<div><img width="1920" height="1081" src="https://searchengineland.com/wp-content/seloads/2026/01/How-LLMs-See-Brands.png" class="attachment-large size-large wp-post-image" alt="How LLMs see brands" style="margin-bottom: 15px;" decoding="async" fetchpriority="high" srcset="https://searchengineland.com/wp-content/seloads/2026/01/How-LLMs-See-Brands.png 1920w, https://searchengineland.com/wp-content/seloads/2026/01/How-LLMs-See-Brands-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/01/How-LLMs-See-Brands-1536x865.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>A roundtable of SEO’s most trusted voices explains how LLMs really surface brands, why shortcuts fail, and what's working now.

<div><img width="1920" height="1081" src="https://searchengineland.com/wp-content/seloads/2026/01/How-LLMs-See-Brands.png" class="attachment-large size-large wp-post-image" alt="How LLMs see brands" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/How-LLMs-See-Brands.png 1920w, https://searchengineland.com/wp-content/seloads/2026/01/How-LLMs-See-Brands-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/01/How-LLMs-See-Brands-1536x865.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>One of the biggest SEO challenges right now isn’t AI. It’s the irresponsible misinformation surrounding it. </p>



<p><a href="https://searchengineland.com/ai-search-booming-seo-still-not-dead-458935">SEO isn’t dying — it’s evolving</a>. That means it’s on us to understand how the industry is changing, and to be careful about who we listen to.</p>



<p>I’m not easily shocked, but some of the AEO (or GEO) talks I’ve seen over the past year have been genuinely eyebrow-raising — even for someone with Botox. </p>



<p>I still remember one speaker telling a room full of marketers they were “sorry for anyone still working in SEO,” then immediately recommending outdated tactics as the “secret sauce” for LLM visibility. It’s been… painful.</p>



<p>Thankfully, the adults have entered the room. This week, four of the industry’s most trusted voices — <a href="https://www.linkedin.com/in/lily-ray-44755615/" target="_blank" rel="noopener">Lily Ray</a>, <a href="https://www.linkedin.com/in/kevinindig/">Kevin Indig</a>, <a href="https://www.linkedin.com/in/stevetothjr/">Steve Toth</a>, and <a href="https://www.linkedin.com/in/rosshudgens/">Ross Hudgens</a> — came together for a roundtable on the future of search. It was easily the most useful AEO session I’ve attended. Each shared specific tactics they’ve personally used to achieve LLM visibility. </p>



<p>Here’s what they had to say.</p>



<h2 class="wp-block-heading" id="h-1-advertorials-work">1. Advertorials work</h2>



<p>LLMs don’t currently distinguish between paid and organic editorial. That means well-placed advertorials on reputable publishers can help brands show up in AI search, much like earned coverage. As with traditional PR, the publication&#8217;s credibility still matters most.</p>



<h2 class="wp-block-heading" id="h-2-syndication-can-scale-visibility">2. Syndication can scale visibility</h2>



<p>Paid syndication can increase reach, but quality matters more than quantity. Focus on reputable, relevant publications and use this tactic carefully.</p>



<h2 class="wp-block-heading" id="h-3-map-pages-to-every-audience-and-use-case-you-serve">3. Map pages to every audience and use case you serve</h2>



<p>Brands that create clearly defined pages for each audience, industry, and use case are better positioned as AI search becomes more personalized. This structure helps LLMs understand relevance and remains a strong SEO practice, with or without AI.</p>



<h2 class="wp-block-heading" id="h-4-homepage-clarity">4. Homepage clarity</h2>



<p>Your homepage should clearly communicate who you serve and what you do. LLMs parse homepage content far more easily than navigation menus, so relying on your nav to explain your offering is a missed opportunity.</p>



<h2 class="wp-block-heading" id="h-5-optimize-your-footer">5. Optimize your footer</h2>



<p>Don’t overlook your footer. Brand and service signals placed here are being picked up by LLMs. Wil Reynolds shared <a href="https://www.seerinteractive.com/insights/ai-optimization-test-footers-are-back-like-2003">a great case study</a> showing how footer content can directly influence AI visibility.</p>



<h2 class="wp-block-heading" id="h-6-don-t-prioritize-llm-txt">6. Don’t prioritize llm.txt</h2>



<p>Despite the speculation, no major LLM has confirmed using llm.txt files, and <a href="https://www.seroundtable.com/google-does-not-endorse-llms-txt-40789.html" target="_blank" rel="noopener">Google has explicitly said it does not</a>. Your time and effort are better spent elsewhere.</p>



<h2 class="wp-block-heading" id="h-7-go-multimodal">7. Go multimodal</h2>



<p>Repurpose your core content across text, video, audio, and imagery. The goal is to build brand recognition across the full range of sources an LLM may pull from.</p>



<h2 class="wp-block-heading" id="h-8-actively-shape-your-brand-narrative">8. Actively shape your brand narrative</h2>



<p>Actively shape your brand narrative. It&#8217;s estimated that 250 documents are needed to meaningfully influence how an LLM perceives a brand. Brands that don’t publish and promote content consistently risk letting others define that narrative for them.</p>



<h2 class="wp-block-heading" id="h-9-freshness-carries-disproportionate-weight">9. Freshness carries disproportionate weight</h2>



<p>Recent content tends to perform especially well in AI search, reflecting LLMs’ preference for up-to-date information. That said, artificial “refreshing” without meaningful updates is a bad idea.</p>



<h2 class="wp-block-heading" id="h-10-social-works-fast">10. Social works fast</h2>



<p>Posts on platforms like LinkedIn—including Pulse articles—can appear in AI search within hours, sometimes minutes, especially for accounts with strong followings. Reddit, YouTube, and other high-trust platforms show similar behavior.</p>



<h2 class="wp-block-heading" id="h-11-authority-accelerates-inclusion">11. Authority accelerates inclusion</h2>



<p>Publishing on respected, niche industry sites can lead to rapid inclusion in LLM responses — sometimes within hours.</p>



<h2 class="wp-block-heading" id="h-12-don-t-hide-faqs">12. Don’t hide FAQs</h2>



<p>FAQs should be visible and substantial, not hidden behind accordions. Don’t hold back on content either— eight to 10 well-answered questions can clearly signal expertise, intent, and relevance to both users and LLMs.</p>



<ol class="wp-block-list"></ol>



<h2 class="wp-block-heading" id="h-is-aeo-the-same-as-seo">Is AEO the same as SEO? </h2>



<p>This much-debated question was <a href="https://www.linkedin.com/posts/schwartze_everyones-looking-for-the-aeogeo-secrets-activity-7405672878899187712-j_ln/" target="_blank" rel="noopener">addressed directly by John Mueller at Google Search Live</a> in December. Putting the AEO cowboys in their place, he made it clear that good AEO still relies on good SEO:</p>



<ul class="wp-block-list">
<li>&#8220;AI systems rely on search. and there is no such thing as GEO or AEO without doing SEO fundamentals. Tricks will come out and they will work for a short time, companies that want to be around for the long term should focus on something that is proven with long term stability and not tricks.&#8221; </li>
</ul>



<p>The overlap makes sense when you look at how modern LLMs like GPT-5 actually work. They use Retrieval-Augmented Generation (RAG). Rather than relying only on frozen training data, RAG lets an LLM query search engines and trusted sources in real time before answering. </p>



<p>Put simply: if you want LLM visibility, you need to show up in search first.</p>



<ul class="wp-block-list">
<li><a href="https://www.youtube.com/watch?v=2nJkT8zOzcM">Lily Ray has an excellent video</a> explaining this process in more detail, which is well worth watching.</li>
</ul>



<p>So yes, good AEO is good SEO — but there’s nuance. The tactics above work right now, but they will inevitably evolve as LLMs continue to advance.</p>



<h2 class="wp-block-heading" id="h-the-best-ai-search-strategy-for-2026">The best AI search strategy for 2026</h2>



<p>Forget the magic button. Keep testing. Stay skeptical of the hype. And be selective about who you let into your ear — or your LinkedIn feed.</p>



<p><em>Thanks to Bernard Huang and Clearscope for hosting this excellent panel.</em></p>


One of the biggest SEO challenges right now isn’t AI. It’s the irresponsible misinformation surrounding it. 
SEO isn’t dying — it’s evolving. That means it’s on us to understand how the industry is changing, and to be careful about who we listen to.
I’m not easily shocked, but some of the AEO (or GEO) talks I’ve seen over the past year have been genuinely eyebrow-raising — even for someone with Botox. 
I still remember one speaker telling a room full of marketers they were “sorry for anyone still working in SEO,” then immediately recommending outdated tactics as the “secret sauce” for LLM visibility. It’s been… painful.
Thankfully, the adults have entered the room. This week, four of the industry’s most trusted voices — Lily Ray, Kevin Indig, Steve Toth, and Ross Hudgens — came together for a roundtable on the future of search. It was easily the most useful AEO session I’ve attended. Each shared specific tactics they’ve personally used to achieve LLM visibility. 
Here’s what they had to say.
1. Advertorials work
LLMs don’t currently distinguish between paid and organic editorial. That means well-placed advertorials on reputable publishers can help brands show up in AI search, much like earned coverage. As with traditional PR, the publication’s credibility still matters most.
2. Syndication can scale visibility
Paid syndication can increase reach, but quality matters more than quantity. Focus on reputable, relevant publications and use this tactic carefully.
3. Map pages to every audience and use case you serve
Brands that create clearly defined pages for each audience, industry, and use case are better positioned as AI search becomes more personalized. This structure helps LLMs understand relevance and remains a strong SEO practice, with or without AI.
4. Homepage clarity
Your homepage should clearly communicate who you serve and what you do. LLMs parse homepage content far more easily than navigation menus, so relying on your nav to explain your offering is a missed opportunity.
5. Optimize your footer
Don’t overlook your footer. Brand and service signals placed here are being picked up by LLMs. Wil Reynolds shared a great case study showing how footer content can directly influence AI visibility.
6. Don’t prioritize llm.txt
Despite the speculation, no major LLM has confirmed using llm.txt files, and Google has explicitly said it does not. Your time and effort are better spent elsewhere.
7. Go multimodal
Repurpose your core content across text, video, audio, and imagery. The goal is to build brand recognition across the full range of sources an LLM may pull from.
8. Actively shape your brand narrative
Actively shape your brand narrative. It’s estimated that 250 documents are needed to meaningfully influence how an LLM perceives a brand. Brands that don’t publish and promote content consistently risk letting others define that narrative for them.
9. Freshness carries disproportionate weight
Recent content tends to perform especially well in AI search, reflecting LLMs’ preference for up-to-date information. That said, artificial “refreshing” without meaningful updates is a bad idea.
10. Social works fast
Posts on platforms like LinkedIn—including Pulse articles—can appear in AI search within hours, sometimes minutes, especially for accounts with strong followings. Reddit, YouTube, and other high-trust platforms show similar behavior.
11. Authority accelerates inclusion
Publishing on respected, niche industry sites can lead to rapid inclusion in LLM responses — sometimes within hours.
12. Don’t hide FAQs
FAQs should be visible and substantial, not hidden behind accordions. Don’t hold back on content either— eight to 10 well-answered questions can clearly signal expertise, intent, and relevance to both users and LLMs.




Is AEO the same as SEO? 
This much-debated question was addressed directly by John Mueller at Google Search Live in December. Putting the AEO cowboys in their place, he made it clear that good AEO still relies on good SEO:
“AI systems rely on search. and there is no such thing as GEO or AEO without doing SEO fundamentals. Tricks will come out and they will work for a short time, companies that want to be around for the long term should focus on something that is proven with long term stability and not tricks.” 
The overlap makes sense when you look at how modern LLMs like GPT-5 actually work. They use Retrieval-Augmented Generation (RAG). Rather than relying only on frozen training data, RAG lets an LLM query search engines and trusted sources in real time before answering. 
Put simply: if you want LLM visibility, you need to show up in search first.
Lily Ray has an excellent video explaining this process in more detail, which is well worth watching.
So yes, good AEO is good SEO — but there’s nuance. The tactics above work right now, but they will inevitably evolve as LLMs continue to advance.
The best AI search strategy for 2026
Forget the magic button. Keep testing. Stay skeptical of the hype. And be selective about who you let into your ear — or your LinkedIn feed.
Thanks to Bernard Huang and Clearscope for hosting this excellent panel.

A roundtable of SEO’s most trusted voices explains how LLMs really surface brands, why shortcuts fail, and what's working now.

How to optimize for AI search: 12 proven LLM visibility tactics

<div><img width="1920" height="1097" src="https://searchengineland.com/wp-content/seloads/2026/01/bar-chart-1920.jpg" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/bar-chart-1920.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/01/bar-chart-1920-768x439.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/01/bar-chart-1920-1536x878.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>42% said they would not block Google and 25% are still unsure.

<div><img width="1920" height="1097" src="https://searchengineland.com/wp-content/seloads/2026/01/bar-chart-1920.jpg" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/bar-chart-1920.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/01/bar-chart-1920-768x439.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/01/bar-chart-1920-1536x878.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Google announced yesterday that it is exploring ways for sites to <a href="https://searchengineland.com/google-may-give-sites-a-way-to-opt-out-of-ai-search-generative-features-468063">opt out of Google using their content</a> for its AI-generative search features, such as AI Mode and AI Overviews. I asked the SEO community on X if they would opt out of these Google Search AI-generative features or not.</p>



<p><strong>The results. </strong>Of the over 350 responses that took the poll yesterday, most said they would not opt out.  However, about 1/3 of respondents said they would block or opt out of these features. Here is the breakdown:</p>



<p>Question: Would you block Google from using your content for AI Overviews and AI Mode?</p>



<ul class="wp-block-list">
<li>33.2% &#8211; Yes, I&#8217;d block Google</li>



<li>41.9% &#8211; No, I wouldn&#8217;t block</li>



<li>24.9% &#8211; I am not sure yet.</li>
</ul>



<p>Here is the actual poll:</p>



<figure class="wp-block-embed is-type-rich is-provider-twitter wp-block-embed-twitter"><div class="wp-block-embed__wrapper">
<blockquote class="twitter-tweet" data-width="500" data-dnt="true"><p lang="en" dir="ltr">Would you block Google from using your content for AI Overviews and AI Mode &#8211; Google may be giving us more controls &#8211; take my poll below. <a href="https://t.co/60M3Vt0YlN">https://t.co/60M3Vt0YlN</a></p>&mdash; Barry Schwartz (@rustybrick) <a href="https://twitter.com/rustybrick/status/2016468488622071935?ref_src=twsrc%5Etfw">January 28, 2026</a></blockquote><script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
</div></figure>



<p><strong>How to opt out. </strong>We don&#8217;t know. Google only said it is &#8220;exploring&#8221; ways to handle this but has not provided any mechanism for this.  So we don&#8217;t know how hard or easy it would be to opt out.  The easier it is, the more likely sites will opt out; the harder, the less likely. </p>



<p><strong>Why we care. </strong>The true number of sites that might opt out of AI Mode or AI Overviews won&#8217;t be known until the mechanism is out to handle this.  And trust me, there will be many reports on how many sites are opting out. </p>



<p>Like recently, &#8220;Some 79% of almost 100 top news websites in the UK and US are blocking at least one crawler used for AI training out of OpenAI’s GPTBot, ClaudeBot, Anthropic-ai, CCBot, Applebot-Extended and Google-Extended,&#8221; reported <a href="https://pressgazette.co.uk/platforms/eight-in-ten-of-worlds-biggest-news-websites-now-block-ai-training-bots/">The Press Gazette</a>.</p>



<p>My recommendation; once it is out, it is something you will want to test and see the results of opting out or opting in.</p>


Google announced yesterday that it is exploring ways for sites to opt out of Google using their content for its AI-generative search features, such as AI Mode and AI Overviews. I asked the SEO community on X if they would opt out of these Google Search AI-generative features or not.
The results. Of the over 350 responses that took the poll yesterday, most said they would not opt out.  However, about 1/3 of respondents said they would block or opt out of these features. Here is the breakdown:
Question: Would you block Google from using your content for AI Overviews and AI Mode?
33.2% – Yes, I’d block Google
41.9% – No, I wouldn’t block
24.9% – I am not sure yet.
Here is the actual poll:


Would you block Google from using your content for AI Overviews and AI Mode – Google may be giving us more controls – take my poll below. https://t.co/60M3Vt0YlN
— Barry Schwartz (@rustybrick) January 28, 2026





How to opt out. We don’t know. Google only said it is “exploring” ways to handle this but has not provided any mechanism for this.  So we don’t know how hard or easy it would be to opt out.  The easier it is, the more likely sites will opt out; the harder, the less likely. 
Why we care. The true number of sites that might opt out of AI Mode or AI Overviews won’t be known until the mechanism is out to handle this.  And trust me, there will be many reports on how many sites are opting out. 
Like recently, “Some 79% of almost 100 top news websites in the UK and US are blocking at least one crawler used for AI training out of OpenAI’s GPTBot, ClaudeBot, Anthropic-ai, CCBot, Applebot-Extended and Google-Extended,” reported The Press Gazette.
My recommendation; once it is out, it is something you will want to test and see the results of opting out or opting in.

