=en">Beginning October 5, Google will require stronger proof of government authorisation</a> for advertisers promoting government documents and services, limiting eligibility to providers that are explicitly recognised by the relevant government authority.</p>


Google is tightening its Government documents and services policy, introducing stricter requirements for advertisers that promote government-issued documents and administrative services.
The changes, which take effect on October 5th, are designed to ensure only explicitly authorised providers can advertise these services through Google Ads.
What’s changing. Under the updated policy, advertisers will need to demonstrate that they have explicit government authorisation to provide the specific document or service they advertise.
To qualify, a provider’s domain must be linked from an official government website and clearly identified as an authorised provider for that document or service. Government-managed directories of approved partners and official regulatory portals will qualify, while business licences, commercial contracts, company registrations and government-hosted blog posts will not.
Google will also require authorised providers to advertise only the services covered by their authorisation and restrict ad targeting to the relevant geographic regions, except for inherently cross-border services such as electronic travel authorisations, border entry documents and U.S. Trusted Traveler programs.
Why we care. Advertisers operating in government services, visa assistance and administrative support may need to review their eligibility before the policy takes effect. Businesses that cannot demonstrate the required government authorisation could lose the ability to advertise these services on Google Ads.
The bigger picture. The update reflects Google’s continued effort to reduce misleading advertising in sensitive categories. By raising the certification threshold, Google is placing greater emphasis on official government recognition rather than general business credentials or commercial relationships.
Bottom line. Beginning October 5, Google will require stronger proof of government authorisation for advertisers promoting government documents and services, limiting eligibility to providers that are explicitly recognised by the relevant government authority.

Advertisers now need to prove explicit government authorisation before promoting government documents through Google Ads.

Google tightens Ads policy for government document providers

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/08/What-happens-when-AI-Overviews-contradict-paid-search-ads.png" class="attachment-large size-large wp-post-image" alt="What happens when AI Overviews contradict paid search ads?" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/What-happens-when-AI-Overviews-contradict-paid-search-ads.png 1920w, https://searchengineland.com/wp-content/seloads/2026/08/What-happens-when-AI-Overviews-contradict-paid-search-ads-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/What-happens-when-AI-Overviews-contradict-paid-search-ads-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/What-happens-when-AI-Overviews-contradict-paid-search-ads-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>AI recommendations can steer users toward competitors, leaving advertisers to absorb the impact on CTR, CPC, and campaign performance.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/08/What-happens-when-AI-Overviews-contradict-paid-search-ads.png" class="attachment-large size-large wp-post-image" alt="What happens when AI Overviews contradict paid search ads?" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/What-happens-when-AI-Overviews-contradict-paid-search-ads.png 1920w, https://searchengineland.com/wp-content/seloads/2026/08/What-happens-when-AI-Overviews-contradict-paid-search-ads-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/What-happens-when-AI-Overviews-contradict-paid-search-ads-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/What-happens-when-AI-Overviews-contradict-paid-search-ads-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p class="wp-block-paragraph">For months, the search industry across <a href="https://searchengineland.com/guide/what-is-seo">SEO</a> and <a href="https://searchengineland.com/guide/what-is-paid-search">PPC</a> has been bracing for the ultimate SERP fusion: an all-in-one AI panel where your sponsored ad, your organic citation, and your Merchant Center product card appear in a single, pixel-efficient layout.</p>



<p class="wp-block-paragraph">I set out to find screenshots of it for this article. I didn&#8217;t find any. Instead, I found a different threat to paid search strategies: an AI Overview confident enough to directly contradict the paid ad sitting immediately above it on the same page, in real time.</p>



<p class="wp-block-paragraph">So while we&#8217;ve all been focused on a layout challenge, what I found points to another issue: trust and attribution.</p>



<h2 id="h-how-ai-overviews-replace-comparison-with-conclusions" class="wp-block-heading">How AI Overviews replace comparison with conclusions</h2>



<p class="wp-block-paragraph">I started with a classic transactional query: &#8220;What is the best plumber for a broken pipe?&#8221;</p>



<p class="wp-block-paragraph">At the top of the SERP sat a textbook, high-converting sponsored ad from Eco Plumbers featuring an $89 leak detection promo, 24/7 availability, 4.9 stars across 20,000+ reviews, a video carousel, and location extensions. It contained every conversion signal an advertiser could pay to deploy.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1049" height="638" src="https://searchengineland.com/wp-content/seloads/2026/08/image-13.png" alt="" class="wp-image-484324" srcset="https://searchengineland.com/wp-content/seloads/2026/08/image-13.png 1049w, https://searchengineland.com/wp-content/seloads/2026/08/image-13-768x467.png 768w" sizes="(max-width: 1049px) 100vw, 1049px" /><figcaption class="wp-element-caption"><em><em>Sponsored ad from Google search</em></em></figcaption></figure>
</div>


<p class="wp-block-paragraph">Directly below it sat an AI Overview with zero hedging:</p>



<ul class="wp-block-list">
<li><em>&#8220;The best plumber for a broken pipe is a local 24/7 emergency plumbing company like Roto-Rooter Plumbing &amp; Water Cleanup or Amanda Plumbing.&#8221;</em></li>
</ul>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1339" height="643" src="https://searchengineland.com/wp-content/seloads/2026/08/image-14.png" alt="" class="wp-image-484325" srcset="https://searchengineland.com/wp-content/seloads/2026/08/image-14.png 1339w, https://searchengineland.com/wp-content/seloads/2026/08/image-14-768x369.png 768w" sizes="(max-width: 1339px) 100vw, 1339px" /><figcaption class="wp-element-caption"><em><em>AI Overview from Google Search</em></em></figcaption></figure>
</div>


<p class="wp-block-paragraph">Google served two definitive verdicts on the same page for the same query, and they openly contradicted each other. The advertiser paying premium CPCs for the top position wasn&#8217;t even mentioned in the AI Overview&#8217;s response.</p>


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<h2 id="h-ai-overviews-shift-user-psychology-from-options-to-verdicts" class="wp-block-heading">AI Overviews shift user psychology from options to verdicts</h2>



<p class="wp-block-paragraph">For two decades, organic search was a candidate pool, or what we like to call a list of blue links. Searchers scanned 10 blue links, evaluated meta descriptions, weighed brand familiarity, and calculated their own trust.</p>



<p class="wp-block-paragraph">Ads sat above or alongside those links with clear &#8220;Sponsored&#8221; labels. Users maintained a healthy baseline of skepticism, treating both paid and organic links as raw material for a decision they still had to make.</p>



<p class="wp-block-paragraph">AI Overviews eliminate that evaluation phase through their phrasing. An AI Overview doesn&#8217;t offer candidates. It issues a conclusion. It doesn&#8217;t say, &#8220;Here are options to consider.&#8221; It states, &#8220;The best plumber for a broken pipe is&#8230;&#8221;</p>



<p class="wp-block-paragraph">This declarative, single-answer format is delivered with the same authority whether the underlying data is exhaustive or thin. Searcher psychology has fundamentally shifted. Users are far more likely to accept a fluent, synthesis-driven answer than to manually compare 10 disparate URLs.</p>



<p class="wp-block-paragraph">The AI Overview isn&#8217;t just competing with your ad for a click. It&#8217;s replacing the user&#8217;s internal decision-making process with an algorithmic verdict that your ad team had zero say in.</p>



<h2 id="h-query-variations-trigger-volatile-citations-across-ecommerce-brands" class="wp-block-heading">Query variations trigger volatile citations across ecommerce brands</h2>



<p class="wp-block-paragraph">To test this behavior across ecommerce, I ran several variations of &#8220;sweatshirts for anxiety.&#8221;</p>



<p class="wp-block-paragraph">On the standard SERP, a Shopping carousel displayed six products from brands like Cloud Nine and Comfrt ($39 to $89.95), immediately followed by a text ad for Cloud Nine&#8217;s &#8220;Ultimate Calming Hoodie&#8221; featuring a &#8220;100K+ visits last month&#8221; social proof snippet. Cloud Nine dominated the paid real estate across two distinct formats.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1509" height="956" src="https://searchengineland.com/wp-content/seloads/2026/08/image-17.png" alt="" class="wp-image-484328" srcset="https://searchengineland.com/wp-content/seloads/2026/08/image-17.png 1509w, https://searchengineland.com/wp-content/seloads/2026/08/image-17-768x487.png 768w" sizes="(max-width: 1509px) 100vw, 1509px" /><figcaption class="wp-element-caption"><em><em>Google search for sweatshirts for anxiety</em></em></figcaption></figure>
</div>


<p class="wp-block-paragraph">When I prompted the AI Overview directly on which sweatshirts were best for anxiety, it recommended weighted and sensory hoodies, highlighting Comfrt ($75), Thera ($158), and Cozy Ghost ($118). Comfrt earned both a paid slot and an organic AI citation, but Thera and Cozy Ghost appeared in the AI Overview despite having no paid presence.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1174" height="451" src="https://searchengineland.com/wp-content/seloads/2026/08/image-15.png" alt="" class="wp-image-484327" srcset="https://searchengineland.com/wp-content/seloads/2026/08/image-15.png 1174w, https://searchengineland.com/wp-content/seloads/2026/08/image-15-768x295.png 768w" sizes="(max-width: 1174px) 100vw, 1174px" /><figcaption class="wp-element-caption"><em><em>AI Overview for sweatshirts for anxiety</em></em></figcaption></figure>
</div>


