This release is for developers and anyone who builds on Yoast SEO. It brings two changes: you can now use your AI tool to update titles, meta descriptions, and social previews with Yoast SEO Abilities. In addition, we’ve done our yearly cleanup of deprecated code. If you maintain a theme or plugin that hooks into Yoast SEO, read the cleanup section before you update.
Update titles and descriptions from your AI tool
Since April, Yoast SEO Abilities have let you use your AI tool to check your SEO, readability, and inclusive language scores. In September, you could also read a post’s SEO data and correct its technical settings without opening wp-admin. Now you can update the titles and descriptions people see in search results and social feeds too.
The yoast-seo/update-post-seo-data ability now supports six more fields:
SEO title
Meta description
Open Graph title and description (what platforms like Facebook and LinkedIn show when someone shares your post)
X title and description
For example, say you’ve renamed a product, and its title and social previews still show the old name. You can use your AI tool to read the post’s SEO data, review what’s out of date, and update it in the same conversation.
Everything else works as before. Your focus keyphrase stays read-only, so you always set it yourself. In addition, access still follows native WordPress capability checks.
Already using Abilities? The new fields are ready once you update. New to it? The developer documentation covers how to connect your LLM and the WordPress MCP Adapter, plus the full ability list and schemas.
Yearly cleanup of deprecated code
We’ve removed code we deprecated in Yoast SEO 26.1 or earlier. If your site, theme, or plugin still uses any of it, you’ll have been seeing deprecation notices for at least a year. As a result, most sites won’t notice a thing. However, these changes are the most likely to affect you:
We’ve removed the WPSEO_Frontend class, which we deprecated in Yoast SEO 14.0 (April 2020).
We’ve removed the wpseo_opengraph and wpseo_twitter actions. Use wpseo_frontend_presenters instead. You’ll still get a warning if your code hooks into them.
The wpseo_robots_array filter must now return an array. Returning anything else causes a fatal error.
We’ve deprecated the $where and $format arguments of WPSEO_Database_Proxy::upsert(). That means we’ll remove them in next year’s cleanup.
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AI adoption in email is concentrated in content production. Personalization, automation, and deliverability, where the bigger revenue gains sit, get far less attention.
Personalization is moving from broad segments, like geography and demographics, to individual, predictive targeting.
Automation’s share of email revenue grows with company size. Businesses over $51 million in revenue get 71 percent of email revenue from automation versus 11 percent from campaigns.
Nearly a fifth of sent emails never reach the inbox, and most of that loss happens before a subscriber has any chance to engage.
The programs that win connect personalization, automation, and deliverability into a single system that reinforces itself.
Have you noticed your team is sending more emails than ever, but the results don’t feel any different?
Most marketers are pointing AI at email marketing’s wrong problem. The real opportunity is understanding customer intent, automating decisions, and personalizing experiences at scale. Most teams are using AI to write more emails without fixing the parts of the program that actually drive revenue.
Email personalization, automation, and deliverability are the three areas that actually move that revenue. Inboxes are getting louder as AI makes content creation easier, and louder rarely means more relevant. The rest of this post walks through what’s changing in each area, and how to build them into one connected system.
The AI Shift: What’s Changing in Email Marketing
Marketing teams are under real pressure right now: do more with fewer resources, scale personalization, improve retention and lifetime value, and increase marketing efficiency, all at once. AI looks like the obvious answer.
The problem is where that AI effort is actually going. Ask marketers what their biggest email challenge is today, and list growth tops the list at 29 percent, followed by personalization at 25 percent. Deliverability comes in last, at just 6 percent, even though it’s the foundation everything else depends on. An email that never reaches the inbox can’t be personalized or well-timed enough to matter.
Deliverability: making sure it reaches the inbox at all.
You can’t improve these levers in isolation and expect the same lift each time. A gain in one gets erased by a gap in another. Perfect personalization that lands in spam accomplishes nothing, and flawless deliverability paired with generic, one-size-fits-all messaging just means more people ignoring an email they did receive.
Personalization in the AI Era
Most brands are stuck in what amounts to a segmentation trap. They personalize using broad buckets, new versus returning customers, geography, industry, demographics, and call it personalization. Only 34 percent of companies actually use AI-driven or predictive email marketing personalization. Another 24 percent are still at basic audience segmentation, and 5 percent use no personalization at all.
Most teams have the customer data needed for real personalization, they just aren’t using it to predict what happens next. Teams rate themselves strongest in measurement and attribution, with 55 percent calling that capability strong or very advanced. They rate themselves weakest in customer data and identity, at just 37 percent strong or advanced, along with AI skills and governance.
Personalization moves through three stages. Demographic personalization (location, age, gender) is the easiest to set up but produces broad assumptions and low relevance. Behavioral personalization (products viewed, purchases, engagement) produces higher engagement and better conversion. Predictive personalization goes a step further, using purchase likelihood, churn risk, and lifetime value to guide what happens next.
Open rates already vary by age group, from roughly 20.6 percent among 18-24-year-olds up to 25.7 percent among 55-64-year-olds, which makes a strong case for layering behavioral and predictive signals on top of basic demographic segmentation.
Four tactics you can implement this week: dynamic product recommendations based on browsing and purchase history, dynamic content blocks that swap headlines and offers by segment, send-time optimization based on when a subscriber actually engages, and predictive offers built around what a subscriber is likely to buy next.