42% said they would not block Google and 25% are still unsure.

1/3rd of publishers say they will block Google Search AI-generative features like AI Overviews

<div><img width="800" height="450" src="https://searchengineland.com/wp-content/seloads/2025/03/Your-guide-to-Google-Ads-Smart-Bidding-800x450.png" class="attachment-large size-large wp-post-image" alt="Your guide to Google Ads Smart Bidding" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/03/Your-guide-to-Google-Ads-Smart-Bidding-800x450.png 800w, https://searchengineland.com/wp-content/seloads/2025/03/Your-guide-to-Google-Ads-Smart-Bidding-600x338.png 600w, https://searchengineland.com/wp-content/seloads/2025/03/Your-guide-to-Google-Ads-Smart-Bidding-200x113.png 200w, https://searchengineland.com/wp-content/seloads/2025/03/Your-guide-to-Google-Ads-Smart-Bidding-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2025/03/Your-guide-to-Google-Ads-Smart-Bidding-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2025/03/Your-guide-to-Google-Ads-Smart-Bidding.png 1920w" sizes="(max-width: 800px) 100vw, 800px" /></div>Google’s v23 Ads API speeds up releases while adding deeper Performance Max insights, AI-driven audiences, and more granular reporting.

<div><img width="800" height="450" src="https://searchengineland.com/wp-content/seloads/2025/03/Your-guide-to-Google-Ads-Smart-Bidding-800x450.png" class="attachment-large size-large wp-post-image" alt="Your guide to Google Ads Smart Bidding" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/03/Your-guide-to-Google-Ads-Smart-Bidding-800x450.png 800w, https://searchengineland.com/wp-content/seloads/2025/03/Your-guide-to-Google-Ads-Smart-Bidding-600x338.png 600w, https://searchengineland.com/wp-content/seloads/2025/03/Your-guide-to-Google-Ads-Smart-Bidding-200x113.png 200w, https://searchengineland.com/wp-content/seloads/2025/03/Your-guide-to-Google-Ads-Smart-Bidding-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2025/03/Your-guide-to-Google-Ads-Smart-Bidding-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2025/03/Your-guide-to-Google-Ads-Smart-Bidding.png 1920w" sizes="(max-width: 800px) 100vw, 800px" /></div>
<p>Google released v23 of the Google Ads API, the first update of 2026. It marks the start of a faster release cadence. </p>



<p><strong>What’s new</strong>. The update adds deeper Performance Max reporting, more granular invoicing, AI-powered audience tools, expanded campaign controls, and more:</p>



<ul class="wp-block-list">
<li><strong>Performance Max transparency:</strong> Ad network type breakdowns are now available for PMax campaigns.</li>



<li><strong>More detailed invoices:</strong> Campaign-level costs, regulatory fees, and adjustments can be retrieved via InvoiceService.</li>



<li><strong>More precise scheduling:</strong> Campaigns can now use start and end date-times instead of date-only fields.</li>



<li><strong>Local data access:</strong> Store location details are available through PerStoreView, matching the Stores report.</li>



<li><strong>New audience dimension:</strong> LIFE_EVENT_USER_INTEREST enables life-event-based audience building in Insights tools.</li>



<li><strong>Smarter Demand Gen planning:</strong> Conversion rate forecasts now vary by surface (e.g., Gmail, Shorts).</li>



<li><strong>Generative AI audiences:</strong> Free-text audience descriptions can be translated into structured audience attributes.</li>



<li><strong>Expanded Shopping metrics:</strong> New competitive and conversion metrics are available by conversion date.</li>
</ul>



<p><strong>Why we care</strong>. A faster update cycle lets advertisers and developers access new capabilities sooner, especially as Google pushes deeper into automation, AI-driven planning, and cross-campaign visibility.</p>



<p><strong>Plan for upgrades</strong>. Some updates require upgrading client libraries and code, so teams may need to plan development time to fully benefit from v23.</p>



<p><strong>Google&#8217;s announcement.</strong> <a href="http://ads-developers.googleblog.com/2026/01/announcing-v23-of-google-ads-api.html" target="_blank" rel="noopener">Announcing v23 of the Google Ads API</a></p>


Google released v23 of the Google Ads API, the first update of 2026. It marks the start of a faster release cadence. 
What’s new. The update adds deeper Performance Max reporting, more granular invoicing, AI-powered audience tools, expanded campaign controls, and more:
Performance Max transparency: Ad network type breakdowns are now available for PMax campaigns.
More detailed invoices: Campaign-level costs, regulatory fees, and adjustments can be retrieved via InvoiceService.
More precise scheduling: Campaigns can now use start and end date-times instead of date-only fields.
Local data access: Store location details are available through PerStoreView, matching the Stores report.
New audience dimension: LIFE_EVENT_USER_INTEREST enables life-event-based audience building in Insights tools.
Smarter Demand Gen planning: Conversion rate forecasts now vary by surface (e.g., Gmail, Shorts).
Generative AI audiences: Free-text audience descriptions can be translated into structured audience attributes.
Expanded Shopping metrics: New competitive and conversion metrics are available by conversion date.
Why we care. A faster update cycle lets advertisers and developers access new capabilities sooner, especially as Google pushes deeper into automation, AI-driven planning, and cross-campaign visibility.
Plan for upgrades. Some updates require upgrading client libraries and code, so teams may need to plan development time to fully benefit from v23.
Google’s announcement. Announcing v23 of the Google Ads API

Google’s v23 Ads API speeds up releases while adding deeper Performance Max insights, AI-driven audiences, and more granular reporting.

Google Ads API v23 brings PMax data, richer invoicing, scheduling

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/01/When-search-performance-improves-but-pipeline-doesnt.jpg" class="attachment-large size-large wp-post-image" alt="When search performance improves but pipeline doesn’t" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/When-search-performance-improves-but-pipeline-doesnt.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/01/When-search-performance-improves-but-pipeline-doesnt-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/01/When-search-performance-improves-but-pipeline-doesnt-1536x864.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Strong rankings and traffic can mask post-click breakdowns. These breakpoints show where intent, conversion, and measurement fail.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/01/When-search-performance-improves-but-pipeline-doesnt.jpg" class="attachment-large size-large wp-post-image" alt="When search performance improves but pipeline doesn’t" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/When-search-performance-improves-but-pipeline-doesnt.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/01/When-search-performance-improves-but-pipeline-doesnt-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/01/When-search-performance-improves-but-pipeline-doesnt-1536x864.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Many search teams are seeing better rankings, more visibility, increased traffic, and more leads. </p>



<p>Yet feedback on pipeline, revenue, and sales outcomes isn’t showing the same positive results.</p>



<p>When <a href="https://searchengineland.com/guide/what-is-seo">SEO</a> KPIs are green and graphs are up and to the right, business outcomes don’t always reflect the same success.</p>



<h2 class="wp-block-heading" id="h-why-strong-search-performance-doesn-t-translate-to-business-outcomes">Why strong search performance doesn’t translate to business outcomes</h2>



<p>Search performance can look healthy on the surface while breaking down in places search teams don’t own or fully see.</p>



<p>It’s tempting to turn immediately to attribution models, data quality, or KPI definitions.&nbsp;</p>



<p>Ultimately, the issue is often how performance breaks down after the click – in areas search teams don’t own.</p>



<p>While search work has become easier to scale with automation, software, established workflows, and frameworks, execution doesn’t equal understanding or deeper control.&nbsp;</p>



<p>This challenge has existed for more than 20 years and can be magnified by scale.</p>



<p>Stopping analysis too early, or keeping it too shallow, limits understanding of performance in the broader context of the business or brand.</p>



<p>In larger organizations, silos widen the gap. When CRM and sales aren’t tightly integrated with search, teams operate independently, with no one owning the full journey.</p>



<p>Pressure from leadership can intensify the problem.&nbsp;</p>



<p>When results look good but fail to deliver at the bottom line, the lack of clarity becomes uncomfortable for everyone. This dynamic isn’t new, but it’s becoming more pronounced.</p>



<p>To help address these disconnects, here are five breakpoints to focus on.</p>



<h2 class="wp-block-heading" id="h-1-intent-misalignment">1. Intent misalignment</h2>



<p><a href="https://searchengineland.com/search-intent-more-types-430814">Intent</a> is what search teams focus on when shaping the content, topics, and focus used to attract target audiences through search. That’s a given.&nbsp;</p>



<p>It doesn’t always match or map to deeper factors such as buying stage, urgency, or alignment with internal sales expectations at a given moment or season.</p>



<p>If traffic is qualified by topic, keyword, or other search criteria, even when intent is aligned with the best available research and data, a prospect’s sales readiness and stage can still be missing or difficult to quantify.</p>



<p>Analyzing what problem the searcher believed they were solving, and how closely that aligns with how sales positions the offering, can help close the gap between search and sales.</p>



<p>That, in turn, allows teams to question whether they are optimizing for demand, curiosity, or another aspect of how someone enters the customer journey.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/explain-flat-traffic-seo-467757">How to explain flat traffic when SEO is actually working</a></em></strong></p>



<h2 class="wp-block-heading" id="h-2-conversion-friction">2. Conversion friction</h2>



<p>When leads driven by search convert on the website, it can become an uncomfortable situation if they don&#8217;t ultimately become clients or customers, and sales has strong opinions about those conversions.</p>



<p>There are many reasons for this friction. Technically, the leads pass the criteria outlined and agreed on within the organization or with an agency.&nbsp;</p>



<p>Problems often exist silently in another gap, sometimes categorized as conversion rate optimization or tied to brand, product development, or related areas. But that is often a distraction.</p>



<p>When teams drill into lead specifics and qualification, the issues often come down to generic forms, CTAs that are not tightly aligned, or unclear next steps between form submission and an actual conversation.</p>



<p>Conversions do not equal customers, or even a commitment to the sales process. </p>



<p>Key questions center on the promise made in the search results, the website content the visitor consumed, and whether the landing page and site journey fulfilled the visitor’s intended goal.</p>



<p>Most importantly, when evaluating performance, teams need to ask what signal a conversion actually sends to the organization, versus what the prospect intended.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/seo-tests-improve-traffic-engagement-conversions-454934">6 SEO tests to help improve traffic, engagement, and conversions</a></em></strong></p>



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<h2 class="wp-block-heading" id="h-3-lead-qualification-gaps">3. Lead qualification gaps</h2>



<p>Whether you operate within a company or environment, including agency and in-house teams, that uses lead scoring and qualification or not, ensuring that marketing-qualified leads are sales-ready is critical in a lead-focused business.</p>



<p>This article is not intended to delve deeply into the differences between marketing-qualified and sales-qualified leads or into all the nuances involved.&nbsp;</p>



<p>However, the challenge cannot be overstated when teams lack shared understanding and definitions.</p>



<p>That includes scoring models, definitions of what qualifies as “qualified,” who agreed to those definitions, and what happens when sales rejects leads.</p>



<p>This may not be comfortable territory to navigate.&nbsp;</p>



<p>But reaching standard definitions and qualification criteria can be some of the most helpful and meaningful work teams do, because it helps prove the value of search.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/monitor-website-performance-seo-metrics-463985">How to monitor your website’s performance and SEO metrics</a></em></strong></p>



<h2 class="wp-block-heading" id="h-4-sales-handoff-and-follow-up">4. Sales handoff and follow-up</h2>



<p>Yes, I’m sharing points, but this is the one that tends to hit the hardest and may be the most challenging.&nbsp;</p>



<p>That’s because you may be a C-level executive, manager, agency partner, or otherwise oversee or be directly involved in the marketing-to-sales handoff.</p>



<p>We are adversaries, friends, and colleagues. I’m not here to revisit the fundamentals of marketing versus sales. But I&#8217;m here to challenge you.</p>



<p>Speed, messaging, and context matter. This is not just about getting a form in front of someone as quickly as possible and whether they fill it out.&nbsp;</p>



<p>Substance and detail matter. Getting the right prospect with the right context, carried through from how they searched and found you, is critical.</p>



<p>Yes, this is harder when analyzing customer journeys that involve LLMs and other sources, but that doesn’t mean teams can’t or shouldn’t try to understand that behavior.</p>



<p>When a disconnect appears in this category, teams should push to understand whether sales knows why the lead came in, how quickly follow-up happened, and whether the messaging aligns with the original intent. These are key areas that help teams tune or adjust their strategies.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/seo-great-sales-leads-terrible-436954">9 things to do when SEO is great but sales and leads are terrible</a></em></strong></p>



<h2 class="wp-block-heading" id="h-5-measurement-blind-spots">5. Measurement blind spots</h2>



<p>Sometimes everything appears to be in place.&nbsp;</p>



<p>Analytics shows conversions and search leads qualify, but there is no movement when reviewing CRM results.&nbsp;</p>



<p>Whether attribution becomes messy, impatience sets in, gray areas emerge, or other factors are at play, blind spots can form.</p>



<p>This often leads teams to default to their own metrics.&nbsp;</p>



<p>No one wins when KPIs are not shared or when there is no single source of truth and trust.</p>