<p class="wp-block-paragraph">Cloud Nine, the brand spending aggressively to capture top-of-page paid placement, was completely omitted.</p>



<p class="wp-block-paragraph">However, when I adjusted the search query slightly to the informational variant &#8220;what is an anxiety sweatshirt,&#8221; the AI model shifted its logic entirely. Cloud Nine suddenly appeared in the AI Overview alongside Etsy sellers and We&#8217;re Not Really Strangers, reclassified under &#8220;graphic and affirmation apparel&#8221; rather than &#8220;weighted hoodies&#8221;.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="928" height="519" src="https://searchengineland.com/wp-content/seloads/2026/08/image-16.png" alt="" class="wp-image-484326" srcset="https://searchengineland.com/wp-content/seloads/2026/08/image-16.png 928w, https://searchengineland.com/wp-content/seloads/2026/08/image-16-768x430.png 768w" sizes="(max-width: 928px) 100vw, 928px" /><figcaption class="wp-element-caption"><em><em>Modified query example for anxiety sweatshirt</em></em></figcaption></figure>
</div>


<p class="wp-block-paragraph">The same brand appeared in sponsored results, but the AI generated completely different verdicts based on minor semantic shifts.</p>



<p class="wp-block-paragraph">This reveals a critical operational reality: the auction engine and the retrieval-augmented generation (RAG) engine operate on entirely separate logic.</p>



<p class="wp-block-paragraph">Neither your PPC team nor your SEO team fully controls how these systems interact, and that logic can flip based on subtle variations in prompt structure.</p>



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<h2 id="h-where-seo-still-matters-in-an-ai-first-serp" class="wp-block-heading">Where SEO still matters in an AI-first SERP</h2>



<p class="wp-block-paragraph">This doesn&#8217;t mean organic search optimization is dead. It means SEO&#8217;s objective has evolved from ranking in a list to earning a place in the AI verdict.</p>



<p class="wp-block-paragraph">Traditional SEO focused on ranking in the top 10 links, optimizing meta titles, and driving direct click-through rates. Today, success increasingly depends on becoming a source the AI chooses to cite.&nbsp;</p>



<p class="wp-block-paragraph">Generative engine optimization (GEO) shifts that focus toward building strong entity authority and feeding retrieval-augmented generation (RAG) models with structured, extractable content.</p>



<p class="wp-block-paragraph">The examples above illustrate that those citations are still rooted in classic SEO fundamentals:</p>



<ul class="wp-block-list">
<li><strong>Entity clarity and structured data:</strong> Roto-Rooter wasn&#8217;t cited by luck. The AI Overview source panel referenced two distinct Roto-Rooter landing pages optimized with hyperlocal structured data and consistent name, address, and phone (NAP) information.</li>



<li><strong>Granular product specifications: </strong>Ecommerce brands cited by the model (Comfrt, Thera, and Cozy Ghost) featured highly detailed schema and on-page copy specifying exact weight, materials, and functional benefits.</li>



<li><strong>Multi-platform footprint:</strong> Cloud Nine&#8217;s citation for the informational query was backed by indexed TikTok content appearing directly in the AI Overview&#8217;s reference panel.</li>
</ul>



<p class="wp-block-paragraph">Entity authority, structured markup, local consistency, and extractable content still dictate visibility. SEO hasn&#8217;t vanished. The goal has shifted from earning a position on the page to earning a citation in the AI&#8217;s answer.</p>



<h2 id="h-ai-overviews-create-hidden-costs-and-quality-score-risks-for-ppc" class="wp-block-heading">AI Overviews create hidden costs and Quality Score risks for PPC</h2>



<p class="wp-block-paragraph">Consider the downstream impact on paid search accounts when an AI Overview interrupts the funnel:</p>



<ul class="wp-block-list">
<li>You bid aggressively on transactional terms like &#8220;emergency plumber near me.&#8221;</li>



<li>Your ad wins the top auction spot.</li>



<li>Simultaneously, an AI Overview appears below your ad, naming two competitors as the authoritative solution.</li>



<li>Searchers read the AI Overview&#8217;s confident recommendation and convert with the cited brand, never scrolling back up to click your ad.</li>



<li>Google Ads registers an impression without a click, causing your expected CTR relative to ad position to fall.</li>



<li>The system lowers your Quality Score and increases your effective CPC for future auctions.</li>
</ul>



<p class="wp-block-paragraph">You still received the impression, but the click was intercepted by an unmonetized module that sounds certain on the results page.</p>



<p class="wp-block-paragraph">This creates a systemic problem for PPC managers: Your CTR drops relative to its historical position, and Google Ads&#8217; internal diagnostic tools offer no explanation why.</p>



<p class="wp-block-paragraph">The Quality Score algorithm doesn&#8217;t adjust for an AI Overview undermining your ad&#8217;s credibility on the same SERP. It simply registers a drop in expected CTR, penalizes the keyword, and lowers your Quality Score.</p>



<p class="wp-block-paragraph">As a result, your effective CPC rises. You end up paying a premium for diminished traffic on queries where an AI module assigned brand trust to a competitor before your ad had the opportunity to compete.</p>



<h2 id="h-unanswered-questions-demand-a-new-approach-to-search-analytics" class="wp-block-heading">Unanswered questions demand a new approach to search analytics</h2>



<ul class="wp-block-list">
<li>We&#8217;re entering a phase where traditional search playbooks no longer apply as they once did, leaving search marketers with critical diagnostic challenges:</li>



<li><strong>Erosion diagnostics:</strong> If your paid CTR is declining while impression share remains stable, you must audit the AI Overviews triggering on those primary keyword clusters.</li>



<li><strong>Quality Score attribution:</strong> Search teams need to reevaluate Quality Score penalties when the root cause is an algorithmic citation choice made outside the Google Ads ecosystem.</li>



<li><strong>Bidding strategy:</strong> When CPCs rise because of AI-driven CTR suppression, target CPA and ROAS thresholds must be recalculated for impacted campaign types.</li>



<li><strong>Semantic volatility:</strong> As minor syntax changes alter AI citations entirely, teams must map and optimize for prompt variations across high-value intents.</li>
</ul>


<a href="https://www.semrush.com/analytics/traffic/paid-search?utm_campaign=ic_sel_0102ppc&#038;utm_source=searchengineland.com&#038;utm_medium=overlay&#038;onboarding=off" target="_blank">
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        Every click they win is <span>a customer you lose</span>.
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<h2 id="h-the-search-strategist-must-now-bridge-both-channels" class="wp-block-heading">The search strategist must now bridge both channels</h2>



<p class="wp-block-paragraph">Searchers don&#8217;t categorize SERP elements by marketing channel. They digest the most authoritative answer available on the screen and act on it.</p>



<p class="wp-block-paragraph">The historical division between SEO and PPC departments was built for a SERP architecture where labeled ads and organic lists operated in parallel. While those elements remain, the SERP is now dominated by an interface layer that synthesizes information independently of both channel silos.</p>



<p class="wp-block-paragraph">Neither channel team can manage this dynamic in isolation. Diagnosing these performance shifts requires search marketers to analyze paid performance data, AI citation mapping, and entity authority as a single, integrated ecosystem.</p>

For months, the search industry across SEO and PPC has been bracing for the ultimate SERP fusion: an all-in-one AI panel where your sponsored ad, your organic citation, and your Merchant Center product card appear in a single, pixel-efficient layout.
I set out to find screenshots of it for this article. I didn’t find any. Instead, I found a different threat to paid search strategies: an AI Overview confident enough to directly contradict the paid ad sitting immediately above it on the same page, in real time.
So while we’ve all been focused on a layout challenge, what I found points to another issue: trust and attribution.
How AI Overviews replace comparison with conclusions
I started with a classic transactional query: “What is the best plumber for a broken pipe?”
At the top of the SERP sat a textbook, high-converting sponsored ad from Eco Plumbers featuring an $89 leak detection promo, 24/7 availability, 4.9 stars across 20,000+ reviews, a video carousel, and location extensions. It contained every conversion signal an advertiser could pay to deploy.
Sponsored ad from Google search



Directly below it sat an AI Overview with zero hedging:
“The best plumber for a broken pipe is a local 24/7 emergency plumbing company like Roto-Rooter Plumbing & Water Cleanup or Amanda Plumbing.”
AI Overview from Google Search



Google served two definitive verdicts on the same page for the same query, and they openly contradicted each other. The advertiser paying premium CPCs for the top position wasn’t even mentioned in the AI Overview’s response.
your competitors win.
      