Campaign marketing runs on a simple loop: campaign, send, repeat. Lifecycle marketing works differently. A customer action triggers an automated response, no one has to remember to hit send.
That shift matters more as companies grow. Businesses earning less than $1 million get 49 percent of their email revenue from campaigns. That flips as revenue scales. Companies earning over $51 million get 71 percent of email revenue from automation and just 11 percent from campaigns. Manual scheduling shows up as inconsistent customer journeys, day-to-day operational inefficiency, and revenue a trigger would have caught but a person missed.
Some automations pull far more weight than others. Abandoned cart drives the largest share of automation revenue at 32 percent, followed by welcome series at 21 percent and post-purchase upsell or replenishment at 16 percent.
Post-purchase flows compound in a way that’s easy to underestimate. Email marketing lifts repurchase rate by 31 percent and shortens time to repurchase by roughly 8 days, and that gain repeats across your entire customer base.
Automation maturity builds in stages. Triggered campaigns just need a trigger to fire. Behavioral automation needs data on what people actually do. Predictive lifecycle marketing needs AI making the calls on timing and offers.
Deliverability: Why Great Emails Still Land in Spam
Here’s how much audience a typical send loses before anyone has a chance to engage. Of emails sent, 98 percent get accepted by the mailbox provider, but only 82 percent actually reach the inbox. Only 36 percent get opened, and only 2.5 percent get clicked. Every stage between send and click loses part of your audience, and most of that loss happens before a subscriber ever sees the email.
Inbox providers are changing the rules on this. They increasingly use AI to decide which emails reach the inbox, which get filtered, and which senders get trusted at all. Marketers tend to rank authentication and open rate as what matters most, but inbox providers weight sender and domain reputation and spam complaints far more heavily. Trust signals like replies and complaint rates are quietly deciding who gets filtered, whether marketers are watching them or not.
Email deliverability best practices rest on authentication (SPF, DKIM, DMARC), sender reputation built through engagement and damaged by complaints, and list quality, where a smaller engaged audience consistently outperforms a larger inactive one. Good list hygiene reinforces each of these: segment by engagement, purchase behavior, and activity recency, then back that up with re-engagement campaigns, sunset policies, and suppression strategies for contacts who’ve gone quiet.
Higher send frequency can shrink your effective audience instead of growing it. Open rates decline as cadence increases, from 33.8 percent at one send a week down to 26.2 percent at five or more, and volume without value trains subscribers to stop opening. Affiliate emails and cold emails carry the highest unsubscribe and spam complaint rates of any email type. The most common mistakes behind poor email deliverability are excessive frequency, poor segmentation, purchased lists, misleading subject lines, and ignoring inactive subscribers instead of suppressing them.
Personalization, automation, and deliverability only work as one system. Personalization without deliverability never gets read. Automation without personalization feels robotic. Deliverability without automation can’t scale past what a person can manually manage.
A modern email stack needs five pieces working together: an ESP platform, a customer data platform, AI content tools, predictive analytics, and deliverability monitoring. Most teams already have some of these, but few have them talking to each other.
That disconnect shows up in where AI investment is actually going. Teams are pouring the most effort into content creation and paid media optimization, the two areas with the highest percentage of teams applying AI. Personalization and marketing automation get far less investment, despite rating comparable or higher on effectiveness. Investment is going toward the easiest wins, even though personalization and automation are rated as more effective.
The future email team blends strategy, data, automation, and AI into a single connected workflow from the start.
The 90-Day Action Plan
Trying to fix personalization, automation, and deliverability all at once is how most programs stall. Sequencing beats doing everything simultaneously.
Days 1 to 30 (Audit): Review deliverability, automation, and segmentation to find the weakest link in your current program.
Days 31 to 60 (Implement): Build the priority automations, dynamic content, and AI-assisted workflows the audit surfaced.
Days 61 to 90 (Scale): Layer in predictive personalization, advanced testing, and revenue measurement once the foundation holds.
The sequencing matters more than the individual tactics. Predictive personalization and recommendations account for the largest single share of incremental business impact among AI email initiatives, at 31 percent, and impact compounds as each subsequent initiative builds on the last, reaching 100 percent cumulative impact across all five. Sequence each initiative starting with whichever is easiest to implement, and let each one build on the last.
FAQs
What is AI email personalization?
AI email personalization uses behavioral and predictive data, like purchase likelihood, churn risk, or browsing history, to tailor subject lines, content, and offers to each subscriber individually.
How do I improve email deliverability?
Focus on authentication (SPF, DKIM, DMARC), sender reputation built through consistent engagement, and list quality maintained through regular re-engagement campaigns and suppression of inactive contacts.
What email automations have the highest ROI?
Abandoned cart, welcome series, and post-purchase upsell or replenishment automations drive the largest share of automation revenue. Browse abandonment and re-engagement automations round out the five workflows worth building first.
How much should I automate vs. send as campaigns?
It depends on company size and program maturity, but the trend is clear: larger, more mature email programs shift the majority of their revenue toward automation. Businesses over $51 million in revenue get 71 percent of email revenue from automation, compared to 49 percent from campaigns at businesses under $1 million.
Conclusion
AI raises the ceiling on an email program that already has strong fundamentals in place.
Personalization, automation, and deliverability function as one integrated system. A gap in any one of them limits what the other two can do. Brands that build these pillars in sequence see the gains compound faster than brands trying to fix everything simultaneously.