<p>When visibility stops and ownership of “connecting the dots” is unclear, challenges emerge regardless of function, team, or leadership role.&nbsp;</p>



<p>Decisions then get made without full context.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/measuring-what-matters-in-a-post-seo-world-460664">Measuring what matters in a post-SEO world</a></em></strong></p>



<h2 class="wp-block-heading" id="h-the-cost-of-not-knowing-what-s-working">The cost of not knowing what’s working</h2>



<p>I&#8217;m not writing this article to be hard on search marketing leaders or practitioners. This is not a failure of search.</p>



<p>If any of the challenges described here feel familiar, you are not alone, and they are likely cross-functional to solve.</p>



<p>Marketing leaders do not need perfection when it comes to attribution or search efforts. That is not realistic. What is needed instead are better questions, shared definitions, and clear ownership.</p>



<p>The biggest danger is not when performance drops, but when performance is strong and no one knows with confidence why.</p>



<p>Scaling always involves risk, and teams should not scale efforts without conviction or a clear understanding of that risk.&nbsp;</p>



<p>Ultimately, the goal is for search work to build credibility, confidence, and influence beyond deep expertise in search engines and large language models tied to visibility.</p>

Many search teams are seeing better rankings, more visibility, increased traffic, and more leads. 
Yet feedback on pipeline, revenue, and sales outcomes isn’t showing the same positive results.
When SEO KPIs are green and graphs are up and to the right, business outcomes don’t always reflect the same success.
Why strong search performance doesn’t translate to business outcomes
Search performance can look healthy on the surface while breaking down in places search teams don’t own or fully see.
It’s tempting to turn immediately to attribution models, data quality, or KPI definitions. 
Ultimately, the issue is often how performance breaks down after the click – in areas search teams don’t own.
While search work has become easier to scale with automation, software, established workflows, and frameworks, execution doesn’t equal understanding or deeper control. 
This challenge has existed for more than 20 years and can be magnified by scale.
Stopping analysis too early, or keeping it too shallow, limits understanding of performance in the broader context of the business or brand.
In larger organizations, silos widen the gap. When CRM and sales aren’t tightly integrated with search, teams operate independently, with no one owning the full journey.
Pressure from leadership can intensify the problem. 
When results look good but fail to deliver at the bottom line, the lack of clarity becomes uncomfortable for everyone. This dynamic isn’t new, but it’s becoming more pronounced.
To help address these disconnects, here are five breakpoints to focus on.
1. Intent misalignment
Intent is what search teams focus on when shaping the content, topics, and focus used to attract target audiences through search. That’s a given. 
It doesn’t always match or map to deeper factors such as buying stage, urgency, or alignment with internal sales expectations at a given moment or season.
If traffic is qualified by topic, keyword, or other search criteria, even when intent is aligned with the best available research and data, a prospect’s sales readiness and stage can still be missing or difficult to quantify.
Analyzing what problem the searcher believed they were solving, and how closely that aligns with how sales positions the offering, can help close the gap between search and sales.
That, in turn, allows teams to question whether they are optimizing for demand, curiosity, or another aspect of how someone enters the customer journey.
Dig deeper: How to explain flat traffic when SEO is actually working
2. Conversion friction
When leads driven by search convert on the website, it can become an uncomfortable situation if they don’t ultimately become clients or customers, and sales has strong opinions about those conversions.
There are many reasons for this friction. Technically, the leads pass the criteria outlined and agreed on within the organization or with an agency. 
Problems often exist silently in another gap, sometimes categorized as conversion rate optimization or tied to brand, product development, or related areas. But that is often a distraction.
When teams drill into lead specifics and qualification, the issues often come down to generic forms, CTAs that are not tightly aligned, or unclear next steps between form submission and an actual conversation.
Conversions do not equal customers, or even a commitment to the sales process. 
Key questions center on the promise made in the search results, the website content the visitor consumed, and whether the landing page and site journey fulfilled the visitor’s intended goal.
Most importantly, when evaluating performance, teams need to ask what signal a conversion actually sends to the organization, versus what the prospect intended.
Dig deeper: 6 SEO tests to help improve traffic, engagement, and conversions
Get the newsletter search marketers rely on.
  
				
								
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See terms.
3. Lead qualification gaps
Whether you operate within a company or environment, including agency and in-house teams, that uses lead scoring and qualification or not, ensuring that marketing-qualified leads are sales-ready is critical in a lead-focused business.
This article is not intended to delve deeply into the differences between marketing-qualified and sales-qualified leads or into all the nuances involved. 
However, the challenge cannot be overstated when teams lack shared understanding and definitions.
That includes scoring models, definitions of what qualifies as “qualified,” who agreed to those definitions, and what happens when sales rejects leads.
This may not be comfortable territory to navigate. 
But reaching standard definitions and qualification criteria can be some of the most helpful and meaningful work teams do, because it helps prove the value of search.
Dig deeper: How to monitor your website’s performance and SEO metrics
4. Sales handoff and follow-up
Yes, I’m sharing points, but this is the one that tends to hit the hardest and may be the most challenging. 
That’s because you may be a C-level executive, manager, agency partner, or otherwise oversee or be directly involved in the marketing-to-sales handoff.
We are adversaries, friends, and colleagues. I’m not here to revisit the fundamentals of marketing versus sales. But I’m here to challenge you.
Speed, messaging, and context matter. This is not just about getting a form in front of someone as quickly as possible and whether they fill it out. 
Substance and detail matter. Getting the right prospect with the right context, carried through from how they searched and found you, is critical.
Yes, this is harder when analyzing customer journeys that involve LLMs and other sources, but that doesn’t mean teams can’t or shouldn’t try to understand that behavior.
When a disconnect appears in this category, teams should push to understand whether sales knows why the lead came in, how quickly follow-up happened, and whether the messaging aligns with the original intent. These are key areas that help teams tune or adjust their strategies.
Dig deeper: 9 things to do when SEO is great but sales and leads are terrible
5. Measurement blind spots
Sometimes everything appears to be in place. 
Analytics shows conversions and search leads qualify, but there is no movement when reviewing CRM results. 
Whether attribution becomes messy, impatience sets in, gray areas emerge, or other factors are at play, blind spots can form.
This often leads teams to default to their own metrics. 
No one wins when KPIs are not shared or when there is no single source of truth and trust.
When visibility stops and ownership of “connecting the dots” is unclear, challenges emerge regardless of function, team, or leadership role. 
Decisions then get made without full context.
Dig deeper: Measuring what matters in a post-SEO world
The cost of not knowing what’s working
I’m not writing this article to be hard on search marketing leaders or practitioners. This is not a failure of search.
If any of the challenges described here feel familiar, you are not alone, and they are likely cross-functional to solve.
Marketing leaders do not need perfection when it comes to attribution or search efforts. That is not realistic. What is needed instead are better questions, shared definitions, and clear ownership.
The biggest danger is not when performance drops, but when performance is strong and no one knows with confidence why.
Scaling always involves risk, and teams should not scale efforts without conviction or a clear understanding of that risk. 
Ultimately, the goal is for search work to build credibility, confidence, and influence beyond deep expertise in search engines and large language models tied to visibility.

Strong rankings and traffic can mask post-click breakdowns. These breakpoints show where intent, conversion, and measurement fail.

When search performance improves but pipeline doesn’t

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/01/How-to-find-great-writers-and-other-content-marketing-struggles.jpg" class="attachment-large size-large wp-post-image" alt="How to find great writers (and other content marketing struggles)" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/How-to-find-great-writers-and-other-content-marketing-struggles.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/01/How-to-find-great-writers-and-other-content-marketing-struggles-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/01/How-to-find-great-writers-and-other-content-marketing-struggles-1536x864.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>You get what you pay for in content. Here’s how to find great writers in 2026, from job boards to LinkedIn and beyond.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/01/How-to-find-great-writers-and-other-content-marketing-struggles.jpg" class="attachment-large size-large wp-post-image" alt="How to find great writers (and other content marketing struggles)" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/How-to-find-great-writers-and-other-content-marketing-struggles.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/01/How-to-find-great-writers-and-other-content-marketing-struggles-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/01/How-to-find-great-writers-and-other-content-marketing-struggles-1536x864.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Marketers are spoiled for choice when it comes to <a href="https://searchengineland.com/content-strategy-move-beyond-seo-drive-demand-459943">great sources of content</a>.&nbsp;</p>



<p>We now have <a href="https://searchengineland.com/improve-ai-assisted-content-creation-process-tips-394024">more tools</a> (hello, ChatGPT!) and job boards than ever, making it even easier to find writers and create content.</p>



<p>But abundance comes with a downside: a race to the bottom, where speed and cost often take priority over quality.</p>



<p>If you’re aiming for <strong>great</strong> (not just “good”) content, some sources are better than others.&nbsp;</p>



<p>This guide breaks down where to find top-tier writers and how to build a content process that doesn’t sacrifice quality for speed.</p>



<h2 class="wp-block-heading" id="h-struggle-1-what-qualifies-as-a-great-content-writer">Struggle 1: What qualifies as a ‘great’ content writer?</h2>



<p>Qualifying a good writer can feel a lot like qualifying a new love interest. They look good on paper and make a good first impression, but how do you really know they’re “the one”?</p>



<p>The hard truth is that, just like with a love interest, you’ll have to spend time getting to know your writer before you really get an answer. But that doesn’t mean you have to go in blind.&nbsp;</p>



<p>Follow the non-negotiables below to increase your odds of finding a good fit without wasting time</p>



<h3 class="wp-block-heading" id="h-evaluate-the-fundamentals">Evaluate the fundamentals</h3>



<p>Does this writer understand basic grammar, spelling, clarity, and structure? You don’t need a formal test to spot this – just take a look at their portfolio and content examples. </p>



<p>Also, a few email exchanges during the hiring process can be enough to gauge how confidently they communicate and how well they handle the written word.&nbsp;&nbsp;</p>



<h3 class="wp-block-heading" id="h-make-sure-they-know-how-to-write-for-people-not-bots">Make sure they know how to write for <em>people</em>, not bots</h3>



<p>Strong content writers understand a key truth.</p>



<p>Search engines reward content written for people, not formulas. If you’re looking for <a href="https://searchengineland.com/guide/what-is-seo">SEO</a> expertise, review writers’ samples with this in mind.</p>



<p>Be cautious of pieces overloaded with keywords or awkward phrasing that hurts readability. </p>



<p>As you read, ask yourself, “If I were the target audience, would this feel useful, engaging, and easy to consume?” </p>



<p>If the answer is no, chances are search engines won’t love it, either.</p>



<h3 class="wp-block-heading" id="h-choose-effective-copywriters">Choose effective copywriters</h3>



<p>If you want to doubly ensure that you’re going to get a great return on your investment, prioritize writers who understand <a href="https://searchengineland.com/seo-copywriting-pillars-ranking-relevance-457295">SEO copywriting</a>, not just <a href="https://searchengineland.com/optimize-content-seos-writers-274956">SEO tactics</a>.&nbsp;</p>



<p>Driving traffic is only half the equation. Writers with copywriting skills know how to guide readers toward action, whether that’s signing up, clicking through, or making a purchase.&nbsp;</p>



<h3 class="wp-block-heading" id="h-assess-how-easily-understandable-their-work-is">Assess how easily understandable their work is</h3>



<p>Checking their content for readability is crucial. Run the writer’s work samples through a readability scoring app like HemingwayApp.com. </p>



<p>Sometimes an article will look great on the surface, but you’ll find that it carries a low readability score. This means the way it&#8217;s written lacks clarity and is difficult to consume.</p>



<h3 class="wp-block-heading" id="h-find-writers-that-adapt-to-the-audience-nbsp">Find writers that adapt to the audience&nbsp;</h3>



<p>Your writer must understand the intersection between your audience and your niche. It isn&#8217;t enough to know the product or the demographic in isolation.</p>



<p>Great writers grasp how your audience thinks, what frustrates them, what holds them back, and what ultimately motivates them to act.&nbsp;</p>



<p>The simplest way to uncover this? Ask for relevant, niche-specific samples and pay close attention to how they demonstrate that understanding.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/how-seo-can-collaborate-with-content-teams-446257">How SEO can collaborate with content teams</a></em></strong></p>



<h2 class="wp-block-heading" id="h-struggle-2-where-can-i-find-great-content-writers">Struggle 2: Where can I find great content writers?</h2>



<p>Speaking objectively, you can find “good” writers anywhere. </p>



<p>But there’s definitely a difference between shopping around on Fiverr versus other higher-quality avenues that offer you better screening opportunities.</p>



<h3 class="wp-block-heading" id="h-blogging-sites">Blogging sites</h3>



<p>One of the best ways to vet an SEO content writer is to find them on blogging sites where they post <a href="https://searchengineland.com/long-form-content-steps-examples-392592">long-form content</a>. </p>



<p>Platforms like Medium, Substack, and even LinkedIn (look at the posted articles) let you see how writers think, write, and communicate in real time, not just in polished portfolio pieces.</p>



<h3 class="wp-block-heading" id="h-google-and-other-search-engines">Google and other search engines</h3>



<p>Another often-overlooked place to find high-quality writers is Google itself. Writers who invest in their own websites are effectively practicing what they preach.&nbsp;</p>



<p>Ranking their own content, maintaining a consistent publishing schedule, and building a personal brand all demonstrate a working understanding of SEO and content marketing.</p>



<h3 class="wp-block-heading" id="h-linkedin-and-facebook-groups">LinkedIn and Facebook groups</h3>



<p>Great writers can also be found in groups on LinkedIn or Facebook. Find writer or freelancer groups and spend time observing the conversations.&nbsp;</p>



<p>You’ll notice writers posting in quality groups to share their thoughts and examples of their work. You can also see how they interact with other users and prospective clients.</p>



<h3 class="wp-block-heading" id="h-peer-recommendations">Peer recommendations</h3>



<p>Don’t hesitate to ask for recommendations in the writer groups you come across. Strong writers are often well known within their communities, and peers are usually quick to point you toward people who consistently deliver real value.</p>



<p>Consider asking other business owners for recommendations as well. Tapping into your peer group can surface writers who have proven themselves in real-world projects. High-quality writers tend to earn repeat business, making referrals one of the most reliable vetting tools available.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/how-to-build-a-helpful-content-strategy-for-2023-391074">How to build an effective content strategy for 2026</a></em></strong></p>



<h2 class="wp-block-heading" id="h-struggle-3-do-i-need-an-sop-for-my-writers">Struggle 3: Do I need an ‘SOP’ for my writers?</h2>



<p>Yes, you’re probably going to pick an experienced writer who’s also catering to multiple clients while simultaneously working with you.&nbsp;</p>



<p>Each client they work with has different preferences and concerns, from the style of writing, how the work should be submitted, and so on.&nbsp;</p>



<p><a href="https://searchengineland.com/why-sops-are-the-secret-weapon-for-small-seo-teams-456489">Standard operating procedures (SOPs)</a> help minimize the guesswork for your writer and potential headaches for you.</p>