Analyze your competitors
    
AI Overviews shift user psychology from options to verdicts
For two decades, organic search was a candidate pool, or what we like to call a list of blue links. Searchers scanned 10 blue links, evaluated meta descriptions, weighed brand familiarity, and calculated their own trust.
Ads sat above or alongside those links with clear “Sponsored” labels. Users maintained a healthy baseline of skepticism, treating both paid and organic links as raw material for a decision they still had to make.
AI Overviews eliminate that evaluation phase through their phrasing. An AI Overview doesn’t offer candidates. It issues a conclusion. It doesn’t say, “Here are options to consider.” It states, “The best plumber for a broken pipe is…”
This declarative, single-answer format is delivered with the same authority whether the underlying data is exhaustive or thin. Searcher psychology has fundamentally shifted. Users are far more likely to accept a fluent, synthesis-driven answer than to manually compare 10 disparate URLs.
The AI Overview isn’t just competing with your ad for a click. It’s replacing the user’s internal decision-making process with an algorithmic verdict that your ad team had zero say in.
Query variations trigger volatile citations across ecommerce brands
To test this behavior across ecommerce, I ran several variations of “sweatshirts for anxiety.”
On the standard SERP, a Shopping carousel displayed six products from brands like Cloud Nine and Comfrt ($39 to $89.95), immediately followed by a text ad for Cloud Nine’s “Ultimate Calming Hoodie” featuring a “100K+ visits last month” social proof snippet. Cloud Nine dominated the paid real estate across two distinct formats.
Google search for sweatshirts for anxiety



When I prompted the AI Overview directly on which sweatshirts were best for anxiety, it recommended weighted and sensory hoodies, highlighting Comfrt ($75), Thera ($158), and Cozy Ghost ($118). Comfrt earned both a paid slot and an organic AI citation, but Thera and Cozy Ghost appeared in the AI Overview despite having no paid presence.
AI Overview for sweatshirts for anxiety



Cloud Nine, the brand spending aggressively to capture top-of-page paid placement, was completely omitted.
However, when I adjusted the search query slightly to the informational variant “what is an anxiety sweatshirt,” the AI model shifted its logic entirely. Cloud Nine suddenly appeared in the AI Overview alongside Etsy sellers and We’re Not Really Strangers, reclassified under “graphic and affirmation apparel” rather than “weighted hoodies”.
Modified query example for anxiety sweatshirt



The same brand appeared in sponsored results, but the AI generated completely different verdicts based on minor semantic shifts.
This reveals a critical operational reality: the auction engine and the retrieval-augmented generation (RAG) engine operate on entirely separate logic.
Neither your PPC team nor your SEO team fully controls how these systems interact, and that logic can flip based on subtle variations in prompt structure.
Get the newsletter search marketers rely on.
 
				
				
			
See terms.
		
Where SEO still matters in an AI-first SERP
This doesn’t mean organic search optimization is dead. It means SEO’s objective has evolved from ranking in a list to earning a place in the AI verdict.
Traditional SEO focused on ranking in the top 10 links, optimizing meta titles, and driving direct click-through rates. Today, success increasingly depends on becoming a source the AI chooses to cite. 
Generative engine optimization (GEO) shifts that focus toward building strong entity authority and feeding retrieval-augmented generation (RAG) models with structured, extractable content.
The examples above illustrate that those citations are still rooted in classic SEO fundamentals:
Entity clarity and structured data: Roto-Rooter wasn’t cited by luck. The AI Overview source panel referenced two distinct Roto-Rooter landing pages optimized with hyperlocal structured data and consistent name, address, and phone (NAP) information.
Granular product specifications: Ecommerce brands cited by the model (Comfrt, Thera, and Cozy Ghost) featured highly detailed schema and on-page copy specifying exact weight, materials, and functional benefits.
Multi-platform footprint: Cloud Nine’s citation for the informational query was backed by indexed TikTok content appearing directly in the AI Overview’s reference panel.
Entity authority, structured markup, local consistency, and extractable content still dictate visibility. SEO hasn’t vanished. The goal has shifted from earning a position on the page to earning a citation in the AI’s answer.
AI Overviews create hidden costs and Quality Score risks for PPC
Consider the downstream impact on paid search accounts when an AI Overview interrupts the funnel:
You bid aggressively on transactional terms like “emergency plumber near me.”
Your ad wins the top auction spot.
Simultaneously, an AI Overview appears below your ad, naming two competitors as the authoritative solution.
Searchers read the AI Overview’s confident recommendation and convert with the cited brand, never scrolling back up to click your ad.
Google Ads registers an impression without a click, causing your expected CTR relative to ad position to fall.
The system lowers your Quality Score and increases your effective CPC for future auctions.
You still received the impression, but the click was intercepted by an unmonetized module that sounds certain on the results page.
This creates a systemic problem for PPC managers: Your CTR drops relative to its historical position, and Google Ads’ internal diagnostic tools offer no explanation why.
The Quality Score algorithm doesn’t adjust for an AI Overview undermining your ad’s credibility on the same SERP. It simply registers a drop in expected CTR, penalizes the keyword, and lowers your Quality Score.
As a result, your effective CPC rises. You end up paying a premium for diminished traffic on queries where an AI module assigned brand trust to a competitor before your ad had the opportunity to compete.
Unanswered questions demand a new approach to search analytics
We’re entering a phase where traditional search playbooks no longer apply as they once did, leaving search marketers with critical diagnostic challenges:
Erosion diagnostics: If your paid CTR is declining while impression share remains stable, you must audit the AI Overviews triggering on those primary keyword clusters.
Quality Score attribution: Search teams need to reevaluate Quality Score penalties when the root cause is an algorithmic citation choice made outside the Google Ads ecosystem.
Bidding strategy: When CPCs rise because of AI-driven CTR suppression, target CPA and ROAS thresholds must be recalculated for impacted campaign types.
Semantic volatility: As minor syntax changes alter AI citations entirely, teams must map and optimize for prompt variations across high-value intents.
a customer you lose.
      
See who’s stealing your traffic
    
The search strategist must now bridge both channels
Searchers don’t categorize SERP elements by marketing channel. They digest the most authoritative answer available on the screen and act on it.
The historical division between SEO and PPC departments was built for a SERP architecture where labeled ads and organic lists operated in parallel. While those elements remain, the SERP is now dominated by an interface layer that synthesizes information independently of both channel silos.
Neither channel team can manage this dynamic in isolation. Diagnosing these performance shifts requires search marketers to analyze paid performance data, AI citation mapping, and entity authority as a single, integrated ecosystem.

AI recommendations can steer users toward competitors, leaving advertisers to absorb the impact on CTR, CPC, and campaign performance.

What happens when AI Overviews contradict paid search ads?

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/08/Why-paid-search-could-be-your-AI-search-advantage.png" class="attachment-large size-large wp-post-image" alt="Why paid search could be your AI search advantage" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Why-paid-search-could-be-your-AI-search-advantage.png 1920w, https://searchengineland.com/wp-content/seloads/2026/08/Why-paid-search-could-be-your-AI-search-advantage-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Why-paid-search-could-be-your-AI-search-advantage-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Why-paid-search-could-be-your-AI-search-advantage-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>The search terms, ads, landing pages, and product feeds you've already built can strengthen your visibility across AI search.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/08/Why-paid-search-could-be-your-AI-search-advantage.png" class="attachment-large size-large wp-post-image" alt="Why paid search could be your AI search advantage" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Why-paid-search-could-be-your-AI-search-advantage.png 1920w, https://searchengineland.com/wp-content/seloads/2026/08/Why-paid-search-could-be-your-AI-search-advantage-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Why-paid-search-could-be-your-AI-search-advantage-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Why-paid-search-could-be-your-AI-search-advantage-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p class="wp-block-paragraph">Ask most marketing teams how they plan to stay visible in AI search, and you&#8217;ll most commonly hear: content strategies, <a href="https://searchengineland.com/guide/what-is-seo">SEO</a> audits, and schema projects. What rarely comes up is the paid search account they&#8217;ve been running for years.</p>



<p class="wp-block-paragraph">That&#8217;s a big miss. The things AI search tools reward — clear answers, structured product data, strong landing pages, and messaging that matches how people talk — are things paid search practitioners influence every day. As a result, most businesses already own the raw data for AI visibility. They just don&#8217;t realize it.</p>



<p class="wp-block-paragraph">Here&#8217;s how the assets in your paid search account translate into visibility across AI search tools like ChatGPT, Google&#8217;s AI Overviews and AI Mode, Microsoft Copilot, and Perplexity. Plus, get a five-step framework to put those assets to work now.</p>



<h2 id="h-your-ad-account-already-knows-how-your-customers-search" class="wp-block-heading">Your ad account already knows how your customers search</h2>



<p class="wp-block-paragraph">Most businesses think of their Google Ads account as a place where budget goes in and leads come out. But it&#8217;s also one of the richest sources of data you have about how customers actually search, including how they phrase problems, compare options, and decide what to buy.</p>



<p class="wp-block-paragraph" id="h-how-this-data-accumulates">Here&#8217;s what your ad account already contains:</p>



<ul class="wp-block-list">
<li>Search term data shows the exact language customers use at every stage of their journey, including long, conversational queries that resemble AI prompts.</li>



<li>Ad copy performance data reveals which value propositions, offers, and phrasings earn clicks and conversions.</li>



<li>Conversion data identifies which products, services, and pages actually drive revenue, not just traffic.</li>



<li>Product feed infrastructure, with structured titles, attributes, images, and pricing, is already formatted for machine learning.</li>



<li>Landing pages are built for relevance, clarity, and speed to meet Quality Score and CPC standards.</li>
</ul>



<p class="wp-block-paragraph">Every one of those assets maps to something AI search systems use when deciding which businesses to mention. Teams treating AI visibility as a &#8220;from scratch&#8221; project are ignoring years of paid search learnings. The teams pulling ahead are treating the ad account as the research layer for their AI search strategy.</p>


<a href="https://www.semrush.com/analytics/traffic/paid-search?utm_campaign=ic_sel_0101ppc&#038;utm_source=searchengineland.com&#038;utm_medium=overlay&#038;onboarding=off" target="_blank">
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        Uncover the keywords, ads, landing pages, and strategies driving your competitors&#8217; paid search success—and find your next opportunity to outperform them.
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    </a>




<h2 id="h-search-term-data-conversational-intent" class="wp-block-heading">Search term data: Conversational intent</h2>