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If you’re weighing Yoast SEO vs All in One SEO, you’re asking the right question. Your SEO plugin touches almost every page you publish. It shapes how search engines read your site and how AI platforms understand it too. Both plugins have been part of WordPress for a long time and are a popular choice among website owners and agencies worldwide. So this isn’t a choice between a proven tool and an untested one. It’s a choice between two ideas of what an SEO plugin should do for you.
What matters in a WordPress SEO plugin comparison
Most established plugins cover the basics: SEO titles, meta descriptions, content analyses. What separates them is how they help you make decisions, handle change, and support you when something goes wrong. Before comparing features, ask yourself:
Will it help me understand SEO, or will it only tell me what to change?
Will it keep working reliably as WordPress and search evolve?
Can I get help right away when something breaks?
Is it ready for how people search now, including AI assistants?
Can it grow with my site, my team, and the platforms we use?
Yoast SEO vs AIOSEO: how the plugins compare
AIOSEO positions itself as an all-in-one toolkit. Alongside its TruSEO on-page analysis, it offers a Schema generator, search statistics, a keyword rank tracker, local SEO, a link assistant, and AI writing tools. At the moment, AIOSEO has over 3 millions users of their WordPress plugin.
Yoast SEO takes a different approach. We focus on guiding you as you write, structuring your site for search engines and AI platforms, and explaining the why behind every recommendation. Yoast SEO is active on more than 13 million websites with more than 1 billion downloads in total.
Feature
Yoast SEO
All in One SEO
Free version
Yoast SEO
AIOSEO Lite
Content feedback
Real-time SEO and readability analysis, plus inclusive language analysis
TruSEO on-page analysis and score
AI tools
AI Generate, AI Optimize, AI Summarize, AI Content Planner (Premium), AI Bulk Editor (Premium) and AI Brand Insights (Yoast SEO AI+)
AI Assistant, AI Content Generator, and AI Image Generator
Structured data
One connected Schema graph, generated automatically
Schema Generator with rich snippet types
AI readability
llms.txt and Schema Aggregation, both free
LLMs.txt Generator
Platforms
WordPress/WooCommerce, Shopify, and Google Docs
WordPress including WooCommerce
Learning
Yoast SEO Academy courses, blog posts, help articles, and monthly webinars
Documentation, blog, and guides
Both are capable plugins. AIOSEO leans toward breadth and reporting inside WordPress, while Yoast SEO leans toward guidance, structure, and readiness for wider discovery.
Understanding what you need
The best WordPress SEO plugin is the one that fits your goals:
Guidance and learning: Choose a plugin that explains why each recommendation matters.
AI readiness: Look for connected Schema, llms.txt, and control over AI crawlers.
Support: Check how quickly you can reach a real person when something breaks.
Search data in WordPress: Does the plugin provide sufficient data to make choices about your content and website?
The long term: Pick a plugin with a record of stable updates and a team that keeps adapting.
Experience that keeps up with search
For more than 15 years, Yoast has tracked every major shift in search, from early algorithm updates to AI-generated answers. Today, Yoast SEO is active on more than 13 million websites and has passed one billion downloads.
That experience works for you. Our team follows algorithm updates and how AI platforms read content, updates the plugin when things change, and explains what it means on our blog, in webinars, and in Yoast SEO Academy. Since 2010, our mission hasn’t changed: SEO for everyone, regardless of budget or technical skill.
Innovation for how people search today
People now find answers through search engines, AI Overviews, and assistants like ChatGPT, Claude, Gemini, and Perplexity. Here’s how Yoast SEO helps search engines and AI platforms understand your content.
Make your site readable for AI
Schema Aggregation (free): Built with Microsoft NLWeb, it brings your structured data together in a standard format that’s easier to read for AI agents.
llms.txt (free): A plain-text guide, generated for you, that points large language models (LLMs) to your most important content.
Bot Blocker (Premium): Choose which AI crawlers can access your content.
Yoast SEO Abilities (free): This integration allows your AI tool to read and fix a post’s core technical SEO settings.
AI Generate: SEO title and meta description options in one click
AI Optimize: Specific fixes for SEO assessments, which you can apply, edit, or dismiss
AI Summarize: A key takeaways block for long posts
AI Content Planner: Five post ideas specifically for your site, plus a starter draft
Bulk Editor: AI-drafted metadata for your whole site, with every change yours to approve
See how AI represents your brand
Yoast SEO AI+ includes AI Brand Insights, which tracks how your brand appears in ChatGPT, Claude, Gemini, and Perplexity. See your AI Visibility Index, sentiment, and cited sources, and compare them with competitors. No tool can guarantee AI mentions, but this gives you the visibility to decide what to create next.
Schema that search engines can understand
Structured data, or Schema, shows search engines who wrote a page, which organization is behind it, and what it offers. Most plugins add some option to add structured data to your pages. The difference is how the pieces fit together.
Yoast SEO automatically builds one connected Schema graph per page. Your organization, website, pages, articles, and authors are linked in a single JSON-LD structure, the format search engines read. No setup is needed and Yoast WooCommerce SEO adds product details like price and availability to the same graph.
A consistent graph makes your site easier for search engines and AI platforms to interpret. It also makes pages eligible for rich results like breadcrumbs, though no plugin can guarantee they’ll appear.