<p>The truth is, most business owners aren’t struggling to find quality writers – they’re struggling to keep them.&nbsp;</p>



<p>Without clear direction, writers have to guess how you want things done, and that generally causes confusion and room for error. With more direction and outlines like an SOP, everyone stays happy.</p>



<p>Writing SOPs may seem like a time-intensive step, but the good news is that once they&#8217;re done, they save you hundreds of hours on the backend. </p>



<p>If you want to take it off your plate, consult an operations specialist who can assist. It’ll increase your return on investment (ROI), help eliminate stress, and keep good writers happy and in your employ.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/documenting-your-content-strategy-393845">How to document your content strategy</a></em></strong></p>



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<h2 class="wp-block-heading" id="h-struggle-4-how-much-should-i-pay-for-content">Struggle 4: How much should I pay for content?</h2>



<p>Low-cost content can be tempting, especially when turnaround times are fast and promises are big. </p>



<p>But the real question isn’t the hourly rate, it’s how much time and effort you’ll spend fixing, revising, or rewriting the work afterward.</p>



<p>Do you have editors available to help, or are you setting yourself up to spend just as much time editing a piece as you would have spent writing it yourself? </p>



<p>The allure of inexpensive writers is high, but unless you have the time and patience to train them, it’s probably not a smart investment.</p>



<p>In 2026, expect to spend <a href="https://bestwriting.com/blog/content-writing-rates/" target="_blank" rel="noopener">at least $0.20 per word</a> for great content.<strong> </strong>That said, prices can vary widely based on a writer’s experience and accolades. </p>



<p>Some of the best writers in the world charge thousands of dollars for a single web page – it just depends on their skills (and the ROI you’re aiming for).</p>



<p>Paying more for experienced writers buys you clarity, expertise, and content that requires far less oversight. The goal isn’t just to “spend more,” but to spend <em>wisely</em> on writing that actually converts.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/mastering-content-quality-guide-433615">Mastering content quality: The ultimate guide</a></em></strong></p>



<h2 class="wp-block-heading" id="h-struggle-5-should-i-use-freelance-writers-or-build-a-team">Struggle 5: Should I use freelance writers or build a team?</h2>



<p>The decision between freelance writers and an in-house team depends on your goals, budget, and stage of growth.</p>



<p>Freelance writers offer flexibility. They’re ideal if you want to scale content production up or down, or don’t yet have the resources to support full-time hires.&nbsp;</p>



<p>Experienced freelancers can plug into your existing workflow, making them a strong option for lean or growing brands.</p>



<p>An in-house team provides consistency, reliability, and deep brand knowledge. Full-time writers have the time to learn your brand voice, products, and audience in great detail.&nbsp;</p>



<p>This can be valuable for businesses that produce a lot of content or work in complex niches. The tradeoff, of course, is higher overhead, longer hiring timelines, and more responsibility.</p>



<p>For many businesses, the best solution is a hybrid model: a small internal team that owns editorial standards, supported by freelance writers who help scale production. </p>



<p>Ultimately, it’s all about building a content system that aligns with your resources and fits your business&#8217;s stage.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/5-seo-content-pitfalls-that-could-be-hurting-your-traffic-452702">5 SEO content pitfalls that could be hurting your traffic</a></em></strong></p>



<h2 class="wp-block-heading" id="h-struggle-6-is-great-content-worth-the-investment">Struggle 6: Is ‘great content’ worth the investment?</h2>



<p>Optimized content is like anything else – you get out of it what you put into it.</p>



<p>If you hire top-quality writers, you’re going to get top-quality content, which in turn will help drive traffic and better rankings for your site.</p>



<p>So yes, it’s worth the investment in high-quality content because the benefits compound over time.</p>



<p>A well-researched, well-written piece can attract qualified visitors for months (or even years) after it’s published. It can also build trust with your audience, leading to even more sales over time.&nbsp;</p>



<p>Great content also supports the entire customer journey. It answers questions, addresses objections, and positions your brand as credible long before a prospect actually decides to buy. </p>



<p><span style="box-sizing: border-box; margin: 0px; padding: 0px;">A great writer helps you bring in the <strong>right</strong>&nbsp;traffic.</span> And that’s worth every penny.</p>



<h2 class="wp-block-heading" id="h-great-writers-come-from-clear-standards-not-lucky-hires">Great writers come from clear standards, not lucky hires</h2>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p>Finding great content writers is less about discovering a hidden talent pool and more about setting clear standards. </p>



<p>When you know what quality looks like, where to look and how to support writers once they’re hired, the process becomes far more predictable – and far less frustrating.</p>



<p>The most successful content programs treat writing as a long-term investment, not a one-off transaction. </p>



<p>By pairing strong writers with clear expectations, fair compensation and repeatable processes, brands can build content engines that consistently deliver value over time.</p>
</blockquote>

Marketers are spoiled for choice when it comes to great sources of content. 
We now have more tools (hello, ChatGPT!) and job boards than ever, making it even easier to find writers and create content.
But abundance comes with a downside: a race to the bottom, where speed and cost often take priority over quality.
If you’re aiming for great (not just “good”) content, some sources are better than others. 
This guide breaks down where to find top-tier writers and how to build a content process that doesn’t sacrifice quality for speed.
Struggle 1: What qualifies as a ‘great’ content writer?
Qualifying a good writer can feel a lot like qualifying a new love interest. They look good on paper and make a good first impression, but how do you really know they’re “the one”?
The hard truth is that, just like with a love interest, you’ll have to spend time getting to know your writer before you really get an answer. But that doesn’t mean you have to go in blind. 
Follow the non-negotiables below to increase your odds of finding a good fit without wasting time
Evaluate the fundamentals
Does this writer understand basic grammar, spelling, clarity, and structure? You don’t need a formal test to spot this – just take a look at their portfolio and content examples. 
Also, a few email exchanges during the hiring process can be enough to gauge how confidently they communicate and how well they handle the written word.  
Make sure they know how to write for people, not bots
Strong content writers understand a key truth.
Search engines reward content written for people, not formulas. If you’re looking for SEO expertise, review writers’ samples with this in mind.
Be cautious of pieces overloaded with keywords or awkward phrasing that hurts readability. 
As you read, ask yourself, “If I were the target audience, would this feel useful, engaging, and easy to consume?” 
If the answer is no, chances are search engines won’t love it, either.
Choose effective copywriters
If you want to doubly ensure that you’re going to get a great return on your investment, prioritize writers who understand SEO copywriting, not just SEO tactics. 
Driving traffic is only half the equation. Writers with copywriting skills know how to guide readers toward action, whether that’s signing up, clicking through, or making a purchase. 
Assess how easily understandable their work is
Checking their content for readability is crucial. Run the writer’s work samples through a readability scoring app like HemingwayApp.com. 
Sometimes an article will look great on the surface, but you’ll find that it carries a low readability score. This means the way it’s written lacks clarity and is difficult to consume.
Find writers that adapt to the audience 
Your writer must understand the intersection between your audience and your niche. It isn’t enough to know the product or the demographic in isolation.
Great writers grasp how your audience thinks, what frustrates them, what holds them back, and what ultimately motivates them to act. 
The simplest way to uncover this? Ask for relevant, niche-specific samples and pay close attention to how they demonstrate that understanding.
Dig deeper: How SEO can collaborate with content teams
Struggle 2: Where can I find great content writers?
Speaking objectively, you can find “good” writers anywhere. 
But there’s definitely a difference between shopping around on Fiverr versus other higher-quality avenues that offer you better screening opportunities.
Blogging sites
One of the best ways to vet an SEO content writer is to find them on blogging sites where they post long-form content. 
Platforms like Medium, Substack, and even LinkedIn (look at the posted articles) let you see how writers think, write, and communicate in real time, not just in polished portfolio pieces.
Google and other search engines
Another often-overlooked place to find high-quality writers is Google itself. Writers who invest in their own websites are effectively practicing what they preach. 
Ranking their own content, maintaining a consistent publishing schedule, and building a personal brand all demonstrate a working understanding of SEO and content marketing.
LinkedIn and Facebook groups
Great writers can also be found in groups on LinkedIn or Facebook. Find writer or freelancer groups and spend time observing the conversations. 
You’ll notice writers posting in quality groups to share their thoughts and examples of their work. You can also see how they interact with other users and prospective clients.
Peer recommendations
Don’t hesitate to ask for recommendations in the writer groups you come across. Strong writers are often well known within their communities, and peers are usually quick to point you toward people who consistently deliver real value.
Consider asking other business owners for recommendations as well. Tapping into your peer group can surface writers who have proven themselves in real-world projects. High-quality writers tend to earn repeat business, making referrals one of the most reliable vetting tools available.
Dig deeper: How to build an effective content strategy for 2026
Struggle 3: Do I need an ‘SOP’ for my writers?
Yes, you’re probably going to pick an experienced writer who’s also catering to multiple clients while simultaneously working with you. 
Each client they work with has different preferences and concerns, from the style of writing, how the work should be submitted, and so on. 
Standard operating procedures (SOPs) help minimize the guesswork for your writer and potential headaches for you.
The truth is, most business owners aren’t struggling to find quality writers – they’re struggling to keep them. 
Without clear direction, writers have to guess how you want things done, and that generally causes confusion and room for error. With more direction and outlines like an SOP, everyone stays happy.
Writing SOPs may seem like a time-intensive step, but the good news is that once they’re done, they save you hundreds of hours on the backend. 
If you want to take it off your plate, consult an operations specialist who can assist. It’ll increase your return on investment (ROI), help eliminate stress, and keep good writers happy and in your employ.
Dig deeper: How to document your content strategy
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See terms.
Struggle 4: How much should I pay for content?
Low-cost content can be tempting, especially when turnaround times are fast and promises are big. 
But the real question isn’t the hourly rate, it’s how much time and effort you’ll spend fixing, revising, or rewriting the work afterward.
Do you have editors available to help, or are you setting yourself up to spend just as much time editing a piece as you would have spent writing it yourself? 
The allure of inexpensive writers is high, but unless you have the time and patience to train them, it’s probably not a smart investment.
In 2026, expect to spend at least $0.20 per word for great content. That said, prices can vary widely based on a writer’s experience and accolades. 
Some of the best writers in the world charge thousands of dollars for a single web page – it just depends on their skills (and the ROI you’re aiming for).
Paying more for experienced writers buys you clarity, expertise, and content that requires far less oversight. The goal isn’t just to “spend more,” but to spend wisely on writing that actually converts.
Dig deeper: Mastering content quality: The ultimate guide
Struggle 5: Should I use freelance writers or build a team?
The decision between freelance writers and an in-house team depends on your goals, budget, and stage of growth.
Freelance writers offer flexibility. They’re ideal if you want to scale content production up or down, or don’t yet have the resources to support full-time hires. 
Experienced freelancers can plug into your existing workflow, making them a strong option for lean or growing brands.
An in-house team provides consistency, reliability, and deep brand knowledge. Full-time writers have the time to learn your brand voice, products, and audience in great detail. 
This can be valuable for businesses that produce a lot of content or work in complex niches. The tradeoff, of course, is higher overhead, longer hiring timelines, and more responsibility.
For many businesses, the best solution is a hybrid model: a small internal team that owns editorial standards, supported by freelance writers who help scale production. 
Ultimately, it’s all about building a content system that aligns with your resources and fits your business’s stage.
Dig deeper: 5 SEO content pitfalls that could be hurting your traffic
Struggle 6: Is ‘great content’ worth the investment?
Optimized content is like anything else – you get out of it what you put into it.
If you hire top-quality writers, you’re going to get top-quality content, which in turn will help drive traffic and better rankings for your site.
So yes, it’s worth the investment in high-quality content because the benefits compound over time.
A well-researched, well-written piece can attract qualified visitors for months (or even years) after it’s published. It can also build trust with your audience, leading to even more sales over time. 
Great content also supports the entire customer journey. It answers questions, addresses objections, and positions your brand as credible long before a prospect actually decides to buy. 
A great writer helps you bring in the right traffic. And that’s worth every penny.
Great writers come from clear standards, not lucky hires
Finding great content writers is less about discovering a hidden talent pool and more about setting clear standards. 
When you know what quality looks like, where to look and how to support writers once they’re hired, the process becomes far more predictable – and far less frustrating.
The most successful content programs treat writing as a long-term investment, not a one-off transaction. 
By pairing strong writers with clear expectations, fair compensation and repeatable processes, brands can build content engines that consistently deliver value over time.

You get what you pay for in content. Here’s how to find great writers in 2026, from job boards to LinkedIn and beyond.

How to find great writers (and other content marketing struggles)

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/01/Why-AI-makes-agency-client-relationships-matter-more-than-ever.jpg" class="attachment-large size-large wp-post-image" alt="Why AI makes agency-client relationships matter more than ever" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/Why-AI-makes-agency-client-relationships-matter-more-than-ever.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/01/Why-AI-makes-agency-client-relationships-matter-more-than-ever-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/01/Why-AI-makes-agency-client-relationships-matter-more-than-ever-1536x864.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>AI may optimize PPC, but it can’t replace empathy, listening, or trust. Four relationship fundamentals still set agencies apart.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/01/Why-AI-makes-agency-client-relationships-matter-more-than-ever.jpg" class="attachment-large size-large wp-post-image" alt="Why AI makes agency-client relationships matter more than ever" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/Why-AI-makes-agency-client-relationships-matter-more-than-ever.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/01/Why-AI-makes-agency-client-relationships-matter-more-than-ever-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/01/Why-AI-makes-agency-client-relationships-matter-more-than-ever-1536x864.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Working as an office manager in my early 20s, I read Dale Carnegie’s &#8220;How to Win Friends and Influence People.&#8221; </p>



<p>Many of its principles still hold true today, and they guided me through multiple career transitions. Success in most careers comes from our interactions with people – whether clients or coworkers.</p>



<p>For years, those principles of human connection, combined with technical knowledge and expertise, helped digital marketers succeed. </p>



<p>Agencies made sense of the machines for clients, and strong relationship-building allowed them to retain those clients over time. That model is now being challenged. </p>



<p>As AI has become fully embedded in <a href="https://searchengineland.com/guide/what-is-paid-search">PPC</a> platforms, the question has become unavoidable: what prevents clients from relying on an entirely AI-built approach?</p>



<p>What agencies have that AI can’t duplicate is their relational side – the ability to connect with others and understand, strategically, what business owners are actually after.</p>



<h2 class="wp-block-heading" id="h-1-ask-questions">1. Ask questions</h2>



<p>The key to discovering who people are and what makes them tick is to ask. </p>



<p>Sounds simple, really, but so much of communication gets lost in translation or is left up to assumption.&nbsp;</p>



<p>When I go into a sales call, I bring a list of questions. How much can we find out about this potential client in this half-hour window? </p>



<p>Likewise, when I conduct a strategy call, I have a list of questions: some for me and some for them. </p>



<p>What is this potential client looking to accomplish? What about their current strategy is or is not working? How can we improve upon this strategy?&nbsp;</p>



<p>AI can’t do this yet. Our interactions with it are primarily one-sided (at least at the time of this writing). </p>