<p class="wp-block-paragraph">The biggest behavioral shift AI search introduced is query length. People don&#8217;t type &#8220;crm small business&#8221; into ChatGPT — they type &#8220;what&#8217;s the best CRM for a five-person landscaping company that mostly needs scheduling and invoicing?&#8221;</p>



<p class="wp-block-paragraph">Paid search campaigns have already surfaced these terms. Broad match, Performance Max, and AI Max have been matching ads to long-tail, natural-language searches for years through search terms reporting. Your search terms report is a preview of the questions customers are asking AI tools.</p>



<p class="wp-block-paragraph">Here&#8217;s what this looks like in practice.&nbsp;</p>



<ul class="wp-block-list">
<li>An HVAC client running a Google Ads search campaign exported the last 12 months of search terms and found questions like &#8220;why is my AC running but not cooling the house&#8221; and &#8220;best HVAC company for older homes near me.&#8221; After pulling these conversational searches out, we grouped them by theme. Then we searched the client&#8217;s website using those queries to identify whether there was a clear, quotable answer to each one. Wherever there wasn&#8217;t, we found a gap between what customers were asking and what AI tools could pull from the site.</li>



<li>In another example, when reviewing a plumbing company&#8217;s search terms report, we found dozens of queries like &#8220;how much does it cost to replace a water heater in a condo.&#8221; These searches converted well, but the website said nothing concrete about pricing. Google Ads profited from that gap. ChatGPT will simply cite a competitor that published the answer.</li>
</ul>



<h2 id="h-your-best-ads-already-have-the-right-message" class="wp-block-heading">Your best ads already have the right message</h2>



<p class="wp-block-paragraph">Your ad copy has already been tested with real buyers. Your highest-performing ads already reflect customer intent. That messaging usually doesn&#8217;t surface outside your ad platform. Your website says one thing, while the ads that convert say another. AI tools only see your website — they never see your ads.</p>



<p class="wp-block-paragraph">To fix this, find your best-performing headlines and descriptions, then make sure those same claims and offers appear as plain text on the pages your ads point to. </p>



<p class="wp-block-paragraph">If &#8220;24/7 emergency service — arrival in 90 minutes or less&#8221; is your best-converting headline, that promise should be on the page itself, not just in the ad. Ad copy also happens to be exactly what AI tools like to quote: specific numbers, timeframes, guarantees, and prices — not vague marketing language.</p>



<h2 id="h-product-feeds-power-paid-and-organic-ai-visibility" class="wp-block-heading">Product feeds power paid and organic AI visibility</h2>



<p class="wp-block-paragraph">If you run Shopping campaigns, your product feed is one of your most leveraged assets. The same structured data you built for Google Merchant Center — accurate titles, complete attributes, quality images, current availability, and pricing — is now what AI shopping tools use to decide which products to show.</p>



<p class="wp-block-paragraph">Product feed quality is a primary eligibility signal for whether Shopping and Performance Max ads appear in AI Overviews and AI Mode. On OpenAI&#8217;s side, ChatGPT&#8217;s shopping results draw from product feeds, which led OpenAI to roll out product feed ads in May. The same feed also powers organic recommendations.</p>



<p class="wp-block-paragraph">Start by rewriting short or keyword-stuffed titles so they describe the product in plain language. Fill in the optional fields you&#8217;ve been skipping, keep pricing and availability current, and submit your feed directly to the AI search tools that accept one instead of leaving them to guess from whatever they find on your site.</p>



<div class="nl-inline-form border py-2 px-1 my-2">
	
	<div class="row align-items-center nl-inline-container">
		<div class="col-12 col-lg-3 col-xl-4 pe-md-0 pb-2 pb-lg-0">
			<p class="inline-form-text text-center mb-0">Get the newsletter search marketers rely on.</p>
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			<p class="text-center mb-0"><a class="nl-terms" href="https://searchengineland.com/termsofuse" target="_blank" aria-label="opens in a new tab">See terms.</a>
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</div>




<hr class="wp-block-separator has-text-color has-cyan-bluish-gray-color has-css-opacity has-cyan-bluish-gray-background-color has-background"/>



<h2 id="h-a-5-step-framework-for-redeploying-paid-search-terms-into-ai" class="wp-block-heading">A 5-step framework for redeploying paid search terms into AI</h2>



<p class="wp-block-paragraph">Work through these in order. The early steps set everything that follows.</p>



<h3 id="h-step-1-open-the-gates" class="wp-block-heading">Step 1: Open the gates</h3>



<p class="wp-block-paragraph">Confirm your site is indexed in Bing and verified in Bing Webmaster Tools, since ChatGPT searches rely on Bing&#8217;s index. Audit your robots.txt file to ensure OAI-SearchBot and other AI search crawlers you want visibility with aren&#8217;t blocked.</p>



<h3 id="h-step-2-mine-the-search-terms-report-for-conversational-intent" class="wp-block-heading">Step 2: Mine the search terms report for conversational intent</h3>



<p class="wp-block-paragraph">Export 12 months of search terms across campaigns. Filter for searches with five or more words, questions, and comparisons. </p>



<p class="wp-block-paragraph">Group them by theme and conversion value, then add them to your website as a prioritized list of questions the site must answer explicitly. This replaces speculative &#8220;what might people ask ChatGPT?&#8221; exercises with observed demand you already paid to discover.</p>



<h3 id="h-step-3-republish-winning-ad-copy-as-citable-page-content" class="wp-block-heading">Step 3: Republish winning ad copy as citable page content</h3>



<p class="wp-block-paragraph">Identify your top responsive search ad assets by conversion performance. Verify each high-performing claim exists as crawlable, on-page text — exact numbers and exact guarantees — on relevant pages. </p>



<p class="wp-block-paragraph">Then add schema markup — simple behind-the-scenes code that tells search engines and AI tools exactly what your page says — so there&#8217;s no confusion about your claims.</p>



<h3 id="h-step-4-upgrade-the-product-feed-for-ai-platforms" class="wp-block-heading">Step 4: Upgrade the product feed for AI platforms</h3>



<p class="wp-block-paragraph">Rewrite product titles in descriptive, natural language, complete optional attributes, and verify pricing and availability accuracy. Then put your feed to work in both places: </p>



<ul class="wp-block-list">
<li>Keep it updated in Merchant Center so it powers Google&#8217;s AI results.</li>



<li>Submit it to OpenAI so ChatGPT&#8217;s shopping results pull from your actual data instead of whatever it finds online. </li>
</ul>



<p class="wp-block-paragraph">One feed now supports both paid and organic visibility across both platforms.</p>



<h3 id="h-step-5-measure-then-test-paid-ai-placements" class="wp-block-heading">Step 5: Measure, then test paid AI placements</h3>



<p class="wp-block-paragraph">Start by finding out how much traffic AI tools are already sending you. In your analytics, set up tracking for visits from chatgpt.com, perplexity.ai, and copilot.microsoft.com so you have a baseline to measure against. </p>



<p class="wp-block-paragraph">Expand your paid presence one step at a time. Make sure your Google campaigns can appear in AI Overviews and AI Mode (through Shopping, Performance Max, or AI Max for Search), explore Copilot ad placements in Microsoft Advertising, and consider ChatGPT&#8217;s self-serve ads if that&#8217;s where your audience is.</p>



<p class="wp-block-paragraph"><strong><em>Dig deeper: <a href="https://searchengineland.com/ai-visibility-ppc-performance-484199">How AI visibility adds context to PPC performance</a></em></strong>


<a href="https://www.semrush.com/analytics/traffic/paid-search?utm_campaign=ic_sel_0101ppc&#038;utm_source=searchengineland.com&#038;utm_medium=overlay&#038;onboarding=off" target="_blank">
  <div>
    
    <div>
      
      <div id="semrush-one-headline" class="headline-responsive">
        See exactly how <span>your competitors win</span>.
      </div>
      <p id="semrush-one-subhead">
        Uncover the keywords, ads, landing pages, and strategies driving your competitors&#8217; paid search success—and find your next opportunity to outperform them.
      </p>
    </div>
    <div>
      <span id="semrush-one-cta">Analyze your competitors</span>
    </div>
    </div>
    </a>




<h2 id="h-put-your-paid-search-assets-to-work-for-ai-search" class="wp-block-heading">Put your paid search assets to work for AI search</h2>



<p class="wp-block-paragraph">AI search visibility is being pitched as something brand new that requires brand new spend. But if you&#8217;re already running paid search, the hard part is done. </p>



<p class="wp-block-paragraph">The customer data, the proven messaging, and the product feeds — you&#8217;ve already paid for all of it. The only thing missing is connecting what&#8217;s in your ad account to the places AI tools look.</p>



<p class="wp-block-paragraph">Businesses that make that connection get more value from everything they&#8217;re already doing. Every new search term teaches you something, every winning ad makes your website stronger, and every feed update works in more than one place. </p>



<p class="wp-block-paragraph">Businesses that don&#8217;t will end up paying for two separate strategies — one that learns and one that guesses. You don&#8217;t need to build an AI search strategy from scratch. You just need to put the one you&#8217;ve been paying for to work in new places.</p>

Ask most marketing teams how they plan to stay visible in AI search, and you’ll most commonly hear: content strategies, SEO audits, and schema projects. What rarely comes up is the paid search account they’ve been running for years.
That’s a big miss. The things AI search tools reward — clear answers, structured product data, strong landing pages, and messaging that matches how people talk — are things paid search practitioners influence every day. As a result, most businesses already own the raw data for AI visibility. They just don’t realize it.
Here’s how the assets in your paid search account translate into visibility across AI search tools like ChatGPT, Google’s AI Overviews and AI Mode, Microsoft Copilot, and Perplexity. Plus, get a five-step framework to put those assets to work now.
Your ad account already knows how your customers search
Most businesses think of their Google Ads account as a place where budget goes in and leads come out. But it’s also one of the richest sources of data you have about how customers actually search, including how they phrase problems, compare options, and decide what to buy.
Here’s what your ad account already contains:
Search term data shows the exact language customers use at every stage of their journey, including long, conversational queries that resemble AI prompts.
Ad copy performance data reveals which value propositions, offers, and phrasings earn clicks and conversions.
Conversion data identifies which products, services, and pages actually drive revenue, not just traffic.
Product feed infrastructure, with structured titles, attributes, images, and pricing, is already formatted for machine learning.
Landing pages are built for relevance, clarity, and speed to meet Quality Score and CPC standards.
Every one of those assets maps to something AI search systems use when deciding which businesses to mention. Teams treating AI visibility as a “from scratch” project are ignoring years of paid search learnings. The teams pulling ahead are treating the ad account as the research layer for their AI search strategy.
your competitors win.
      