An ecosystem that supports you
24/7 support (Premium): Help from real people, whenever you need it.
Yoast SEO Academy (Premium): Courses from SEO basics to AI for SEO, with certificates. Some courses are free for everyone.
Local, Video, and News SEO (Premium): All included in Yoast SEO Premium.
New features are exciting, while reliable updates are what keep your site running. Every Yoast SEO release is tested, PHP setups, and common plugin combinations, and built to keep your existing settings working. With more than 13 million active installations, the same plugin runs on personal blogs and large enterprise sites.
Where Yoast SEO stands out
Guidance that teaches as you write
Color-coded SEO and readability feedback in your editor, with a short explanation per assessment, in more than 20 languages. The optional inclusive language analysis helps you spot wording that could leave readers out. Premium adds multiple keyphrases, word forms, and synonyms, so you can write naturally.
Internal linking and redirects (Premium)
Yoast SEO suggests relevant pages to link to as you write. The redirect manager prompts you to create a redirect when you change a URL, and supports CSV import and export and regex. A regex pattern allows you to redirect a whole group of URLs that share a word or pattern in one single redirect.
Crawl settings
Turn off URLs, scripts, and metadata that WordPress adds automatically with the crawl settings, so search engines focus on the pages that matter. Less wasted crawling also helps reduce your site’s carbon footprint.
Which Yoast product fits you?
Plan
Best for
What you get
Yoast SEO
Anyone getting started with SEO
Real-time SEO and readability analysis, connected Schema graph, XML sitemaps, llms.txt, Schema Aggregation, bulk editor and crawl settings
Yoast SEO Premium
Entrepreneurs and in-house marketing teams
Everything in Yoast SEO, plus AI tools, internal linking suggestions, redirect manager, Bot Blocker, Local, Video, and News SEO, Yoast SEO Academy, and 24/7 support
Yoast WooCommerce SEO
Online stores on WooCommerce
Everything in Premium, plus product Schema, ecommerce content analysis, and AI-generated SEO titles and meta descriptions for products
Yoast SEO AI+
Marketers and brands who want to track AI visibility
Everything in Yoast WooCommerce SEO, plus AI Brand Insights
Yoast SEO tends to suit you if you want a plugin that explains its recommendations, structures your site for search engines and AI platforms, and comes with education and support. Switching is simple, because Yoast SEO’s import tool supports All in One SEO. Our migration guide covers each step in detail.
Make the choice that supports your growth
Choosing an SEO plugin isn’t about the longest feature list. It’s about a partner that fits how you work and keeps up as search changes. With Yoast SEO, you get guidance that teaches as you write, free AI-readiness tools, AI built into Premium, and 24/7 support, backed by more than 15 years of dependable releases.
Whichever plugin you choose, pick the one you’ll be happy to build on for years. Check out our Yoast SEO Premium page for more information on our SEO plugin and its features.
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Each month, we host the SEO Update by Yoast, covering the latest in search and AI. In this edition, Carolyn Shelby and Alex Moss discussed Google’s latest content updates, the impact of AI on search visibility, and how to adapt to the evolving digital landscape.
A study from The State of Brand highlighted the risks brands face when their information is cited on third-party platforms such as Reddit. Since LLMs are probabilistic rather than deterministic, they rely on recurring information to verify their accuracy.
Why it matters: Your brand’s messaging might be shaped by external sources, not just your own content. If negative sentiment dominates discussions about your brand on Reddit or review sites, that could be the narrative LLMs pick up.
Actionable takeaway:
Ensure your messaging is consistent and widely referenced across all platforms.
Actively engage in discussions on third-party sites to provide counter-narratives where needed.
Monitor mentions of your brand regularly and address inaccuracies.
Google says ChatGPT sends new audience to Search
AI is not replacing search but altering how people interact with it. Google reports that ChatGPT is driving new search queries, often long-tail and more specific.
Why it matters: Users are now conducting more searches than ever before, but these searches differ from traditional ones. They are more conversational and tailored to specific needs. The growth in AI-generated queries means more opportunities for your content to rank, provided it addresses niche topics.
Actionable takeaway:
Focus on creating content that dives deep into specific Subject matter and answers unique questions.
Optimize for long-tail keywords and conversational queries.
Leverage tools like Google Trends and Mark Williams Cook’s AlsoAsked to explore related topics.
Why it matters: Ads in ChatGPT could further complicate visibility for organic results. Just like Google Ads once did, paid placements may start to dominate attention within AI conversations. However, this can also be an opportunity for brands that want to ensure their content is seen.
Actionable takeaway:
Explore running ads on ChatGPT, so your brand doesn’t miss out on visibility.
Optimize your ad creatives to stand out against organic listings.
Google loses faith in low-value programmatic SEO
Google is cracking down on sites using low-value programmatic content to manipulate rankings.
Why it matters: Forget what you heard in the past; this type of content is not just unhelpful now, it is actively harmful. These pages are often created solely to rank for as many keywords as possible with minimal effort, offering little to no value to users. This approach has always been risky, and since the September 2026 core update, it is increasingly likely to backfire.
Actionable takeaway:
Audit all programmatic content on your site.
Ensure every page provides unique insights or first-person perspectives.
Back up your content with evidence, original research, or unique data.
Google deploys new AI spam detector
Google has officially launched SAFE, its new AI spam detector. This is another step in their ongoing effort to fight low-quality, auto-generated content.