<p>We may be able to have a conversation with it, but AI is never the initiator. We go to AI asking it what it can do for us using ideas we already have. </p>



<p>AI is not interested in who we are as people or in sussing out our specific pain points.</p>



<p>We can never discover a new pain point without asking, and we also can never find it out if we don’t listen, which brings me to the next point.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/build-ppc-client-relationships-tips-436315">6 tips to build PPC client relationships</a></em></strong></p>



<h2 class="wp-block-heading" id="h-2-talk-less-listen-more">2. Talk less, listen more</h2>



<p>How often do we find ourselves in conversations with others, only waiting for the silence so we can interject with our own thoughts? </p>



<p>I&#8217;m guilty of this. I’ve also found that clients and client prospects really just want to be heard. </p>



<p>So, let them explain themselves, then ask them more clarifying questions, and let them talk more. Continue to listen.&nbsp;</p>



<p>It’s amazing what you can find out about a person if you go into a call with absolutely no agenda beyond learning about the other person. </p>



<p>Let them continue to talk, do not interject, and see what you are able to find out. </p>



<p>Try not to fill the silence unless it becomes uncomfortable and you, yourself, have agenda items to cover based on what you’ve learned.&nbsp;</p>



<p>I find this type of approach is usually easier to do in sales calls. </p>



<p>Typically, we go into these thinking we need to prove ourselves and our abilities, but if it is the first call, we ideally want to find out what they are seeking and spend as much time as possible getting them to discuss that goal.&nbsp;</p>



<p>Using this approach with an existing client, I find it most beneficial to hear their nuances, strategy pushes, and ideas. </p>



<p>These assist with collaboration and generate ideas more quickly than anything I can say on the call. </p>



<p>This approach also builds agreement with the client, which is another important foundational building block of relationships.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/new-ppc-client-questions-445138">8 questions to ask your new PPC clients</a></em></strong></p>



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<h2 class="wp-block-heading" id="h-3-find-common-ground">3. Find common ground</h2>



<p>If I can, I always like to find commonalities between myself and anyone new I meet. </p>



<p>Building on these commonalities creates rapport and supports personal and professional relationships.&nbsp;</p>



<p>And, regardless of whether the person you are communicating with is a friend or colleague, be personal and specific in your conversations. </p>



<p>I’ve always enjoyed remembering things about people and following up on those things in our conversations together. </p>



<p>People like to be remembered, and they enjoy it when someone values what they have to say.&nbsp;</p>



<p>Memory is a facet that AI is just starting to develop.</p>



<p>However, finding commonalities and shared experiences with another person will never (hopefully) be rendered obsolete by artificial intelligence.&nbsp;</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/fire-ppc-clients-when-how-446916">When and how to fire PPC clients</a></em></strong></p>



<h2 class="wp-block-heading" id="h-4-smile-be-less-serious-when-it-s-appropriate">4. Smile, be less serious (when it’s appropriate)</h2>



<p>In the ever-changing world of marketing, it’s easy to fall into an all-serious, never-ending analytical cycle of data observation and testing. </p>



<p>However, we also have to remember not to take ourselves too seriously. After all, this career is still relatively new, and who knows what it will look like in the next five years.&nbsp;</p>



<p>Consider why you got into this occupation in the first place. I think we all have an innate desire to help people and connect with them – at least I hope so. </p>



<p>So, let’s connect with others by allowing ourselves to be less serious when we can be and throw in the awkward joke when applicable. </p>



<p>We are humans, too, and it’s important for the people we work for to see this. It’s important in any relationship.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/set-manage-ppc-expectations-teams-stakeholders-439715">How to set and manage PPC expectations for teams and stakeholders</a></em></strong></p>



<h2 class="wp-block-heading" id="h-what-differentiates-a-partner-from-an-algorithm">What differentiates a partner from an algorithm</h2>



<p>In a world increasingly dominated by AI, the balance between technical expertise and human connection is shifting. </p>



<p>While AI excels at data, analysis, and optimization – and can offer advice at all hours of the day – knowledge and specialization alone are no longer enough.</p>



<p>What AI cannot replicate is empathy, shared experience, or genuine rapport. </p>



<p>Over time, those principles of human connection, paired with technical knowledge, helped agencies translate machines for clients and build long-term relationships.</p>



<p>By returning to the basics – asking thoughtful questions, practicing active listening, finding common ground, and connecting on a human level – agencies can secure their value. </p>



<p>These relational skills are what differentiate a partner from an algorithm, ensuring that agency work remains not just important, but indispensable.</p>

Working as an office manager in my early 20s, I read Dale Carnegie’s “How to Win Friends and Influence People.” 
Many of its principles still hold true today, and they guided me through multiple career transitions. Success in most careers comes from our interactions with people – whether clients or coworkers.
For years, those principles of human connection, combined with technical knowledge and expertise, helped digital marketers succeed. 
Agencies made sense of the machines for clients, and strong relationship-building allowed them to retain those clients over time. That model is now being challenged. 
As AI has become fully embedded in PPC platforms, the question has become unavoidable: what prevents clients from relying on an entirely AI-built approach?
What agencies have that AI can’t duplicate is their relational side – the ability to connect with others and understand, strategically, what business owners are actually after.
1. Ask questions
The key to discovering who people are and what makes them tick is to ask. 
Sounds simple, really, but so much of communication gets lost in translation or is left up to assumption. 
When I go into a sales call, I bring a list of questions. How much can we find out about this potential client in this half-hour window? 
Likewise, when I conduct a strategy call, I have a list of questions: some for me and some for them. 
What is this potential client looking to accomplish? What about their current strategy is or is not working? How can we improve upon this strategy? 
AI can’t do this yet. Our interactions with it are primarily one-sided (at least at the time of this writing). 
We may be able to have a conversation with it, but AI is never the initiator. We go to AI asking it what it can do for us using ideas we already have. 
AI is not interested in who we are as people or in sussing out our specific pain points.
We can never discover a new pain point without asking, and we also can never find it out if we don’t listen, which brings me to the next point.
Dig deeper: 6 tips to build PPC client relationships
2. Talk less, listen more
How often do we find ourselves in conversations with others, only waiting for the silence so we can interject with our own thoughts? 
I’m guilty of this. I’ve also found that clients and client prospects really just want to be heard. 
So, let them explain themselves, then ask them more clarifying questions, and let them talk more. Continue to listen. 
It’s amazing what you can find out about a person if you go into a call with absolutely no agenda beyond learning about the other person. 
Let them continue to talk, do not interject, and see what you are able to find out. 
Try not to fill the silence unless it becomes uncomfortable and you, yourself, have agenda items to cover based on what you’ve learned. 
I find this type of approach is usually easier to do in sales calls. 
Typically, we go into these thinking we need to prove ourselves and our abilities, but if it is the first call, we ideally want to find out what they are seeking and spend as much time as possible getting them to discuss that goal. 
Using this approach with an existing client, I find it most beneficial to hear their nuances, strategy pushes, and ideas. 
These assist with collaboration and generate ideas more quickly than anything I can say on the call. 
This approach also builds agreement with the client, which is another important foundational building block of relationships.
Dig deeper: 8 questions to ask your new PPC clients
Get the newsletter search marketers rely on.
  
				
								
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See terms.
3. Find common ground
If I can, I always like to find commonalities between myself and anyone new I meet. 
Building on these commonalities creates rapport and supports personal and professional relationships. 
And, regardless of whether the person you are communicating with is a friend or colleague, be personal and specific in your conversations. 
I’ve always enjoyed remembering things about people and following up on those things in our conversations together. 
People like to be remembered, and they enjoy it when someone values what they have to say. 
Memory is a facet that AI is just starting to develop.
However, finding commonalities and shared experiences with another person will never (hopefully) be rendered obsolete by artificial intelligence. 
Dig deeper: When and how to fire PPC clients
4. Smile, be less serious (when it’s appropriate)
In the ever-changing world of marketing, it’s easy to fall into an all-serious, never-ending analytical cycle of data observation and testing. 
However, we also have to remember not to take ourselves too seriously. After all, this career is still relatively new, and who knows what it will look like in the next five years. 
Consider why you got into this occupation in the first place. I think we all have an innate desire to help people and connect with them – at least I hope so. 
So, let’s connect with others by allowing ourselves to be less serious when we can be and throw in the awkward joke when applicable. 
We are humans, too, and it’s important for the people we work for to see this. It’s important in any relationship.
Dig deeper: How to set and manage PPC expectations for teams and stakeholders
What differentiates a partner from an algorithm
In a world increasingly dominated by AI, the balance between technical expertise and human connection is shifting. 
While AI excels at data, analysis, and optimization – and can offer advice at all hours of the day – knowledge and specialization alone are no longer enough.
What AI cannot replicate is empathy, shared experience, or genuine rapport. 
Over time, those principles of human connection, paired with technical knowledge, helped agencies translate machines for clients and build long-term relationships.
By returning to the basics – asking thoughtful questions, practicing active listening, finding common ground, and connecting on a human level – agencies can secure their value. 
These relational skills are what differentiate a partner from an algorithm, ensuring that agency work remains not just important, but indispensable.

AI may optimize PPC, but it can’t replace empathy, listening, or trust. Four relationship fundamentals still set agencies apart.

Why AI makes agency-client relationships matter more than ever

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/01/ai-visibility-gap.png" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/ai-visibility-gap.png 1920w, https://searchengineland.com/wp-content/seloads/2026/01/ai-visibility-gap-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/01/ai-visibility-gap-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Data shows AI assistants recommend only 1% to 11% of locations, revealing a massive gap between Google rankings and AI visibility.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/01/ai-visibility-gap.png" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/ai-visibility-gap.png 1920w, https://searchengineland.com/wp-content/seloads/2026/01/ai-visibility-gap-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/01/ai-visibility-gap-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Most brands performing well in traditional local search fail to appear in results from ChatGPT, Gemini, and Perplexity, according to SOCi’s newly released 2026 local visibility index.</p>



<ul class="wp-block-list">
<li>Also of note: business profile information was only about 68% accurate on ChatGPT and Perplexity, compared with 100% accuracy on Gemini, which is grounded in Google Maps. </li>
</ul>



<p><strong>AI limits local visibility</strong>. Performance data from nearly 350,000 locations across 2,751 multi-location brands was analyzed to measure how often locations are surfaced or recommended by AI assistants. Turns out, AI platforms are far more selective than Google’s local results:</p>



<ul class="wp-block-list">
<li>1.2% of locations were recommended by ChatGPT, 11% by Gemini, and 7.4% by Perplexity. </li>



<li>By comparison, brands appeared in Google’s local 3-pack 35.9% of the time. </li>



<li>AI visibility is three to 30 times harder to achieve than ranking well in traditional local search, SOCi estimated.</li>
</ul>



<p><strong>AI and Google visibility differ</strong>. Across industries, fewer than half of the brands that lead in Google local visibility also appear among the most visible brands in AI results. </p>



<ul class="wp-block-list">
<li>In retail, only 45% of the top 20 brands by traditional local search visibility overlapped with the top 20 brands most frequently recommended by AI.</li>
</ul>



<p><strong>Why we care</strong>. Strong Google local rankings don&#8217;t guarantee visibility in AI-powered recommendations. Your brand’s data, reputation, and content must be consistent across the wider ecosystem that AI systems rely on (Google Maps, Yelp, Facebook, brand websites, and other trusted sources). They filter aggressively and favor locations with accurate data, strong sentiment, and clear differentiation. That&#8217;s a big shift – from optimization to qualification.</p>



<p><strong>AI favors higher-rated businesses</strong>. AI recommendations consistently favor businesses with above-average sentiment, treating reviews as a filter rather than a ranking signal.</p>



<ul class="wp-block-list">
<li>Locations recommended by ChatGPT averaged 4.3 stars, compared with 3.9 stars on Gemini and 4.1 stars on Perplexity, according to SOCi.</li>



<li>In traditional local search, businesses with average or even middling ratings can still rank based on proximity and category relevance. In AI-driven results, SOCi found those same locations are frequently excluded altogether, as AI systems prioritize confidence and risk reduction over breadth.</li>
</ul>



<p><strong><strong>Impact varies by industry</strong>.</strong> AI visibility thresholds differ sharply by sector:</p>



<ul class="wp-block-list">
<li><strong>Retail:</strong> Fewer than half of top-ranked local search brands (45%) carried over into AI recommendations. Sam’s Club and Aldi exceeded expectations, while Target and Batteries Plus Bulbs slipped. The gap shows that AI favors consistent, trusted signals across platforms.</li>



<li><strong>Restaurants:</strong> Visibility is concentrated among a small group of leaders. Culver’s beat category benchmarks, reaching AI recommendation rates of 30.0% on ChatGPT and 45.8% on Gemini. Strong ratings and complete profiles drove this performance. Brands with weaker data and sentiment often failed to appear in AI recommendations at all.</li>



<li><strong>Financial services:</strong> After improving profile coverage, ratings, and data accuracy, Liberty Tax achieved 68.3% visibility in Google’s local 3-pack and was recommended 19.2% of the time on Gemini and 26.9% on Perplexity, well above category benchmarks.
<ul class="wp-block-list">
<li>Underperforming financial brands with low profile accuracy, average ratings near 3.4 stars, and review response rates below 5% were effectively invisible in AI recommendations. Weak fundamentals now translate directly into zero AI visibility, SOCi found.</li>
</ul>
</li>
</ul>



<p><strong>The report.</strong> <a href="https://www.soci.ai/insights/lvi/" target="_blank" rel="noopener">The 2026 Local Visibility Index</a> (registration required)</p>


Most brands performing well in traditional local search fail to appear in results from ChatGPT, Gemini, and Perplexity, according to SOCi’s newly released 2026 local visibility index.
Also of note: business profile information was only about 68% accurate on ChatGPT and Perplexity, compared with 100% accuracy on Gemini, which is grounded in Google Maps. 
AI limits local visibility. Performance data from nearly 350,000 locations across 2,751 multi-location brands was analyzed to measure how often locations are surfaced or recommended by AI assistants. Turns out, AI platforms are far more selective than Google’s local results:
1.2% of locations were recommended by ChatGPT, 11% by Gemini, and 7.4% by Perplexity. 
By comparison, brands appeared in Google’s local 3-pack 35.9% of the time. 
AI visibility is three to 30 times harder to achieve than ranking well in traditional local search, SOCi estimated.
AI and Google visibility differ. Across industries, fewer than half of the brands that lead in Google local visibility also appear among the most visible brands in AI results. 
In retail, only 45% of the top 20 brands by traditional local search visibility overlapped with the top 20 brands most frequently recommended by AI.
Why we care. Strong Google local rankings don’t guarantee visibility in AI-powered recommendations. Your brand’s data, reputation, and content must be consistent across the wider ecosystem that AI systems rely on (Google Maps, Yelp, Facebook, brand websites, and other trusted sources). They filter aggressively and favor locations with accurate data, strong sentiment, and clear differentiation. That’s a big shift – from optimization to qualification.
AI favors higher-rated businesses. AI recommendations consistently favor businesses with above-average sentiment, treating reviews as a filter rather than a ranking signal.
Locations recommended by ChatGPT averaged 4.3 stars, compared with 3.9 stars on Gemini and 4.1 stars on Perplexity, according to SOCi.
In traditional local search, businesses with average or even middling ratings can still rank based on proximity and category relevance. In AI-driven results, SOCi found those same locations are frequently excluded altogether, as AI systems prioritize confidence and risk reduction over breadth.
Impact varies by industry. AI visibility thresholds differ sharply by sector:
Retail: Fewer than half of top-ranked local search brands (45%) carried over into AI recommendations. Sam’s Club and Aldi exceeded expectations, while Target and Batteries Plus Bulbs slipped. The gap shows that AI favors consistent, trusted signals across platforms.
Restaurants: Visibility is concentrated among a small group of leaders. Culver’s beat category benchmarks, reaching AI recommendation rates of 30.0% on ChatGPT and 45.8% on Gemini. Strong ratings and complete profiles drove this performance. Brands with weaker data and sentiment often failed to appear in AI recommendations at all.
Financial services: After improving profile coverage, ratings, and data accuracy, Liberty Tax achieved 68.3% visibility in Google’s local 3-pack and was recommended 19.2% of the time on Gemini and 26.9% on Perplexity, well above category benchmarks.