Analyze your competitors
    
Search term data: Conversational intent
The biggest behavioral shift AI search introduced is query length. People don’t type “crm small business” into ChatGPT — they type “what’s the best CRM for a five-person landscaping company that mostly needs scheduling and invoicing?”
Paid search campaigns have already surfaced these terms. Broad match, Performance Max, and AI Max have been matching ads to long-tail, natural-language searches for years through search terms reporting. Your search terms report is a preview of the questions customers are asking AI tools.
Here’s what this looks like in practice. 
An HVAC client running a Google Ads search campaign exported the last 12 months of search terms and found questions like “why is my AC running but not cooling the house” and “best HVAC company for older homes near me.” After pulling these conversational searches out, we grouped them by theme. Then we searched the client’s website using those queries to identify whether there was a clear, quotable answer to each one. Wherever there wasn’t, we found a gap between what customers were asking and what AI tools could pull from the site.
In another example, when reviewing a plumbing company’s search terms report, we found dozens of queries like “how much does it cost to replace a water heater in a condo.” These searches converted well, but the website said nothing concrete about pricing. Google Ads profited from that gap. ChatGPT will simply cite a competitor that published the answer.
Your best ads already have the right message
Your ad copy has already been tested with real buyers. Your highest-performing ads already reflect customer intent. That messaging usually doesn’t surface outside your ad platform. Your website says one thing, while the ads that convert say another. AI tools only see your website — they never see your ads.
To fix this, find your best-performing headlines and descriptions, then make sure those same claims and offers appear as plain text on the pages your ads point to. 
If “24/7 emergency service — arrival in 90 minutes or less” is your best-converting headline, that promise should be on the page itself, not just in the ad. Ad copy also happens to be exactly what AI tools like to quote: specific numbers, timeframes, guarantees, and prices — not vague marketing language.
Product feeds power paid and organic AI visibility
If you run Shopping campaigns, your product feed is one of your most leveraged assets. The same structured data you built for Google Merchant Center — accurate titles, complete attributes, quality images, current availability, and pricing — is now what AI shopping tools use to decide which products to show.
Product feed quality is a primary eligibility signal for whether Shopping and Performance Max ads appear in AI Overviews and AI Mode. On OpenAI’s side, ChatGPT’s shopping results draw from product feeds, which led OpenAI to roll out product feed ads in May. The same feed also powers organic recommendations.
Start by rewriting short or keyword-stuffed titles so they describe the product in plain language. Fill in the optional fields you’ve been skipping, keep pricing and availability current, and submit your feed directly to the AI search tools that accept one instead of leaving them to guess from whatever they find on your site.
Get the newsletter search marketers rely on.
 
				
				
			
See terms.
		
A 5-step framework for redeploying paid search terms into AI
Work through these in order. The early steps set everything that follows.
Step 1: Open the gates
Confirm your site is indexed in Bing and verified in Bing Webmaster Tools, since ChatGPT searches rely on Bing’s index. Audit your robots.txt file to ensure OAI-SearchBot and other AI search crawlers you want visibility with aren’t blocked.
Step 2: Mine the search terms report for conversational intent
Export 12 months of search terms across campaigns. Filter for searches with five or more words, questions, and comparisons. 
Group them by theme and conversion value, then add them to your website as a prioritized list of questions the site must answer explicitly. This replaces speculative “what might people ask ChatGPT?” exercises with observed demand you already paid to discover.
Step 3: Republish winning ad copy as citable page content
Identify your top responsive search ad assets by conversion performance. Verify each high-performing claim exists as crawlable, on-page text — exact numbers and exact guarantees — on relevant pages. 
Then add schema markup — simple behind-the-scenes code that tells search engines and AI tools exactly what your page says — so there’s no confusion about your claims.
Step 4: Upgrade the product feed for AI platforms
Rewrite product titles in descriptive, natural language, complete optional attributes, and verify pricing and availability accuracy. Then put your feed to work in both places: 
Keep it updated in Merchant Center so it powers Google’s AI results.
Submit it to OpenAI so ChatGPT’s shopping results pull from your actual data instead of whatever it finds online. 
One feed now supports both paid and organic visibility across both platforms.
Step 5: Measure, then test paid AI placements
Start by finding out how much traffic AI tools are already sending you. In your analytics, set up tracking for visits from chatgpt.com, perplexity.ai, and copilot.microsoft.com so you have a baseline to measure against. 
Expand your paid presence one step at a time. Make sure your Google campaigns can appear in AI Overviews and AI Mode (through Shopping, Performance Max, or AI Max for Search), explore Copilot ad placements in Microsoft Advertising, and consider ChatGPT’s self-serve ads if that’s where your audience is.
Dig deeper: How AI visibility adds context to PPC performance



  
your competitors win.
      
Analyze your competitors
    
Put your paid search assets to work for AI search
AI search visibility is being pitched as something brand new that requires brand new spend. But if you’re already running paid search, the hard part is done. 
The customer data, the proven messaging, and the product feeds — you’ve already paid for all of it. The only thing missing is connecting what’s in your ad account to the places AI tools look.
Businesses that make that connection get more value from everything they’re already doing. Every new search term teaches you something, every winning ad makes your website stronger, and every feed update works in more than one place. 
Businesses that don’t will end up paying for two separate strategies — one that learns and one that guesses. You don’t need to build an AI search strategy from scratch. You just need to put the one you’ve been paying for to work in new places.

The search terms, ads, landing pages, and product feeds you've already built can strengthen your visibility across AI search.

Why paid search could be your AI search advantage

<div><img width="1920" height="1097" src="https://searchengineland.com/wp-content/seloads/2026/08/google-assitant-1920.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/google-assitant-1920.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/08/google-assitant-1920-768x439.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/08/google-assitant-1920-1536x878.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Gemini will be replacing the Google Assistant on these devices.

<div><img width="1920" height="1097" src="https://searchengineland.com/wp-content/seloads/2026/08/google-assitant-1920.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/google-assitant-1920.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/08/google-assitant-1920-768x439.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/08/google-assitant-1920-1536x878.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p class="wp-block-paragraph">Over a year ago, Google told us that <a href="https://searchengineland.com/google-to-replace-google-assistant-with-gemini-453269">Gemini would be replacing the Google Assistant</a>. Well, we finally have an official date for when Gemini will replace Google Assistant on mobile devices such as Android and Wear OS. The date is September 4, 2026.</p>



<p class="wp-block-paragraph"><strong>What Google said. </strong>Google sent out an email to some users saying:</p>



<ul class="wp-block-list">
<li>&#8220;As we transition our mobile experience to Gemini, Google Assistant will no longer be available on your mobile device.&#8221; </li>



<li>&#8220;We will begin removing access to Google Assistant starting on 4 September, and expect that this process may take a few weeks to reach everyone.&#8221;</li>



<li>&#8220;Once availability is removed, you will no longer be able to use or switch back to Google Assistant on your phone, tablet or paired devices.&#8221;</li>
</ul>



<p class="wp-block-paragraph"><strong>Devices impacted. </strong>This is impacting mobile devices to start, including devices paird with your mobile device such as:</p>



<ul class="wp-block-list">
<li>Watches running Wear OS</li>



<li>Headphones or earbuds compatible with Gemini</li>



<li>Vehicles running Android Auto projected from a user&#8217;s mobile device. For cars with Google built-in, Google Assistant will continue to function beyond 4 September 2026.</li>
</ul>



<p class="wp-block-paragraph"><strong>The email. </strong>A copy of the email can be found on <a href="https://www.reddit.com/r/google/comments/1vfm5s1/google_assistant_is_going_away_on_mobile_devices/">Reddit</a> and I stitched it together for you to read:</p>



<figure class="wp-block-image size-full"><img decoding="async" width="705" height="2048" src="https://searchengineland.com/wp-content/seloads/2026/08/google-assistant-going-away-laEdSzU1-scaled.png" alt="" class="wp-image-484312" srcset="https://searchengineland.com/wp-content/seloads/2026/08/google-assistant-going-away-laEdSzU1-scaled.png 705w, https://searchengineland.com/wp-content/seloads/2026/08/google-assistant-going-away-laEdSzU1-768x2231.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/google-assistant-going-away-laEdSzU1-529x1536.png 529w" sizes="(max-width: 705px) 100vw, 705px" /></figure>