Why it matters: Google is actively working to combat spammy content. This new protection is filtering out unhelpful, auto-generated content so that useful content can surface instead.
Actionable takeaway:
Review your content and remove any low-quality or auto-generated pages.
Focus on creating high-quality, user-centric content.
Why it matters: As AI answers become the norm, publishers need new ways to monetize their content. If they rely solely on traditional models, they may struggle as traffic declines. With fewer people clicking through to their sites, publishers need to find an alternative way to earn, and Google may be providing it.
Actionable takeaway:
Explore new revenue models beyond ad-based traffic.
Monitor development in AI-driven content monetization closely.
Cloudflare lets sites block AI training without blocking Googlebot
Why it matters: While this may sound tempting, it’s best to think long and hard before blocking AI from crawling your site. Blocking AI crawlers will remove your site from AI-generated answers, making your content less visible. If you’re not in those AI answers, you won’t get the traffic or the credit.
Actionable takeaway:
Weigh the pros and cons of blocking AI crawlers.
Focus on ensuring your content is well-structured and accessible so that AI systems can cite it accurately.
Why it matters: With annotations disappearing from Google Analytics and Google blocking scrapers, the tools we rely on for this data will become less reliable. This shift will likely force SEOs to adapt their strategies and rely more on alternative data sources. The insights we get from our tools will probably become more directional instead of exact.
Actionable takeaway:
Prepare clients and stakeholders for less reliable data.
Diversify your data sources so that you can cross-reference for accuracy.
Use LLMs to analyze your exports and find consistencies in your data.
Google Lighthouse adds AI agent resource discovery audit
Why it matters: This tells agents a site’s capabilities. It is expected to become increasingly important for discovery. Should you implement it? That depends on how large your site is. If your site is small, consisting of around five pages, then it isn’t necessary. However, if your site is large and complex, ARD will let agents understand what they can do with your site’s pages.
Actionable takeaway:
Decide if your business needs ARD.
If your site is large and complex, work with your development team to prioritize this.
Research finds AI mode may send fewer clicks
Research shows that AI Overviews may be sending fewer clicks to publishers.
Why it matters: If we want to be discovered, we need to rank highly and ensure our snippets pull users in. Bearing this in mind, it is now more important than ever to ensure your content is unique so that an LLM has a reason to cite you.
Actionable takeaway:
Focus on high-quality, unique content that provides genuine value.
Optimize your snippets to entice users to click.
Google Search traffic to publishers continues to decline
Google Search continues to see a drop in referrals, a trend observed across the web.
Why it matters: As the digital landscape shifts, traditional metrics like traffic are becoming less reliable indicators of success. Visibility equals success in the current environment, and you can have visibility without traffic.
Actionable takeaway:
Focus on unique, high-quality content.
Find new KPIs that accurately reflect your performance.
Analyze AI-driven insights to find out what is truly working for your business.
Google updates guidance on using generative AI content
Why it matters: Google is making it clear that using AI to create content is not inherently bad. Bad content is bad, whether humans or AI generate it. If your content offers nothing new, unique, or interesting, then LLMs already have that information. Why would they cite you?
Actionable takeaway:
Use AI to assist in creating new and interesting content.
Always review AI-generated content to ensure its accuracy.
Anthropic calls for a slowdown in AI development
The CEO of Anthropic has called for a slowdown in AI advancement, while other business leaders disagree. You can read their thoughts here and here.
Why it matters: Is this a genuine concern for safety or a strategic move to gain a competitive edge? Either way, it’s sparking crucial conversations about what the future of AI will look like.
Actionable takeaway:
Stay informed about the discussions surrounding AI development.
Consider the ethical implications of your use of AI.
Why it matters: Shopify stores that use Yoast SEO AI+ can gain a deeper understanding of how AI is portraying their brand. This allows the opportunity to adapt to any inaccuracies.
Actionable takeaway:
Try out Yoast SEO AI+ for Shopify to gain valuable insights.
http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png00Dubado Solutionshttp://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.pngDubado Solutions2026-10-07 09:37:262026-10-07 09:37:26The September 2026 SEO Update by Yoast recap
Over the years, the Search Central YouTube channel
has published hundreds of videos across various series, from Search for Beginners and Ask Googlebot
to Search Console Training and Search Off the Record. While our series structure works well for
deep dives and episodic updates, we know that finding a clear, sequential learning path from scratch can sometimes be challenging.
PR budgets could double by 2027 as brands adapt to AI-powered search.
AI systems increasingly rely on authoritative third-party sources when generating answers and recommendations.
Digital PR can help brands build visibility and credibility beyond their own websites.
Consistent earned media coverage can strengthen a brand’s authority over time.
Brands should connect digital PR with SEO and AI visibility rather than treating them as separate strategies.
For years, public relations and SEO have operated in neighboring but often separate parts of the marketing organization. AI search is beginning to change that relationship.
As AI systems become a larger part of how people discover companies, products, and services, the sources those systems rely on are becoming increasingly important. Third-party coverage from trusted publications can provide information that helps establish a brand’s credibility and authority. That shift is changing how organizations think about digital PR. New industry projections suggest PR budgets could double by 2027 as brands respond to the growing importance of AI-powered search. The underlying reason is straightforward: brands need to be visible in the places AI systems use to understand and evaluate them. For marketers, that makes earned media more than a traditional awareness channel. Consistent third-party coverage can contribute to a brand’s broader search presence while strengthening the information available about it across the web.