Underperforming financial brands with low profile accuracy, average ratings near 3.4 stars, and review response rates below 5% were effectively invisible in AI recommendations. Weak fundamentals now translate directly into zero AI visibility, SOCi found.
The report. The 2026 Local Visibility Index (registration required)

Data shows AI assistants recommend only 1% to 11% of locations, revealing a massive gap between Google rankings and AI visibility.

AI local visibility is up to 30x harder than ranking in Google: Report

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/01/Inside-Metas-AI-driven-advertising-system-How-Andromeda-and-GEM-work-together.jpg" class="attachment-large size-large wp-post-image" alt="Inside Meta’s AI-driven advertising system: How Andromeda and GEM work together" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/Inside-Metas-AI-driven-advertising-system-How-Andromeda-and-GEM-work-together.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/01/Inside-Metas-AI-driven-advertising-system-How-Andromeda-and-GEM-work-together-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/01/Inside-Metas-AI-driven-advertising-system-How-Andromeda-and-GEM-work-together-1536x864.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Meta’s new subscriptions and AI features could change how users create, share, and engage with content, reshaping the signals advertisers rely on.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/01/Inside-Metas-AI-driven-advertising-system-How-Andromeda-and-GEM-work-together.jpg" class="attachment-large size-large wp-post-image" alt="Inside Meta’s AI-driven advertising system: How Andromeda and GEM work together" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/Inside-Metas-AI-driven-advertising-system-How-Andromeda-and-GEM-work-together.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/01/Inside-Metas-AI-driven-advertising-system-How-Andromeda-and-GEM-work-together-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/01/Inside-Metas-AI-driven-advertising-system-How-Andromeda-and-GEM-work-together-1536x864.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Meta tests paid subscriptions across Instagram, Facebook and WhatsApp to unlock premium features and AI across its apps.</p>



<p><strong>What is happening.</strong> Meta is testing new subscriptions that unlock exclusive features across Instagram, Facebook and WhatsApp, while keeping the core experiences free. Rather than a single bundle, Meta plans to experiment with different subscription models and feature sets tailored to each app, spanning productivity, creativity and expanded AI capabilities.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full is-resized"><img decoding="async" width="917" height="2048" src="https://searchengineland.com/wp-content/seloads/2026/01/1000051437-scaled.jpg" alt="" class="wp-image-468084" style="width:479px;height:auto" srcset="https://searchengineland.com/wp-content/seloads/2026/01/1000051437-scaled.jpg 917w, https://searchengineland.com/wp-content/seloads/2026/01/1000051437-768x1715.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/01/1000051437-688x1536.jpg 688w" sizes="(max-width: 917px) 100vw, 917px" /></figure></div>


<p>Subscriptions will introduce premium controls and tools for everyday users, creators and businesses — separate from Meta Verified. On Instagram, early tests could include unlimited audience lists, insights into non-followers, and stealth story viewing. </p>



<p>Meta also plans to roll out paid access to AI features, including expanded usage of its Vibes AI video generation tool under a freemium model.</p>



<p><strong>Why we care.</strong> Paid subscriptions could change how users interact with Meta’s apps, potentially shifting engagement, privacy settings, and audience visibility. New AI-powered creation tools and premium features may also influence the volume, quality, and formats of user-generated content advertisers compete with — or can tap into — for campaigns. Over time, subscription tiers could reshape targeting, measurement, and the value of organic vs. paid reach across Instagram, Facebook, and WhatsApp.</p>



<p><strong>Between the lines:</strong> AI is at the center of the strategy. Meta plans to scale Manus, the AI agent it acquired for a reported $2 billion, integrating it directly into its apps while also selling standalone subscriptions to businesses. Early reports say Manus shortcuts could appear inside Instagram, tightening the link between social engagement and AI-assisted creation.</p>



<p><strong>Why now</strong>. Advertising remains Meta’s core business, but subscriptions offer diversification at a time when users are increasingly willing to pay for differentiated social features — as shown by Snapchat+, which has grown to more than 16 million subscribers. Meta is betting it can replicate that success without overwhelming users already feeling subscription fatigue.</p>



<p><strong>The bottom line</strong>. Meta is testing whether premium social and AI features can unlock a new revenue stream beyond ads, but success will hinge on whether users see enough everyday value to justify yet another monthly subscription.</p>



<p><strong>Dig deeper.</strong> <a href="https://techcrunch.com/2026/01/26/meta-to-test-premium-subscriptions-on-instagram-facebook-and-whatsapp/">Meta to test premium subscriptions on Instagram, Facebook, and WhatsApp</a></p>


Meta tests paid subscriptions across Instagram, Facebook and WhatsApp to unlock premium features and AI across its apps.
What is happening. Meta is testing new subscriptions that unlock exclusive features across Instagram, Facebook and WhatsApp, while keeping the core experiences free. Rather than a single bundle, Meta plans to experiment with different subscription models and feature sets tailored to each app, spanning productivity, creativity and expanded AI capabilities.

Subscriptions will introduce premium controls and tools for everyday users, creators and businesses — separate from Meta Verified. On Instagram, early tests could include unlimited audience lists, insights into non-followers, and stealth story viewing. 
Meta also plans to roll out paid access to AI features, including expanded usage of its Vibes AI video generation tool under a freemium model.
Why we care. Paid subscriptions could change how users interact with Meta’s apps, potentially shifting engagement, privacy settings, and audience visibility. New AI-powered creation tools and premium features may also influence the volume, quality, and formats of user-generated content advertisers compete with — or can tap into — for campaigns. Over time, subscription tiers could reshape targeting, measurement, and the value of organic vs. paid reach across Instagram, Facebook, and WhatsApp.
Between the lines: AI is at the center of the strategy. Meta plans to scale Manus, the AI agent it acquired for a reported $2 billion, integrating it directly into its apps while also selling standalone subscriptions to businesses. Early reports say Manus shortcuts could appear inside Instagram, tightening the link between social engagement and AI-assisted creation.
Why now. Advertising remains Meta’s core business, but subscriptions offer diversification at a time when users are increasingly willing to pay for differentiated social features — as shown by Snapchat+, which has grown to more than 16 million subscribers. Meta is betting it can replicate that success without overwhelming users already feeling subscription fatigue.
The bottom line. Meta is testing whether premium social and AI features can unlock a new revenue stream beyond ads, but success will hinge on whether users see enough everyday value to justify yet another monthly subscription.
Dig deeper. Meta to test premium subscriptions on Instagram, Facebook, and WhatsApp

Meta’s new subscriptions and AI features could change how users create, share, and engage with content, reshaping the signals advertisers rely on.

Meta tests paid subscriptions

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/01/ai-same-question-different-answers.png" class="attachment-large size-large wp-post-image" alt="AI same question, different answers" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/ai-same-question-different-answers.png 1920w, https://searchengineland.com/wp-content/seloads/2026/01/ai-same-question-different-answers-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/01/ai-same-question-different-answers-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>AI recommendations vary widely, even when prompts are identical. New data shows intent is consistent, but position tracking is mostly noise.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/01/ai-same-question-different-answers.png" class="attachment-large size-large wp-post-image" alt="AI same question, different answers" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/ai-same-question-different-answers.png 1920w, https://searchengineland.com/wp-content/seloads/2026/01/ai-same-question-different-answers-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/01/ai-same-question-different-answers-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>When ChatGPT, Claude, or Google’s AI get asked for brand or product recommendations, they almost never return the same list twice — and almost never in the same order.</p>



<p>That’s the big finding from a new study from Rand Fishkin, CEO and co-founder of SparkToro, and Patrick O’Donnell, CTO and co-founder of Gumshoe.ai. They investigated whether generative AI recommendations are sufficiently consistent to be measured.</p>



<p><strong>What they tested.</strong> Six hundred volunteers ran 12 identical prompts through ChatGPT, Claude, and Google’s AI nearly 3,000 times.</p>



<ul class="wp-block-list">
<li>Each response was normalized into an ordered list of brands or products. The team then compared those lists for overlap, order, and repetition.</li>



<li>The goal was to see how often the same answers actually appeared.</li>
</ul>



<p><strong>The short answer: almost never.</strong> Across tools and prompts, the odds of getting the same list twice were under 1 in 100. The odds of getting the same list in the same order were closer to 1 in 1,000.</p>



<ul class="wp-block-list">
<li>Even list length varied wildly. Some responses named two or three options. Others named 10 or more.</li>



<li>If you don’t like the result, the data suggests a simple fix: ask again.</li>
</ul>



<figure class="wp-block-image size-full"><img decoding="async" width="1280" height="720" src="https://searchengineland.com/wp-content/seloads/2026/01/ai-tool-response-consistency-lists-of-brands.webp" alt="" class="wp-image-468079" srcset="https://searchengineland.com/wp-content/seloads/2026/01/ai-tool-response-consistency-lists-of-brands.webp 1280w, https://searchengineland.com/wp-content/seloads/2026/01/ai-tool-response-consistency-lists-of-brands-768x432.webp 768w" sizes="(max-width: 1280px) 100vw, 1280px" /></figure>



<p><strong>Why we care.</strong> We’ve heard that personalization drives AI answers. This is the first research that puts real numbers behind that claim — and the implications are massive. If you’re looking for a concrete way SEO and GEO diverge, this is it.</p>



<p><strong>Random by design.</strong> This isn’t a flaw. It’s how these systems work.</p>



<ul class="wp-block-list">
<li>Large language models are probability engines. They’re designed to generate variation, not to return a stable, ordered set of results.</li>



<li>Treating them like Google’s blue links misses the point and produces bad metrics.</li>
</ul>



<p><strong>One thing that works.</strong> While rankings collapsed under scrutiny, one metric held up better than expected: visibility percentage.</p>



<ul class="wp-block-list">
<li>Some brands appeared again and again across dozens of runs, even though their position jumped around. In some cases — hospitals, agencies, consumer brands — names showed up in 60% to 90% of responses for a given intent.</li>



<li>Repeat presence means something. Exact rank does not.</li>
</ul>



<p><strong>Size matters.</strong> The smaller the market, the more stable the results.</p>



<ul class="wp-block-list">
<li>In tight spaces — like regional service providers or niche B2B tools — AI answers clustered around a few familiar names. In massive categories — like novels or creative agencies — results scattered into chaos.</li>



<li>More options create more randomness.</li>
</ul>



<p><strong>Prompts are chaos.</strong> The team also tested real human prompts, and they were a mess — in a very human way.</p>



<ul class="wp-block-list">
<li>Almost no two prompts looked alike, even when people wanted the same thing. Semantic similarity was extremely low.</li>



<li>Here’s the surprise: despite wildly different phrasing, AI tools still returned similar brand sets for the same underlying intent.</li>
</ul>



<p><strong>Intent survives.</strong> For headphone recommendations, hundreds of unique prompts still surfaced leaders like Bose, Sony, Apple, and Sennheiser most of the time.</p>



<ul class="wp-block-list">
<li>Change the intent — gaming, podcasting, noise canceling — and the brand set changed with it.</li>



<li>That suggests AI tools do capture intent, even when prompts are strange.</li>
</ul>



<p><strong>What’s useless.</strong> Tracking “position” in AI answers.</p>



<ul class="wp-block-list">
<li>The study is blunt: ranking positions are so unstable they’re effectively meaningless. Any product selling AI rank movement is selling fiction.</li>
</ul>



<p><strong>What might work.</strong> Track how often your brand appears across many prompts, run many times. It’s imperfect. It’s messy. But it’s closer to reality than pretending AI answers behave like search rankings.</p>



<p><strong>Open questions.</strong> Fishkin points to gaps that still need answers.</p>



<ul class="wp-block-list">
<li>How many runs are needed to make visibility numbers reliable? </li>



<li>Do APIs behave like real users? </li>



<li>How many prompts accurately represent a market?</li>
</ul>



<p><strong>Bottom line.</strong> AI recommendation lists are inherently random. Visibility — measured carefully and at scale — may still tell you something real. Just don’t confuse it with ranking.</p>



<p>The report. <a href="https://sparktoro.com/blog/new-research-ais-are-highly-inconsistent-when-recommending-brands-or-products-marketers-should-take-care-when-tracking-ai-visibility/" target="_blank" rel="noopener">NEW Research: AIs are highly inconsistent when recommending brands or products; marketers should take care when tracking AI visibility</a></p>


When ChatGPT, Claude, or Google’s AI get asked for brand or product recommendations, they almost never return the same list twice — and almost never in the same order.
That’s the big finding from a new study from Rand Fishkin, CEO and co-founder of SparkToro, and Patrick O’Donnell, CTO and co-founder of Gumshoe.ai. They investigated whether generative AI recommendations are sufficiently consistent to be measured.
What they tested. Six hundred volunteers ran 12 identical prompts through ChatGPT, Claude, and Google’s AI nearly 3,000 times.
Each response was normalized into an ordered list of brands or products. The team then compared those lists for overlap, order, and repetition.
The goal was to see how often the same answers actually appeared.
The short answer: almost never. Across tools and prompts, the odds of getting the same list twice were under 1 in 100. The odds of getting the same list in the same order were closer to 1 in 1,000.
Even list length varied wildly. Some responses named two or three options. Others named 10 or more.
If you don’t like the result, the data suggests a simple fix: ask again.