<p class="wp-block-paragraph"><strong>Why we care. </strong>Again, this comes as no surprise but no we finally have an official date for the move. This may lead to more AI-based brand visibility for you and your clients but it may be too soon to tell.</p>



<p class="wp-block-paragraph">It will be interesting to see how searcher behavior changes as both Gemini replaces Google Assistant on Android devices and the new Siri, Apple Intelligence, also powered by Gemini, replaces the old Siri with iOS 27 this coming September. </p>


Over a year ago, Google told us that Gemini would be replacing the Google Assistant. Well, we finally have an official date for when Gemini will replace Google Assistant on mobile devices such as Android and Wear OS. The date is September 4, 2026.
What Google said. Google sent out an email to some users saying:
“As we transition our mobile experience to Gemini, Google Assistant will no longer be available on your mobile device.” 
“We will begin removing access to Google Assistant starting on 4 September, and expect that this process may take a few weeks to reach everyone.”
“Once availability is removed, you will no longer be able to use or switch back to Google Assistant on your phone, tablet or paired devices.”
Devices impacted. This is impacting mobile devices to start, including devices paird with your mobile device such as:
Watches running Wear OS
Headphones or earbuds compatible with Gemini
Vehicles running Android Auto projected from a user’s mobile device. For cars with Google built-in, Google Assistant will continue to function beyond 4 September 2026.
The email. A copy of the email can be found on Reddit and I stitched it together for you to read:




Why we care. Again, this comes as no surprise but no we finally have an official date for the move. This may lead to more AI-based brand visibility for you and your clients but it may be too soon to tell.
It will be interesting to see how searcher behavior changes as both Gemini replaces Google Assistant on Android devices and the new Siri, Apple Intelligence, also powered by Gemini, replaces the old Siri with iOS 27 this coming September.

Gemini will be replacing the Google Assistant on these devices.

Google Assistant to be discontinued on Android starting September 4

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/08/Soci-20260805.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Soci-20260805.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/08/Soci-20260805-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/08/Soci-20260805-1536x864.jpg 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Soci-20260805-1200x675.jpg 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Learn how to boost visibility across search, social, reputation, and AI using SOCi's F.A.C.T.S. model for multi-location brands.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/08/Soci-20260805.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Soci-20260805.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/08/Soci-20260805-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/08/Soci-20260805-1536x864.jpg 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Soci-20260805-1200x675.jpg 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div><div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/08/Soci-20260805.jpg" alt="" class="wp-image-484208" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Soci-20260805.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/08/Soci-20260805-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/08/Soci-20260805-1536x864.jpg 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Soci-20260805-1200x675.jpg 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></figure>
</div>


<p class="wp-block-paragraph">For years, Google has <a href="https://developers.google.com/search/docs/fundamentals/creating-helpful-content" target="_blank" rel="noopener sponsored nofollow">used the E-E-A-T framework</a> to assess the quality of web content. The acronym stands for Experience, Expertise, Authoritativeness, and Trustworthiness.</p>



<p class="wp-block-paragraph">Google recommends that content creators follow E-E-A-T principles because they signal value to searchers and align with what Google&#8217;s search algorithms are designed to reward.</p>



<p class="wp-block-paragraph">Another long-standing Google framework is Relevance, Distance, and Prominence. Google identifies these three signals in its document, <a href="https://support.google.com/business/answer/7091?hl=en" target="_blank" rel="noopener sponsored nofollow">Tips to Improve Your Local Ranking on Google</a>, as the primary factors that influence local search rankings.</p>



<p class="wp-block-paragraph">Frameworks like these can help you identify what to improve to boost search rankings. But until now, there hasn&#8217;t been a comparable framework for AI visibility or one that reflects the priorities of multi-location marketers across search, social, reputation, and AI — the integrated approach we&#8217;ve come to call search everywhere optimization.</p>



<p class="wp-block-paragraph">That&#8217;s why we developed the <a href="https://sociai-www.nyc3.digitaloceanspaces.com/wp-content/uploads/2026/07/17133748/FACTS-Checklist-PDF_June23-1.pdf" target="_blank" rel="noopener sponsored nofollow">F.A.C.T.S. model</a>. F.A.C.T.S. stands for the five factors we believe matter most in a holistic strategy: Freshness, Authority, Consistency, Trust, and Semantic Relevance.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="989" height="441" src="https://searchengineland.com/wp-content/seloads/2026/08/Soci-image1-20260805.jpg" alt="" class="wp-image-484209" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Soci-image1-20260805.jpg 989w, https://searchengineland.com/wp-content/seloads/2026/08/Soci-image1-20260805-768x342.jpg 768w" sizes="(max-width: 989px) 100vw, 989px" /></figure>
</div>


<h2 id="h-freshness" class="wp-block-heading">Freshness</h2>



<p class="wp-block-paragraph">Freshness refers to how recently you publish content on your website and third-party profiles like Google, Yelp, and Facebook. Fresh content matters to people, and search engines and AI platforms also strongly favor it.</p>



<p class="wp-block-paragraph">The average URL cited by AI platforms is 25.7% newer than those cited in traditional search, a recent Ahrefs study <a href="https://ziptie.dev/blog/content-refresh-strategy-for-ai-citations/" target="_blank" rel="noopener sponsored nofollow">found</a>. More than 70% of AI-cited pages were updated within the past 12 months, according to AirOps; meanwhile, 76.4% of ChatGPT’s top-cited pages were updated within the past 30 days, SE Ranking found.</p>



<h2 id="h-authority" class="wp-block-heading">Authority</h2>



<p class="wp-block-paragraph">On this point, our model is similar to Google’s. Authority reflects how a brand demonstrates leadership in its industry.&nbsp;</p>



<p class="wp-block-paragraph">For example, if you’ve been in business since 1963, listing that in your Google profile signals authority. Trusted sources can also reinforce it, including professional certifications, best-of lists, and positive coverage in online publications.</p>



<p class="wp-block-paragraph">Because authority is a complex signal, definitive research on its importance can be hard to find. Its inclusion in E-E-A-T underscores its significance, and Google’s Prominence factor in local search describes a similar concept.&nbsp;</p>



<p class="wp-block-paragraph">Brands publishing authoritative content in their area of expertise and earning recommendations from trusted online sources are <a href="https://www.rankscience.com/blog/ai-citations-brand-mentions-visibility-gap#:~:text=in%20either%20direction.-,Why%20Brand%20Mentions%20Now%20Outweigh%20Backlinks%20for%20AI%20Visibility,more%20accurately%20than%20backlink%20profiles." target="_blank" rel="noopener sponsored nofollow">40% more likely to appear in AI answers</a> than brands missing either factor, AirOps found.</p>



<h2 id="h-consistency" class="wp-block-heading">Consistency</h2>



<p class="wp-block-paragraph">In local visibility, consistency has evolved. It once meant listing each location’s name, address, phone number, and website uniformly across as many directories as possible. As the directory landscape contracted and Google grew dominant, these long-tail citations became largely irrelevant.</p>



<p class="wp-block-paragraph">But AI&#8217;s need to ground answers in trusted sources has renewed the importance of managing your brand&#8217;s presence across multiple platforms — not hundreds of directories, but the handful of sources AI platforms are most likely to cite for local queries.</p>



<p class="wp-block-paragraph">Google Maps, business websites, Yelp, and Facebook (in that order) are the sources most often cited for local queries on ChatGPT, Gemini, and Perplexity, <a href="https://www.soci.ai/ai-visibility-report/" target="_blank" rel="noopener sponsored nofollow">SOCi’s research</a> indicates. However, top sources vary by industry, and individual brands may have citation profiles that differ from the norm.</p>



<p class="wp-block-paragraph">Our <a href="https://www.soci.ai/lvi-2026/" target="_blank" rel="noopener sponsored nofollow">Local Visibility Index</a> shows that inconsistency is a key driver of inaccurate AI mentions and weak brand visibility. While 98% of the brand locations studied had claimed Google profiles, only 80% had claimed Yelp profiles, and just 53% managed Facebook store pages. As a likely result, LLM citations for local brands are only about 79% accurate.</p>



<h2 id="h-trust" class="wp-block-heading">Trust</h2>



<p class="wp-block-paragraph">We use trust to describe signals from outside the brand that reflect approval from both consumers and experts. In local search, trust is conveyed largely through ratings and reviews on platforms like Google and Yelp, which AI platforms use as a primary factor when recommending local brands.</p>



<p class="wp-block-paragraph">Our <a href="https://www.soci.ai/insights/consumer-behavior-index/" target="_blank" rel="noopener sponsored nofollow">Consumer Behavior Index</a> shows that 92% of consumers consult online reviews when choosing a local business. Reflecting this behavior, AI tools use reviews to assess how highly customers regard a brand. The Local Visibility Index found that businesses recommended by ChatGPT average 4.4 stars, compared with 4.2 stars on Google and 3.1 stars on Yelp. AI platforms are setting a higher standard for inclusion in a more selective set of results.</p>



<h2 id="h-semantic-relevance" class="wp-block-heading">Semantic Relevance</h2>



<p class="wp-block-paragraph">Like authority, semantic relevance is complex but can be summarized with one question: Does your brand — across its website, local landing pages, online profiles, and posts — answer every question ideal customers may have before choosing it over a competitor?</p>