Why AI Search Is Increasing the Value of Digital PR
AI search changes how people encounter information. Instead of receiving a list of links and deciding which ones to visit, users can receive a synthesized answer based on information gathered from multiple sources.
AI systems need information they can retrieve and use when generating answers.
A company’s own website is an important source, but it isn’t the only one. News publications, industry websites, reviews, research organizations, and other third-party sources can provide additional context about a brand. Academic databases are a great example.
This is where earned media becomes valuable.
A company that is consistently mentioned by credible publications creates a broader information footprint than one that relies primarily on its own website. Those mentions can help reinforce what the company does, who its experts are, and where it has authority.
That doesn’t guarantee an AI system will cite any particular article. It does create more opportunities for a brand’s information to exist within the sources AI systems may encounter.
Third-Party Coverage Can Build Brand Authority
Authority is difficult to establish through a single piece of coverage.
One major publication can create awareness, but its effect can fade. A sustained presence across relevant publications creates a different type of signal.
Repeated coverage can reinforce the same core facts about a business across multiple sources. Over time, this can contribute to stronger brand recognition and a clearer understanding of the company’s expertise.
For AI visibility, that consistency matters because AI systems are constantly processing information from across the web.
Why One Media Win Isn’t Enough
The temptation in PR has often been to measure success by the biggest placement a campaign can generate. A marquee publication can certainly be valuable, but it shouldn’t be the only objective.
Credibility Compounds Over Time
A single article can introduce a company to a new audience. An ongoing stream of relevant coverage can keep reinforcing the brand.
This is particularly important for companies competing in categories where many businesses make similar claims.
Regular coverage gives journalists, customers, search engines, and AI systems more opportunities to encounter consistent information about the brand.
That makes digital PR a long-term investment rather than a series of isolated campaigns.
Consistency Creates a Stronger Information Footprint
Imagine two companies competing for visibility in the same industry.
One receives a major feature once a year. The other is regularly covered by relevant publications for research, commentary, product developments, and industry expertise.
The second company has a much larger body of third-party information surrounding it.
That doesn’t mean quantity automatically creates authority. Coverage needs to be relevant and credible. But a consistent stream of meaningful mentions gives a brand more opportunities to establish expertise and reinforce its identity.
What This Means for SEO and AI Visibility
The growing importance of digital PR creates an opportunity for SEO teams and PR teams to work more closely together.
Digital PR and SEO Should Work Together
SEO has traditionally focused heavily on a brand’s own website. Digital PR extends that strategy into the broader web.
A strong PR campaign can generate coverage that supports brand awareness, creates referral opportunities, and contributes to the overall authority surrounding a company.
At the same time, SEO research can help identify topics, publications, and audiences that are strategically important to the brand.
Combining these approaches creates a more connected approach to organic visibility.
AI Visibility Depends on More Than Owned Content
Brands have significant control over their own websites. They have much less control over what independent publications say about them.
That makes third-party coverage particularly valuable.
When a brand is consistently described by credible external sources, those sources can provide context beyond what the company says about itself. This can be especially useful when AI systems are trying to determine which businesses, products, or experts are relevant to a user’s question.
The goal isn’t to manufacture mentions. It is to build a legitimate reputation that is reflected across the web.
How Brands Can Build an Always-On Digital PR Strategy
If digital PR is becoming more important to AI visibility, brands need a strategy that goes beyond occasional campaigns.
Create a Consistent Flow of Newsworthy Ideas
An always-on program starts with having something worth talking about.
Brands can develop stories around original research, customer trends, proprietary data, expert commentary, product developments, and broader industry changes.
Not every idea needs to become a major campaign. The goal is to consistently identify useful information that journalists and audiences would find valuable.
Build Relationships With Relevant Publications
Distribution alone isn’t enough.
Brands should identify publications and journalists who regularly cover their industry and develop relationships with them over time.
This makes it easier to provide useful expertise when relevant stories emerge rather than approaching media outlets only when the brand has something it wants promoted.
Measure the Cumulative Impact
An always-on strategy should be evaluated differently from a campaign built around one major placement.
Track the growth of relevant coverage over time alongside brand visibility, branded search, referral traffic, and other meaningful indicators.
For AI visibility, also monitor how frequently the brand appears in relevant AI answers where measurement is possible.
The objective is to understand the cumulative effect of sustained authority building.
PR Investment Is Becoming an AI Visibility Investment
The growing importance of AI search is changing the role of PR.
Brands still need traditional media coverage because journalists and publications reach real audiences. But those same sources can also contribute to the information ecosystem that AI systems use to understand brands.
That makes earned media increasingly relevant to search strategy.
The strongest competitive advantage in AI search is consistency, not a single media win. Credibility compounds through ongoing earned coverage that reinforces brand authority over time.
The implication for marketers is significant. PR budgets shouldn’t be viewed only through the lens of immediate media impressions. The long-term value of consistent coverage can extend into brand authority, organic visibility, and AI discovery.
How to Prepare for the Shift in PR Investment
Brands don’t necessarily need to abandon existing PR programs. Instead, they should consider how those programs can support broader search and visibility goals.
Connect PR Goals with Search Goals
PR and SEO teams should identify the topics, entities, and areas of expertise that matter most to the brand.