Why we care. We’ve heard that personalization drives AI answers. This is the first research that puts real numbers behind that claim — and the implications are massive. If you’re looking for a concrete way SEO and GEO diverge, this is it.
Random by design. This isn’t a flaw. It’s how these systems work.
Large language models are probability engines. They’re designed to generate variation, not to return a stable, ordered set of results.
Treating them like Google’s blue links misses the point and produces bad metrics.
One thing that works. While rankings collapsed under scrutiny, one metric held up better than expected: visibility percentage.
Some brands appeared again and again across dozens of runs, even though their position jumped around. In some cases — hospitals, agencies, consumer brands — names showed up in 60% to 90% of responses for a given intent.
Repeat presence means something. Exact rank does not.
Size matters. The smaller the market, the more stable the results.
In tight spaces — like regional service providers or niche B2B tools — AI answers clustered around a few familiar names. In massive categories — like novels or creative agencies — results scattered into chaos.
More options create more randomness.
Prompts are chaos. The team also tested real human prompts, and they were a mess — in a very human way.
Almost no two prompts looked alike, even when people wanted the same thing. Semantic similarity was extremely low.
Here’s the surprise: despite wildly different phrasing, AI tools still returned similar brand sets for the same underlying intent.
Intent survives. For headphone recommendations, hundreds of unique prompts still surfaced leaders like Bose, Sony, Apple, and Sennheiser most of the time.
Change the intent — gaming, podcasting, noise canceling — and the brand set changed with it.
That suggests AI tools do capture intent, even when prompts are strange.
What’s useless. Tracking “position” in AI answers.
The study is blunt: ranking positions are so unstable they’re effectively meaningless. Any product selling AI rank movement is selling fiction.
What might work. Track how often your brand appears across many prompts, run many times. It’s imperfect. It’s messy. But it’s closer to reality than pretending AI answers behave like search rankings.
Open questions. Fishkin points to gaps that still need answers.
How many runs are needed to make visibility numbers reliable? 
Do APIs behave like real users? 
How many prompts accurately represent a market?
Bottom line. AI recommendation lists are inherently random. Visibility — measured carefully and at scale — may still tell you something real. Just don’t confuse it with ranking.
The report. NEW Research: AIs are highly inconsistent when recommending brands or products; marketers should take care when tracking AI visibility

AI recommendations vary widely, even when prompts are identical. New data shows intent is consistent, but position tracking is mostly noise.

AI recommendation lists repeat less than 1% of the time: Study

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/01/Top-SEO-voices-on-AI-search-in-2026-7-shifts-redefining-visibility.png" class="attachment-large size-large wp-post-image" alt="Top SEO voices on AI search in 2026- 7 shifts redefining visibility" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/Top-SEO-voices-on-AI-search-in-2026-7-shifts-redefining-visibility.png 1920w, https://searchengineland.com/wp-content/seloads/2026/01/Top-SEO-voices-on-AI-search-in-2026-7-shifts-redefining-visibility-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/01/Top-SEO-voices-on-AI-search-in-2026-7-shifts-redefining-visibility-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>AI search now handles discovery, decisioning, and transactions. Here’s what that means for SEO strategy in 2026.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/01/Top-SEO-voices-on-AI-search-in-2026-7-shifts-redefining-visibility.png" class="attachment-large size-large wp-post-image" alt="Top SEO voices on AI search in 2026- 7 shifts redefining visibility" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/Top-SEO-voices-on-AI-search-in-2026-7-shifts-redefining-visibility.png 1920w, https://searchengineland.com/wp-content/seloads/2026/01/Top-SEO-voices-on-AI-search-in-2026-7-shifts-redefining-visibility-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/01/Top-SEO-voices-on-AI-search-in-2026-7-shifts-redefining-visibility-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>The search landscape, today’s buyer journey, and the roadmap to digital success aren’t just shifting. They’re being structurally reimagined.</p>



<p>To make sense of this shift, I spoke with six of the <a href="https://searchengineland.com/guide/what-is-seo">SEO</a> industry’s most forward-thinking voices and distilled their perspectives into seven core predictions for 2026.</p>



<p>What follows is a series of insights into how search is being structurally reimagined.</p>



<h2 class="wp-block-heading" id="h-1-the-rise-of-agentic-commerce">1. The rise of agentic commerce</h2>



<p>We are moving past the era of AI as an answer engine and into the era of <a href="https://blog.google/products/ads-commerce/agentic-commerce-ai-tools-protocol-retailers-platforms/">AI as an executive assistant</a>.</p>



<p>&#8220;Agentic web&#8221; means AI won&#8217;t just tell you which running shoes are best. It will actually find your size, apply a coupon, and execute the checkout.&nbsp;</p>



<p>For SEOs, this means optimizing for clicks is no longer the ceiling. We must optimize for machine readability and API compatibility.&nbsp;</p>



<p>If an agent can’t parse your inventory or price in real-time, you won&#8217;t exist in this new transaction layer.<br><br><a href="https://searchengineland.com/author/jim-yu">Jim Yu</a>, CEO of BrightEdge, stressed the importance of agentic preparation:</p>



<ul class="wp-block-list">
<li>“We’re already seeing a massive rise in agentic crawlers – AI that searches and acts on behalf of users. Brands need to prepare now with structured data, clear content hierarchy, and machine-readable information. The winners will be the ones who can measure AI agent behavior and understand how they’re being discovered and recommended.”</li>
</ul>



<p>Yu elaborated, noting that we’re entering a new market maturity phase.</p>



<ul class="wp-block-list">
<li>“AI search will take the next steps to becoming a real marketplace. The LLMs will expand paid advertising and other paid partnership opportunities. With that will come increased transparency and insights into how people are using LLMs within customer journeys. AI search will move from something that is coming to something that is here and having a major impact. 2026 will be the year that brands solidify the measurement frameworks to understand and respond to that impact.”</li>
</ul>



<p><a href="https://www.linkedin.com/in/samanyougarg" type="link" id="https://www.linkedin.com/in/samanyougarg" target="_blank" rel="noopener">Samanyou Garg</a>, founder and CEO at Writesonic, predicted that the agentic web will move users from the discovery phase directly to the transaction phase within a single AI conversation:</p>



<ul class="wp-block-list">
<li>“810 million people use ChatGPT daily. Google AI Overviews hit 1.5 billion monthly users. The debate about whether AI search matters is over. What’s changing in 2026: AI stops recommending and starts buying.&nbsp; The user never leaves the conversation.&nbsp; OpenAI open-sourced their Agentic Commerce Protocol. Shopify merchants enable checkout with one line of code.&nbsp; Amazon saw this coming.”</li>
</ul>



<p><a href="https://searchengineland.com/author/crystal-carter">Crystal Carter</a>, head of AI search and SEO communications at Wix, warned that focusing solely on being found is no longer enough:</p>



<ul class="wp-block-list">
<li>&#8220;The future of AI search is optimizing for the AI agents. In the last six months, we’ve seen new protocols for agentic payments, agentic shopping, and agent-to-agent frameworks. These each change the paradigm of the marketing funnel significantly by adding an AI decision gatekeeper into the mix.&#8221;</li>



<li>&#8220;I think many search professionals are focusing wholly on being found in classic search or AI surfaces, but ignoring the agentic opportunity is a mistake. SEO and GEO are, of course, valuable, but the agentic layer removes the user from much of the funnel. The so-called messy middle is now managed by AI. If you don’t build for compliance, then you’re not even in the game.&#8221;</li>
</ul>



<p><strong>Key takeaway:</strong> If your product, pricing, and availability data is not machine-readable in real time, AI agents will skip you and favor competitors.</p>



<h2 class="wp-block-heading" id="h-2-ai-ads-will-expand-with-deeper-integration-nbsp">2. AI ads will expand with deeper integration&nbsp;</h2>



<p>As AI platforms mature, <a href="https://searchengineland.com/openai-moves-on-chatgpt-ads-with-impression-based-launch-467783">monetization through ads</a> is following suit.&nbsp;</p>



<p>Today, monetization has moved upstream into the generative process itself.&nbsp;</p>



<p>Whether it’s a sponsored product recommendation within a ChatGPT shopping thread or a paid citation in a Google AI Overview, the ad unit has become conversational.</p>



<p>Yu&#8217;s<strong> </strong>prediction:&nbsp;</p>



<ul class="wp-block-list">
<li>“AI responses are now behind every door in the Google SERP – People Also Ask, Maps, Shopping, and more. YouTube is a prime example: one of the most cited sources in AI search and already a monetization powerhouse. Expect more intuitive ad integration within these AI experiences in 2026, which reinforces why brands need to optimize once and win everywhere.”</li>
</ul>



<p>Garg noted that while AI ad targeting is limited, establishing organic dominance now matters before auctions open:</p>



<ul class="wp-block-list">
<li>“Ads are coming, but the window is now. Google runs ads in AI Overviews across 12 countries, and they’re testing in AI Mode. But brands can’t target these placements yet. Google picks who shows up. Perplexity launched sponsored questions, then paused&#8230; ChatGPT shopping is ‘organic and unsponsored’ today. Their CFO says ads are coming. Same pattern as early Google. Organic visibility now means dominant position when the auction opens.”</li>
</ul>



<p><strong>Key takeaway: </strong>Paid visibility will shift from “buying clicks” to “buying inclusion,” and brands that are not already eligible and trusted will pay more and win less.</p>



<h2 class="wp-block-heading" id="h-3-the-best-seos-ship-tools-not-tasks">3. The best SEOs ship tools, not tasks</h2>



<p>The barrier between having a marketing idea and building a marketing tool has evaporated.&nbsp;</p>



<p>In 2026, the most successful SEO teams will look less like writers and more like product engineers, with efficiency becoming a competitive advantage.</p>



<p>Garg argued that this year marks the end of the visual workflow era, replaced by natural language tools that let non-technical marketers ship production-level code:</p>



<ul class="wp-block-list">
<li>&#8220;The old way: visual workflow builders. Drag nodes, connect arrows, take a three-week course to learn the platform. The new way: Claude Code and tools like it. Describe what you want in plain English. It writes the script, runs it, iterates.&#8221;</li>



<li>&#8220;Anthropic’s own growth team uses this daily. Process a CSV with hundreds of ads, identify underperformers, generate new variations. Minutes, not hours. They cut content audit time 75% and reduced costs 70% through intelligent model routing.&#8221;</li>



<li>&#8220;The gap between ‘I have an idea’ and ‘it’s running in production’ collapsed. 2026 is the year non-technical marketers start shipping like engineers.&#8221;</li>
</ul>



<p><strong>Key takeaway: </strong>Teams that automate repeatable digital marketing tasks will compound output and speed, while manual teams fall behind on both cost and time to impact.</p>



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<h2 class="wp-block-heading" id="h-4-personalization-and-specialization-will-keep-changing-the-optimization-game-nbsp">4. Personalization and specialization will keep changing the optimization game&nbsp;</h2>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="715" height="174" src="https://searchengineland.com/wp-content/seloads/2026/01/image-75.png" alt="Try without personalization" class="wp-image-468046"/></figure></div>


<p>In 2026, the concept of a traditional ranking may finally become obsolete.&nbsp;</p>



<p>If every search result is personalized in real time based on a user’s entire digital history, there is no “Position 1” anymore – there is only intent and relevance.<br><br>While Google and OpenAI dominate the headlines, the next frontier also includes specialization.&nbsp;</p>



<p>As users grow weary of hallucinations in general models, they will increasingly turn to AI platforms built for specific, high-stakes niches.&nbsp;</p>



<p>As a result, AI strategy can&#8217;t be mono-platform. Brands will need to optimize for a fragmented ecosystem of AI models that prioritize different data sources.</p>



<p><a href="https://searchengineland.com/author/michael-king">Mike King</a>, CEO of iPullRank, predicts the death of the generic SERP:</p>



<ul class="wp-block-list">
<li>“In 2026, personalization stops being a feature and becomes the operating system. Google’s Nested Learning work makes the direction obvious. Search systems are no longer learning just from queries. They are learning from you across multiple time horizons. Fast signals like session behavior and immediate intent sit on top of slower, more stable models of how you think, decide, trust, and revisit information over time.”</li>



<li>“The system is not adapting results. It is adapting itself to the user. The practical outcome is that two people asking the same question are no longer in the same information universe. They are getting different answers, different sources, and different levels of explanation based on how the system has learned to serve them without friction or failure. This quietly kills the idea of a single ranking, a single SERP, or a single ‘best page.’ If your content only works for a generic user, it works for no one.”</li>
</ul>



<p>But this shift is not limited to Google. As users seek more reliable, specialized answers, the search ecosystem continues to splinter across platforms and vertical-specific models.<br><br><strong>Key takeaway: </strong>Performance will vary by audience segment rather than a single SERP position, meaning brands can be invisible to high-value buyers even while overall rankings appear stable, creating hidden pipeline risk.</p>



<h2 class="wp-block-heading" id="h-5-seo-splits-humans-vs-agents">5. SEO splits: Humans vs. agents</h2>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="630" height="363" src="https://searchengineland.com/wp-content/seloads/2026/01/SEO-and-AI-search-overlap.png" alt="SEO and AI search overlap" class="wp-image-468044"/></figure></div>


<p>SEO and AI search will continue to fragment.&nbsp;</p>



<p>Historically, SEO had one goal: get the click. Sites were optimized so a human would discover a brand and land on a page.&nbsp;</p>



<p>In 2026, the industry is splitting into two distinct strategic problems.</p>



<ul class="wp-block-list">
<li>Traditional SEO, focused on humans who want to browse, compare, and buy.</li>



<li>AI search optimization, focused on supplying information so AI agents can find, trust, and use it without a user ever visiting the site.</li>
</ul>



<p>This is not just a technical update. It represents a fundamental shift in how success is measured.</p>



<p>King explained why treating these as the same strategic problem is a mistake:</p>



<ul class="wp-block-list">
<li>“Most people think AI search is just SEO evolving. There will be real tactical overlap for a while, and that is not the issue. The mistake is treating it as the same strategic problem. SEO is built around earning visibility that converts into clicks. AI search is built around supplying information that can be extracted, trusted, and reused without a click ever happening. They keep optimizing for rankings and traffic while the system is optimizing for reliability, composability, and downstream usefulness.”</li>



<li>“The work still matters. But the reason it matters has fundamentally changed, and most people have not caught up to that shift yet. We now live in a world where people form relationships with systems that listen, remember, adapt, and respond with context and continuity. That is not a search problem. That is a worldview shift.”</li>



<li>“In 2026, the biggest risk is not that SEO dies. It is that the people who should lead this moment choose to stay small, and the relevance engineers build the future without them.”</li>
</ul>



<p><a href="https://searchengineland.com/author/britney-muller">Britney Muller</a>, AI educator and consultant, cautioned that applying traditional SEO logic to AI citations is a strategic failure:</p>



<ul class="wp-block-list">
<li>“The biggest risk to our industry in 2026 isn’t AI; it’s that we’re trying to fit a baseball bat through a keyhole by applying SEO ranking logic to probabilistic systems.”</li>



<li>“You can’t ‘optimize’ an AI citation like a 2010 keyword. We have to pivot the conversation to what we can actually influence: showing up in the historical training data and winning the real-time RAG layer through fundamental SEO and brand mentions at scale.”</li>
</ul>



<p><strong>Key takeaway: </strong>In 2026, SEO becomes two jobs: driving clicks from humans and supplying clean, trusted inputs for AI agents that may never visit your site.&nbsp;</p>



<p>Measuring success only by rankings and sessions risks missing where revenue is actually influenced.</p>



<h2 class="wp-block-heading" id="h-6-proprietary-data-becomes-your-moat">6. Proprietary data becomes your moat</h2>