<p class="wp-block-paragraph">As with many F.A.C.T.S. factors, this matters more than ever in an AI context. The average traditional search query is four words, while the average AI query is 23, according to <a href="https://www.orbitmedia.com/blog/traditional-search-vs-ai-search/" target="_blank" rel="noopener sponsored nofollow">Orbit Media</a>. Consumers using AI ask longer, more nuanced questions, so brands must create detailed, useful content to avoid exclusion.</p>



<h2 id="h-f-a-c-t-s-is-a-filter-through-which-all-optimization-opportunities-should-be-evaluated" class="wp-block-heading">F.A.C.T.S. is a filter through which all optimization opportunities should be evaluated</h2>



<p class="wp-block-paragraph">Most marketing teams don’t have time to chase every algorithm rumor. You must prioritize the optimizations with the greatest impact. This is where F.A.C.T.S. becomes a practical, daily tool for your team.</p>



<p class="wp-block-paragraph">Before investing in a new local marketing tactic or content update, run it through the F.A.C.T.S. filter. Ask:</p>



<ul class="wp-block-list">
<li>Does it provide an immediate or ongoing freshness signal?</li>



<li>Does it establish our business as an industry authority with clear evidence?</li>



<li>Is it consistent with our brand’s source of truth?</li>



<li>Does it create an opportunity to strengthen trust signals?</li>



<li>Is it semantically relevant to a specific local customer need?</li>
</ul>



<p class="wp-block-paragraph">If an opportunity doesn’t meet these criteria, move it to the bottom of the priority list.</p>



<h2 id="h-how-can-f-a-c-t-s-be-applied-to-your-brand-s-marketing-strategy" class="wp-block-heading">How can F.A.C.T.S. be applied to your brand&#8217;s marketing strategy?</h2>



<p class="wp-block-paragraph">At the brand level, the F.A.C.T.S. filter helps you build an error-free foundation that strengthens relevance and prominence across your location network. Your team manages the core data, technical health, and brand-wide signals.&nbsp;</p>



<p class="wp-block-paragraph">By securing these elements centrally, you help every location pass an algorithm’s baseline risk and confidence checks:</p>



<ul class="wp-block-list">
<li><strong>Freshness:</strong> Keep the brand’s digital pulse active across the network. Use feeds to push seasonal updates and national promotions to local pages and listings. Archive outdated content and use APIs to keep core operational information current, signaling that the network is active and valid.</li>



<li><strong>Authority:</strong> Use the strength of the brand domain to provide comparative data and evidence of expertise. Connect every local page to the authoritative main website. Feature national press coverage, industry awards, and original research to support the brand’s claims at scale.</li>



<li><strong>Consistency:</strong> Build algorithmic confidence by serving as the single source of truth. Audit data aggregators, claim major directory profiles, and suppress duplicate or rogue listings. Consistent data reduces the risk of being filtered out.</li>



<li><strong>Trust:</strong> Support the algorithm’s risk assessment with a secure, technically healthy website. Use compliant, automated review-request workflows that avoid incentivization. Monitor recurring poor customer experiences and spam attacks before they damage brand trust.</li>



<li><strong>Semantic relevance:</strong> Move beyond basic catalogs with an intent-based content architecture. Create dedicated service pages and comprehensive FAQs that address the meaning and common pain points behind customer queries. Structure the corporate site around the definitive solutions AI tools are likely to cite.</li>
</ul>



<h2 id="h-the-f-a-c-t-s-advantage" class="wp-block-heading">The F.A.C.T.S. advantage</h2>



<p class="wp-block-paragraph">Ultimately, F.A.C.T.S. reflects a simple consumer instinct: brands that are current, credible, consistent, trusted, and genuinely useful earn visibility across search, social, and AI. Whatever the research shows, brands are on the right track when their online strategies meet these fundamental customer needs.</p>


For years, Google has used the E-E-A-T framework to assess the quality of web content. The acronym stands for Experience, Expertise, Authoritativeness, and Trustworthiness.
Google recommends that content creators follow E-E-A-T principles because they signal value to searchers and align with what Google’s search algorithms are designed to reward.
Another long-standing Google framework is Relevance, Distance, and Prominence. Google identifies these three signals in its document, Tips to Improve Your Local Ranking on Google, as the primary factors that influence local search rankings.
Frameworks like these can help you identify what to improve to boost search rankings. But until now, there hasn’t been a comparable framework for AI visibility or one that reflects the priorities of multi-location marketers across search, social, reputation, and AI — the integrated approach we’ve come to call search everywhere optimization.
That’s why we developed the F.A.C.T.S. model. F.A.C.T.S. stands for the five factors we believe matter most in a holistic strategy: Freshness, Authority, Consistency, Trust, and Semantic Relevance.




Freshness
Freshness refers to how recently you publish content on your website and third-party profiles like Google, Yelp, and Facebook. Fresh content matters to people, and search engines and AI platforms also strongly favor it.
The average URL cited by AI platforms is 25.7% newer than those cited in traditional search, a recent Ahrefs study found. More than 70% of AI-cited pages were updated within the past 12 months, according to AirOps; meanwhile, 76.4% of ChatGPT’s top-cited pages were updated within the past 30 days, SE Ranking found.
Authority
On this point, our model is similar to Google’s. Authority reflects how a brand demonstrates leadership in its industry. 
For example, if you’ve been in business since 1963, listing that in your Google profile signals authority. Trusted sources can also reinforce it, including professional certifications, best-of lists, and positive coverage in online publications.
Because authority is a complex signal, definitive research on its importance can be hard to find. Its inclusion in E-E-A-T underscores its significance, and Google’s Prominence factor in local search describes a similar concept. 
Brands publishing authoritative content in their area of expertise and earning recommendations from trusted online sources are 40% more likely to appear in AI answers than brands missing either factor, AirOps found.
Consistency
In local visibility, consistency has evolved. It once meant listing each location’s name, address, phone number, and website uniformly across as many directories as possible. As the directory landscape contracted and Google grew dominant, these long-tail citations became largely irrelevant.
But AI’s need to ground answers in trusted sources has renewed the importance of managing your brand’s presence across multiple platforms — not hundreds of directories, but the handful of sources AI platforms are most likely to cite for local queries.
Google Maps, business websites, Yelp, and Facebook (in that order) are the sources most often cited for local queries on ChatGPT, Gemini, and Perplexity, SOCi’s research indicates. However, top sources vary by industry, and individual brands may have citation profiles that differ from the norm.
Our Local Visibility Index shows that inconsistency is a key driver of inaccurate AI mentions and weak brand visibility. While 98% of the brand locations studied had claimed Google profiles, only 80% had claimed Yelp profiles, and just 53% managed Facebook store pages. As a likely result, LLM citations for local brands are only about 79% accurate.
Trust
We use trust to describe signals from outside the brand that reflect approval from both consumers and experts. In local search, trust is conveyed largely through ratings and reviews on platforms like Google and Yelp, which AI platforms use as a primary factor when recommending local brands.
Our Consumer Behavior Index shows that 92% of consumers consult online reviews when choosing a local business. Reflecting this behavior, AI tools use reviews to assess how highly customers regard a brand. The Local Visibility Index found that businesses recommended by ChatGPT average 4.4 stars, compared with 4.2 stars on Google and 3.1 stars on Yelp. AI platforms are setting a higher standard for inclusion in a more selective set of results.
Semantic Relevance
Like authority, semantic relevance is complex but can be summarized with one question: Does your brand — across its website, local landing pages, online profiles, and posts — answer every question ideal customers may have before choosing it over a competitor?
As with many F.A.C.T.S. factors, this matters more than ever in an AI context. The average traditional search query is four words, while the average AI query is 23, according to Orbit Media. Consumers using AI ask longer, more nuanced questions, so brands must create detailed, useful content to avoid exclusion.
F.A.C.T.S. is a filter through which all optimization opportunities should be evaluated
Most marketing teams don’t have time to chase every algorithm rumor. You must prioritize the optimizations with the greatest impact. This is where F.A.C.T.S. becomes a practical, daily tool for your team.
Before investing in a new local marketing tactic or content update, run it through the F.A.C.T.S. filter. Ask:
Does it provide an immediate or ongoing freshness signal?
Does it establish our business as an industry authority with clear evidence?
Is it consistent with our brand’s source of truth?
Does it create an opportunity to strengthen trust signals?
Is it semantically relevant to a specific local customer need?
If an opportunity doesn’t meet these criteria, move it to the bottom of the priority list.
How can F.A.C.T.S. be applied to your brand’s marketing strategy?
At the brand level, the F.A.C.T.S. filter helps you build an error-free foundation that strengthens relevance and prominence across your location network. Your team manages the core data, technical health, and brand-wide signals. 
By securing these elements centrally, you help every location pass an algorithm’s baseline risk and confidence checks:
Freshness: Keep the brand’s digital pulse active across the network. Use feeds to push seasonal updates and national promotions to local pages and listings. Archive outdated content and use APIs to keep core operational information current, signaling that the network is active and valid.
Authority: Use the strength of the brand domain to provide comparative data and evidence of expertise. Connect every local page to the authoritative main website. Feature national press coverage, industry awards, and original research to support the brand’s claims at scale.
Consistency: Build algorithmic confidence by serving as the single source of truth. Audit data aggregators, claim major directory profiles, and suppress duplicate or rogue listings. Consistent data reduces the risk of being filtered out.
Trust: Support the algorithm’s risk assessment with a secure, technically healthy website. Use compliant, automated review-request workflows that avoid incentivization. Monitor recurring poor customer experiences and spam attacks before they damage brand trust.
Semantic relevance: Move beyond basic catalogs with an intent-based content architecture. Create dedicated service pages and comprehensive FAQs that address the meaning and common pain points behind customer queries. Structure the corporate site around the definitive solutions AI tools are likely to cite.
The F.A.C.T.S. advantage
Ultimately, F.A.C.T.S. reflects a simple consumer instinct: brands that are current, credible, consistent, trusted, and genuinely useful earn visibility across search, social, and AI. Whatever the research shows, brands are on the right track when their online strategies meet these fundamental customer needs.