Those priorities can then inform media outreach and content development.
A company trying to establish authority in a particular category, for example, can build an ongoing PR program around the research, expertise, and commentary that supports that position.
Prioritize Quality and Relevance
More coverage isn’t automatically better.
A mention from an irrelevant or low-quality source may contribute little to a brand’s authority. The strongest opportunities are publications and sources that are relevant to the industry and trusted by the audiences the brand wants to reach.
Make Digital PR an Ongoing Investment
The biggest change may be moving away from one-off PR campaigns.
An always-on digital PR program gives brands more opportunities to build relationships, publish useful information, and earn coverage throughout the year.
That sustained activity can create a stronger foundation for organic visibility as search continues to evolve.
The Future of PR Is Connected to Search
AI is changing how brands are discovered, and PR is becoming part of that discovery process.
Third-party coverage gives AI systems additional information about brands while giving consumers independent sources they can use to evaluate a company. Over time, a consistent stream of relevant coverage can help strengthen the brand’s authority across the web.
This doesn’t mean every PR placement will result in an AI citation. It means brands should recognize that the value of earned media can extend beyond the publication’s immediate audience.
The brands that invest consistently in credible coverage will have more opportunities to establish authority as AI search becomes a larger part of how people find information.
FAQs
Why is AI changing PR budgets?
AI search is increasing the importance of authoritative third-party information. As AI systems use external sources to understand and answer questions about brands, organizations are placing greater emphasis on earned media and digital PR as part of their broader visibility strategies.
How does digital PR help with AI visibility?
Digital PR can generate credible third-party coverage that provides additional information about a brand across the web. This can contribute to the broader information ecosystem AI systems use when understanding brands, although coverage doesn’t guarantee an AI citation.
Is earned media becoming more important for SEO?
Earned media can complement SEO by building authority and visibility beyond a company’s own website. Relevant third-party coverage can strengthen brand recognition and provide additional sources of information for search and AI systems.
What is an always-on digital PR strategy?
An always-on strategy continuously identifies opportunities for relevant media coverage throughout the year instead of relying on occasional campaigns. It can include original research, expert commentary, industry insights, and other newsworthy material.
Conclusion
AI search is changing how consumers discover and evaluate brands, and that shift is increasing the strategic value of digital PR.
Third-party coverage can give AI systems additional sources of information while helping consumers validate a brand’s expertise and credibility. A single major placement can create valuable exposure, but consistent coverage can build a much stronger information footprint over time.
For marketers, this means PR and SEO should increasingly work toward the same visibility goals. Building an always-on digital PR program can create a steady stream of earned media that supports brand authority while contributing to a broader AI visibility strategy.
The brands that treat PR as an ongoing investment in credibility will be better positioned as AI search continues to reshape how people discover businesses.
If you want to build an always-on digital PR strategy that supports both traditional search and AI visibility, reach out to the NP Digital team to learn how earned media can fit into your broader organic strategy.
Yoast SEO AI+ for Shopify is live today. The new plan combines Yoast SEO for Shopify with Yoast AI Brand Insights, giving you visibility into how AI systems like ChatGPT, Gemini, Claude, and Perplexity describe your brand, alongside everything you already rely on for search.
Why now
More shoppers are starting their search with AI these days, not just Google. Shopify has seen this firsthand: in Q1 2026, AI-driven traffic to Shopify stores grew 8x year over year, and orders from AI-powered search grew nearly 13x (Shopify, “How Agentic Commerce Works,” 2026).
That doesn’t mean checkout itself has moved to AI, at least not yet. OpenAI closed ChatGPT’s Instant Checkout back in March. What’s actually happening is simpler: AI is helping people discover and compare products, and then they come to your store to buy. AI is becoming a new way for shoppers to find you. Your store is still part of where that relationship builds, alongside social and everything else that shapes how your brand comes across, and it’s still where the sale happens.
That’s why it’s worth knowing what AI is already saying about your brand, before a shopper ever reaches your site. That’s what Yoast SEO AI+ for Shopify helps you do.
Your products have a new audience: AI
See the pitch it’s making. Shape the narrative to your advantage.
Yoast SEO AI+ for Shopify gives you structured data and technical SEO so your products are read correctly, and Yoast AI Brand Insights so you can see how your brand comes across once shoppers arrive.
What’s new
Yoast SEO AI+ for Shopify combines Yoast SEO for Shopify with Yoast AI Brand Insights. Everything you already rely on, product SEO, structured data, technical SEO, is still there. What’s new is visibility into the layer before the sale: how AI systems describe your brand before a shopper ever reaches your store.
With AI Brand Insights, you can:
See your brand’s AI Visibility Index score
Know whether AI speaks positively about you, with sentiment tracking
See how you compare to competitors in AI
See which sources AI is citing when it talks about you
Run scans across ChatGPT, Gemini, Claude, and Perplexity, then decide what to do with what you find. AI Brand Insights shows you the story AI is telling about your brand. It doesn’t write it for you. That part is still yours.
What’s included
Yoast SEO AI+ for Shopify is the complete product visibility plan: everything in Yoast SEO for Shopify, plus AI Brand Insights. You can compare the plans here.
Pricing
Yoast SEO AI+ for Shopify is $45/month or $450/year, with a 14-day free trial.
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Is your 2026 SEO strategy actually ready for the next wave of AI search updates?