<p>Unique, proprietary, and human-driven content wins.&nbsp;</p>



<p>As the web becomes flooded with AI-generated material, the value of human experience and owned data continues to rise.&nbsp;</p>



<p>If an AI can easily synthesize your content without needing to cite you, the underlying value is likely interchangeable.&nbsp;</p>



<p>When brands own the data itself, however, attribution becomes unavoidable.</p>



<p>Muller highlighted that building unique, branded datasets is one of the strongest ways to secure AI attribution:</p>



<ul class="wp-block-list">
<li>“My big bet is on brands that start building entity moats … more strategically naming their data. When you own a unique metric, like the ‘[Brand] Index’ or the ‘[Brand] Score,’ you create a source of truth that AI models can’t just synthesize or ignore.”</li>



<li>“If they can’t replicate your data, they are forced to cite your name. Brands are also getting ahead by harvesting real-world stories and conversations highlighting things that AI cannot do.”</li>
</ul>



<p>Muller<strong> </strong>further shares:</p>



<ul class="wp-block-list">
<li>“Content marketers that will find an edge in 2026 will discover savvy ways of leveraging AI to analyze public datasets and then do something really cool and story-worthy with them.”</li>



<li>“Think about the one million hotel reviews that MonkeyLearn did … which used sentiment analysis to discover nuanced insights.”</li>
</ul>



<p><strong>Key takeaway: </strong>Commodity content becomes a cost center, while proprietary data and real experience become defensible assets that earn citations, trust, and inbound demand.</p>



<h2 class="wp-block-heading" id="h-7-ai-literacy-becomes-a-hiring-filter">7. AI literacy becomes a hiring filter</h2>



<p>AI adoption and training are critical.&nbsp;</p>



<p>The shift in 2026 is as much about people as it is about technology.&nbsp;</p>



<p>The era of AI novelty is over. Simply using ChatGPT is no longer a differentiator.&nbsp;</p>



<p>The competitive divide now depends on whether teams can move beyond basic content drafting and use AI as a strategic partner tied to real outcomes.</p>



<p>The leaders of 2026 will be those who successfully connect AI usage to key performance indicators.</p>



<p>Neil Patel, CEO and co-founder of NP Digital <em>(<strong>Disclosure</strong>: I am the SVP Head of Earned at NP Digital)</em>, pointed to a broader hiring shift, <a href="https://www.cnbc.com/2026/01/06/amd-lisa-su-ai-jobs-hiring.html" target="_blank" rel="noopener">citing comments from AMD CEO Lisa Su</a>, and elaborates:</p>



<ul class="wp-block-list">
<li>“Companies are racing to get mentioned on AI platforms in 2026, but much of that carries over from traditional SEO. Where marketers and marketing departments are going to see the big lift from 2026 is getting their team to use the right tools and focus on the right tasks when it comes to AI.”</li>



<li>“We are seeing adoption rates skyrocket in organizations, but when you look at increased ROI from these AI efforts in marketing, it doesn’t look that great. So in 2026, we will focus more on training and helping teams understand and use AI to improve their KPIs. This way, usage and costs are more closely tied to growth.”</li>
</ul>



<p><strong>Key takeaway: </strong>Companies that operationalize AI into repeatable processes tied to KPIs will gain margin and velocity, while everyone else pays for tools without measurable lift.</p>



<h2 class="wp-block-heading" id="h-what-winning-visibility-looks-like-in-2026">What winning visibility looks like in 2026</h2>



<p>In 2026, winning visibility will be less about chasing rankings and more about becoming the most usable and trustworthy input for humans, AI answers, and autonomous agents alike.&nbsp;</p>



<p>Brands that invest now in machine-readable data, proprietary moats, and AI-literate teams will be the ones thriving in 2027.</p>

The search landscape, today’s buyer journey, and the roadmap to digital success aren’t just shifting. They’re being structurally reimagined.
To make sense of this shift, I spoke with six of the SEO industry’s most forward-thinking voices and distilled their perspectives into seven core predictions for 2026.
What follows is a series of insights into how search is being structurally reimagined.
1. The rise of agentic commerce
We are moving past the era of AI as an answer engine and into the era of AI as an executive assistant.
“Agentic web” means AI won’t just tell you which running shoes are best. It will actually find your size, apply a coupon, and execute the checkout. 
For SEOs, this means optimizing for clicks is no longer the ceiling. We must optimize for machine readability and API compatibility. 
If an agent can’t parse your inventory or price in real-time, you won’t exist in this new transaction layer.
Jim Yu, CEO of BrightEdge, stressed the importance of agentic preparation:
“We’re already seeing a massive rise in agentic crawlers – AI that searches and acts on behalf of users. Brands need to prepare now with structured data, clear content hierarchy, and machine-readable information. The winners will be the ones who can measure AI agent behavior and understand how they’re being discovered and recommended.”
Yu elaborated, noting that we’re entering a new market maturity phase.
“AI search will take the next steps to becoming a real marketplace. The LLMs will expand paid advertising and other paid partnership opportunities. With that will come increased transparency and insights into how people are using LLMs within customer journeys. AI search will move from something that is coming to something that is here and having a major impact. 2026 will be the year that brands solidify the measurement frameworks to understand and respond to that impact.”
Samanyou Garg, founder and CEO at Writesonic, predicted that the agentic web will move users from the discovery phase directly to the transaction phase within a single AI conversation:
“810 million people use ChatGPT daily. Google AI Overviews hit 1.5 billion monthly users. The debate about whether AI search matters is over. What’s changing in 2026: AI stops recommending and starts buying.  The user never leaves the conversation.  OpenAI open-sourced their Agentic Commerce Protocol. Shopify merchants enable checkout with one line of code.  Amazon saw this coming.”
Crystal Carter, head of AI search and SEO communications at Wix, warned that focusing solely on being found is no longer enough:
“The future of AI search is optimizing for the AI agents. In the last six months, we’ve seen new protocols for agentic payments, agentic shopping, and agent-to-agent frameworks. These each change the paradigm of the marketing funnel significantly by adding an AI decision gatekeeper into the mix.”
“I think many search professionals are focusing wholly on being found in classic search or AI surfaces, but ignoring the agentic opportunity is a mistake. SEO and GEO are, of course, valuable, but the agentic layer removes the user from much of the funnel. The so-called messy middle is now managed by AI. If you don’t build for compliance, then you’re not even in the game.”
Key takeaway: If your product, pricing, and availability data is not machine-readable in real time, AI agents will skip you and favor competitors.
2. AI ads will expand with deeper integration 
As AI platforms mature, monetization through ads is following suit. 
Today, monetization has moved upstream into the generative process itself. 
Whether it’s a sponsored product recommendation within a ChatGPT shopping thread or a paid citation in a Google AI Overview, the ad unit has become conversational.
Yu’s prediction: 
“AI responses are now behind every door in the Google SERP – People Also Ask, Maps, Shopping, and more. YouTube is a prime example: one of the most cited sources in AI search and already a monetization powerhouse. Expect more intuitive ad integration within these AI experiences in 2026, which reinforces why brands need to optimize once and win everywhere.”
Garg noted that while AI ad targeting is limited, establishing organic dominance now matters before auctions open:
“Ads are coming, but the window is now. Google runs ads in AI Overviews across 12 countries, and they’re testing in AI Mode. But brands can’t target these placements yet. Google picks who shows up. Perplexity launched sponsored questions, then paused… ChatGPT shopping is ‘organic and unsponsored’ today. Their CFO says ads are coming. Same pattern as early Google. Organic visibility now means dominant position when the auction opens.”
Key takeaway: Paid visibility will shift from “buying clicks” to “buying inclusion,” and brands that are not already eligible and trusted will pay more and win less.
3. The best SEOs ship tools, not tasks
The barrier between having a marketing idea and building a marketing tool has evaporated. 
In 2026, the most successful SEO teams will look less like writers and more like product engineers, with efficiency becoming a competitive advantage.
Garg argued that this year marks the end of the visual workflow era, replaced by natural language tools that let non-technical marketers ship production-level code:
“The old way: visual workflow builders. Drag nodes, connect arrows, take a three-week course to learn the platform. The new way: Claude Code and tools like it. Describe what you want in plain English. It writes the script, runs it, iterates.”
“Anthropic’s own growth team uses this daily. Process a CSV with hundreds of ads, identify underperformers, generate new variations. Minutes, not hours. They cut content audit time 75% and reduced costs 70% through intelligent model routing.”
“The gap between ‘I have an idea’ and ‘it’s running in production’ collapsed. 2026 is the year non-technical marketers start shipping like engineers.”
Key takeaway: Teams that automate repeatable digital marketing tasks will compound output and speed, while manual teams fall behind on both cost and time to impact.
Get the newsletter search marketers rely on.
  
				
								
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See terms.
4. Personalization and specialization will keep changing the optimization game 

In 2026, the concept of a traditional ranking may finally become obsolete. 
If every search result is personalized in real time based on a user’s entire digital history, there is no “Position 1” anymore – there is only intent and relevance.
While Google and OpenAI dominate the headlines, the next frontier also includes specialization. 
As users grow weary of hallucinations in general models, they will increasingly turn to AI platforms built for specific, high-stakes niches. 
As a result, AI strategy can’t be mono-platform. Brands will need to optimize for a fragmented ecosystem of AI models that prioritize different data sources.
Mike King, CEO of iPullRank, predicts the death of the generic SERP:
“In 2026, personalization stops being a feature and becomes the operating system. Google’s Nested Learning work makes the direction obvious. Search systems are no longer learning just from queries. They are learning from you across multiple time horizons. Fast signals like session behavior and immediate intent sit on top of slower, more stable models of how you think, decide, trust, and revisit information over time.”
“The system is not adapting results. It is adapting itself to the user. The practical outcome is that two people asking the same question are no longer in the same information universe. They are getting different answers, different sources, and different levels of explanation based on how the system has learned to serve them without friction or failure. This quietly kills the idea of a single ranking, a single SERP, or a single ‘best page.’ If your content only works for a generic user, it works for no one.”
But this shift is not limited to Google. As users seek more reliable, specialized answers, the search ecosystem continues to splinter across platforms and vertical-specific models.
Key takeaway: Performance will vary by audience segment rather than a single SERP position, meaning brands can be invisible to high-value buyers even while overall rankings appear stable, creating hidden pipeline risk.
5. SEO splits: Humans vs. agents

SEO and AI search will continue to fragment. 
Historically, SEO had one goal: get the click. Sites were optimized so a human would discover a brand and land on a page. 
In 2026, the industry is splitting into two distinct strategic problems.
Traditional SEO, focused on humans who want to browse, compare, and buy.
AI search optimization, focused on supplying information so AI agents can find, trust, and use it without a user ever visiting the site.
This is not just a technical update. It represents a fundamental shift in how success is measured.
King explained why treating these as the same strategic problem is a mistake:
“Most people think AI search is just SEO evolving. There will be real tactical overlap for a while, and that is not the issue. The mistake is treating it as the same strategic problem. SEO is built around earning visibility that converts into clicks. AI search is built around supplying information that can be extracted, trusted, and reused without a click ever happening. They keep optimizing for rankings and traffic while the system is optimizing for reliability, composability, and downstream usefulness.”
“The work still matters. But the reason it matters has fundamentally changed, and most people have not caught up to that shift yet. We now live in a world where people form relationships with systems that listen, remember, adapt, and respond with context and continuity. That is not a search problem. That is a worldview shift.”
“In 2026, the biggest risk is not that SEO dies. It is that the people who should lead this moment choose to stay small, and the relevance engineers build the future without them.”
Britney Muller, AI educator and consultant, cautioned that applying traditional SEO logic to AI citations is a strategic failure:
“The biggest risk to our industry in 2026 isn’t AI; it’s that we’re trying to fit a baseball bat through a keyhole by applying SEO ranking logic to probabilistic systems.”
“You can’t ‘optimize’ an AI citation like a 2010 keyword. We have to pivot the conversation to what we can actually influence: showing up in the historical training data and winning the real-time RAG layer through fundamental SEO and brand mentions at scale.”
Key takeaway: In 2026, SEO becomes two jobs: driving clicks from humans and supplying clean, trusted inputs for AI agents that may never visit your site. 
Measuring success only by rankings and sessions risks missing where revenue is actually influenced.
6. Proprietary data becomes your moat
Unique, proprietary, and human-driven content wins. 
As the web becomes flooded with AI-generated material, the value of human experience and owned data continues to rise. 
If an AI can easily synthesize your content without needing to cite you, the underlying value is likely interchangeable. 
When brands own the data itself, however, attribution becomes unavoidable.
Muller highlighted that building unique, branded datasets is one of the strongest ways to secure AI attribution:
“My big bet is on brands that start building entity moats … more strategically naming their data. When you own a unique metric, like the ‘[Brand] Index’ or the ‘[Brand] Score,’ you create a source of truth that AI models can’t just synthesize or ignore.”
“If they can’t replicate your data, they are forced to cite your name. Brands are also getting ahead by harvesting real-world stories and conversations highlighting things that AI cannot do.”
Muller further shares:
“Content marketers that will find an edge in 2026 will discover savvy ways of leveraging AI to analyze public datasets and then do something really cool and story-worthy with them.”
“Think about the one million hotel reviews that MonkeyLearn did … which used sentiment analysis to discover nuanced insights.”
Key takeaway: Commodity content becomes a cost center, while proprietary data and real experience become defensible assets that earn citations, trust, and inbound demand.
7. AI literacy becomes a hiring filter
AI adoption and training are critical. 
The shift in 2026 is as much about people as it is about technology. 
The era of AI novelty is over. Simply using ChatGPT is no longer a differentiator. 
The competitive divide now depends on whether teams can move beyond basic content drafting and use AI as a strategic partner tied to real outcomes.
The leaders of 2026 will be those who successfully connect AI usage to key performance indicators.
Neil Patel, CEO and co-founder of NP Digital (Disclosure: I am the SVP Head of Earned at NP Digital), pointed to a broader hiring shift, citing comments from AMD CEO Lisa Su, and elaborates:
“Companies are racing to get mentioned on AI platforms in 2026, but much of that carries over from traditional SEO. Where marketers and marketing departments are going to see the big lift from 2026 is getting their team to use the right tools and focus on the right tasks when it comes to AI.”
“We are seeing adoption rates skyrocket in organizations, but when you look at increased ROI from these AI efforts in marketing, it doesn’t look that great. So in 2026, we will focus more on training and helping teams understand and use AI to improve their KPIs. This way, usage and costs are more closely tied to growth.”
Key takeaway: Companies that operationalize AI into repeatable processes tied to KPIs will gain margin and velocity, while everyone else pays for tools without measurable lift.
What winning visibility looks like in 2026
In 2026, winning visibility will be less about chasing rankings and more about becoming the most usable and trustworthy input for humans, AI answers, and autonomous agents alike. 
Brands that invest now in machine-readable data, proprietary moats, and AI-literate teams will be the ones thriving in 2027.

AI search now handles discovery, decisioning, and transactions. Here’s what that means for SEO strategy in 2026.

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