Learn how to boost visibility across search, social, reputation, and AI using SOCi's F.A.C.T.S. model for multi-location brands.

Why the F.A.C.T.S. model is the key to search everywhere optimization by SOCi

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/Google-LocalAds-PMax-.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Google-LocalAds-PMax-.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/Google-LocalAds-PMax--768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Google-LocalAds-PMax--1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Google-LocalAds-PMax--1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>The new guides explain how advertisers can set up, target and optimise Performance Max campaigns with pay-per-lead goals.

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/Google-LocalAds-PMax-.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Google-LocalAds-PMax-.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/Google-LocalAds-PMax--768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Google-LocalAds-PMax--1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Google-LocalAds-PMax--1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>
<p class="wp-block-paragraph">Google has published three new Help Center pages explaining how Performance Max campaigns with pay-per-lead goals will work, following its announcement that <a href="https://searchengineland.com/local-services-ads-come-to-google-ads-via-performance-max-482692">Local Services Ads (LSAs) are being integrated into Google Ads</a>.</p>



<p class="wp-block-paragraph">The documentation provides the clearest look yet at how advertisers will configure, target and optimise the new campaign type.</p>



<p class="wp-block-paragraph"><strong>What&#8217;s happening</strong>. The newly released Help pages cover three key areas of the rollout:</p>



<ul class="wp-block-list">
<li>Campaign settings for Performance Max campaigns with pay-per-lead goals.</li>



<li>Targeting options for pay-per-lead campaigns.</li>



<li>Best practices for maximising performance.</li>
</ul>



<p class="wp-block-paragraph">The guides outline how advertisers can configure campaigns, define service areas, select business categories and optimise toward lead generation rather than traditional conversion objectives.</p>



<p class="wp-block-paragraph"><strong>Why we care.</strong> The Help pages offer more insight into Google&#8217;s plan to bring Local Services Ads into the broader Google Ads ecosystem. Instead of managing LSAs separately, eligible advertisers will increasingly be able to run pay-per-lead campaigns through Performance Max, potentially simplifying campaign management while expanding automation.</p>



<p class="wp-block-paragraph"><strong>Bottom line.</strong> <a href="https://support.google.com/google-ads/answer/17325051">Google&#8217;s latest Help documentation</a> provides advertisers with an early roadmap for managing Performance Max campaigns with pay-per-lead goals, ahead of the wider rollout of Local Services Ads within Google Ads.</p>



<p class="wp-block-paragraph"><strong>Dig deeper.</strong>



<ul class="wp-block-list">
<li><a href="https://support.google.com/google-ads/answer/17325351" target="_blank" rel="noopener">About targeting for pay-per-lead goals for Performance Max</a></li>



<li><a href="https://support.google.com/google-ads/answer/17326561" target="_blank" rel="noopener">Best practices for pay-per-lead goals for Performance Max campaigns</a></li>
</ul>


Google has published three new Help Center pages explaining how Performance Max campaigns with pay-per-lead goals will work, following its announcement that Local Services Ads (LSAs) are being integrated into Google Ads.
The documentation provides the clearest look yet at how advertisers will configure, target and optimise the new campaign type.
What’s happening. The newly released Help pages cover three key areas of the rollout:
Campaign settings for Performance Max campaigns with pay-per-lead goals.
Targeting options for pay-per-lead campaigns.
Best practices for maximising performance.
The guides outline how advertisers can configure campaigns, define service areas, select business categories and optimise toward lead generation rather than traditional conversion objectives.
Why we care. The Help pages offer more insight into Google’s plan to bring Local Services Ads into the broader Google Ads ecosystem. Instead of managing LSAs separately, eligible advertisers will increasingly be able to run pay-per-lead campaigns through Performance Max, potentially simplifying campaign management while expanding automation.
Bottom line. Google’s latest Help documentation provides advertisers with an early roadmap for managing Performance Max campaigns with pay-per-lead goals, ahead of the wider rollout of Local Services Ads within Google Ads.
Dig deeper.




About targeting for pay-per-lead goals for Performance Max
Best practices for pay-per-lead goals for Performance Max campaigns

The new guides explain how advertisers can set up, target and optimise Performance Max campaigns with pay-per-lead goals.

Google releases help doc for Performance Max pay-per-lead goals

<div><img width="1254" height="708" src="https://searchengineland.com/wp-content/seloads/2026/08/Screenshot-2026-08-05-at-11.22.13.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Screenshot-2026-08-05-at-11.22.13.png 1254w, https://searchengineland.com/wp-content/seloads/2026/08/Screenshot-2026-08-05-at-11.22.13-768x434.png 768w" sizes="(max-width: 1254px) 100vw, 1254px" /></div>The new pilot lets advertisers restrict sensitive API actions to approved applications, adding an extra layer of security.

<div><img width="1254" height="708" src="https://searchengineland.com/wp-content/seloads/2026/08/Screenshot-2026-08-05-at-11.22.13.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Screenshot-2026-08-05-at-11.22.13.png 1254w, https://searchengineland.com/wp-content/seloads/2026/08/Screenshot-2026-08-05-at-11.22.13-768x434.png 768w" sizes="(max-width: 1254px) 100vw, 1254px" /></div>
<p class="wp-block-paragraph">Google is piloting a new security feature for the Google Ads API that gives manager account owners greater control over which applications can perform sensitive API actions.</p>



<p class="wp-block-paragraph">The feature is designed to reduce the risk of unauthorized access while improving visibility into third-party tools connected to Google Ads accounts.</p>



<p class="wp-block-paragraph"><strong>What&#8217;s happening.</strong> Google is inviting developers to participate in a pilot that restricts sensitive Google Ads API methods—such as account management, user management and billing operations—to a pre-approved allowlist of Google Cloud projects.</p>



<p class="wp-block-paragraph">To join the pilot, participants submit the customer ID of their top-level Google Ads manager account. Google then audits API activity across the account hierarchy, identifies the applications in use, and works with the advertiser to establish an allowlist of approved tools. Once enabled, any application not on that allowlist will be blocked from making sensitive API requests.</p>



<p class="wp-block-paragraph">Advertisers can also request approval for new applications after joining the program, while newly linked accounts automatically inherit the security protections from the protected manager account.</p>



<p class="wp-block-paragraph"><strong>Why we care.</strong> Agencies and large advertisers often rely on multiple third-party tools to manage Google Ads accounts. The allowlist provides an additional layer of protection by ensuring only trusted applications can perform high-risk actions, even if API credentials are compromised.</p>



<p class="wp-block-paragraph"><strong>The bigger picture.</strong> As advertising platforms become increasingly interconnected with external software, Google is investing more heavily in account security. The pilot complements recent security initiatives, including <a href="https://searchengineland.com/google-makes-passkeys-mandatory-for-google-ads-api-users-483617">mandatory passkey authentication for Google Ads API users</a>, by tightening control over who—and what—can access sensitive account functions.</p>



<p class="wp-block-paragraph"><strong>Bottom line.</strong> <a href="https://ads-developers.googleblog.com/2026/08/google-ads-api-pilot-secure-api-access.html">Google&#8217;s latest Google Ads API pilot</a> gives manager account owners more control over API access, helping protect sensitive account operations by limiting them to verified applications.</p>



<p class="wp-block-paragraph">


Google is piloting a new security feature for the Google Ads API that gives manager account owners greater control over which applications can perform sensitive API actions.
The feature is designed to reduce the risk of unauthorized access while improving visibility into third-party tools connected to Google Ads accounts.
What’s happening. Google is inviting developers to participate in a pilot that restricts sensitive Google Ads API methods—such as account management, user management and billing operations—to a pre-approved allowlist of Google Cloud projects.
To join the pilot, participants submit the customer ID of their top-level Google Ads manager account. Google then audits API activity across the account hierarchy, identifies the applications in use, and works with the advertiser to establish an allowlist of approved tools. Once enabled, any application not on that allowlist will be blocked from making sensitive API requests.
Advertisers can also request approval for new applications after joining the program, while newly linked accounts automatically inherit the security protections from the protected manager account.
Why we care. Agencies and large advertisers often rely on multiple third-party tools to manage Google Ads accounts. The allowlist provides an additional layer of protection by ensuring only trusted applications can perform high-risk actions, even if API credentials are compromised.
The bigger picture. As advertising platforms become increasingly interconnected with external software, Google is investing more heavily in account security. The pilot complements recent security initiatives, including mandatory passkey authentication for Google Ads API users, by tightening control over who—and what—can access sensitive account functions.
Bottom line. Google’s latest Google Ads API pilot gives manager account owners more control over API access, helping protect sensitive account operations by limiting them to verified applications.

The new pilot lets advertisers restrict sensitive API actions to approved applications, adding an extra layer of security.

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Read the Latest Trends and Headlines in Digital Marketing.

Here are some of the latest headlines on digital marketing insights, search, and ecommerce:

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