Between AI-driven search overhauls and constant algorithm tweaks, keeping your site visible can be challenging.
The SEO Update by Yoast brings you the latest insights on algorithm updates, AI-driven search changes, and industry developments, all in one easy-to-follow session.
Join Carolyn Shelby and Alex Moss as they discuss the stories shaping SEO today and share actionable takeaways you can apply right away.
Who should sign up?
This update is ideal if you:
Want expert insight into recent SEO and AI changes and trends
Need help refining or validating your SEO strategy
http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png00Dubado Solutionshttp://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.pngDubado Solutions2026-10-01 11:00:242026-10-01 11:00:24The SEO Update by Yoast – October 2026
If you’ve been setting up MCP connections or agentic workflows, this release is for you. You ask an AI tool to check your site’s SEO. It comes back with real findings: a product page that’s telling Google it’s a recipe, a link still pointing to an old test version of your site. Helpful, but useless on its own: you still have to go and fix each one yourself, by hand, in the back end of your website. Now, Yoast SEO enables the same AI tool to make those changes for you.
Yoast SEO Abilities is what makes that possible. It lets your AI tool read what’s wrong with a page’s SEO and update it directly, the same technical settings you’d otherwise have to change by hand. You diagnose and fix in the same place.
AI tools are moving from answering questions to being able to take actions. Abilities gives that shift a front door on your own site, one you control.
What you could do before
Since its release in April, Yoast SEO already registers three abilities with WordPress’s Abilities API: SEO scores, readability scores, and inclusive language scores for your most recently modified posts. Any AI tool could reliably check which posts had a weak SEO score. However, it had no standardized way to read the underlying fields or change them. Someone still had to open wp-admin.
That gap is what this release closes.
Read a post’s full SEO field set
yoast-seo/get-post-seo-data returns the title, meta description, robots flags, schema type, canonical, social previews, and scores.
In addition, you can identify the post by ID, permalink, or title search. As a result, your agent can find the post you mean from a plain-language description in one call, instead of hunting through several.
Fix the technical fields
Core technical settings are now writable from your AI tool: canonical, robots flags, cornerstone, and schema type. These are fields Yoast already manages, so nothing new sits between your content and your site.
Roll back what you change
Any change made through the WordPress Abilities API can be rolled back, as long as your AI tool holds the changed values in context. In practice, read a post’s SEO data before you update it. Then stay in that session while you review the result. Once the context is gone, the previous value goes with it, so treat the read call as part of the write.
Work in bulk
Bulk and batch operations let you apply a get, update, or filter request across multiple posts in one call. You get per-post results back, so you can see exactly what changed and where.
Control where it matters
Your focus keyphrase stays read-only. You always set it yourself, and it is never generated for you. An automatic change there could invalidate content briefs or marketing workflows, and it would skew every assessment that follows. For content workflows, we suggest continuing in the editor, where the content flow lives.
Access follows native WordPress capability checks. There is no separate permission system to learn. Therefore, you can audit access the same way you audit any other admin-level access.
Built on WordPress standards
These abilities use WordPress’s Abilities API. Once you connect the WordPress MCP Adapter, they become callable MCP tools for any MCP-aware client, for example Claude Desktop, Claude Code, Cursor, or VS Code. Therefore no custom integration is needed.
Typed input and output schemas spell out what to send and what to expect back. For anyone building dashboards or reporting tools on top, that predictability matters more than any single feature.
For agencies, it also means one standard setup across every WordPress build, with no manual per-site reconfiguration.
What you need to get started
Connect your own LLM subscription to Yoast first. After that, read access, core SEO field updates, and bulk operations are all included as part of Yoast SEO. The developer documentation covers the full ability list, the typed input and output schemas, and how to connect the WordPress MCP Adapter.
See it in your dashboard
Once you’ve connected your LLM subscription, head to Yoast SEO, then Integrations. We’ve also reorganized this page: instead of one long list, integrations are now grouped by topic, so they’re easier to scan. Look for the new AI & agentic group. For further information, read the help article on how to set up Abilities.
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AI systems are more likely to reference brands that present original research.
Research suggests that where information appears on a page can influence its chances of receiving an AI citation.
Clear formatting makes original findings easier for AI systems to identify and extract.
Brands can apply this approach to blog posts as well as product and service pages.
Proprietary data can strengthen a brand’s authority while creating new opportunities for AI visibility.
Original research gives brands something valuable in an increasingly crowded search landscape: information that isn’t available everywhere else.
That advantage may become even more important as AI search changes how people discover information. A recent Search Engine Land analysis of AI citations found that proprietary data can be a strong differentiator for brands seeking visibility in AI-generated answers.
The research also points to an important qualification: Unique information alone isn’t enough. AI systems were more likely to cite information when it appeared earlier on the page and was presented in a format that made it easy to identify and extract.
For marketers, this changes how original research should be approached. The value lies in both what you publish and how you present it.
What the Research Found About AI Citations
The research highlights two factors that can work together when brands publish original information. The first is having something unique to contribute. The second is making that information easy to find.
Original Data Gives AI Systems Something Unique to Cite
AI systems have access to an enormous amount of information. When the same statistics, explanations, and observations appear across numerous websites, individual pages can have a difficult time standing out.
Proprietary data gives brands an opportunity to offer something different. This can take the shape of:
Original surveys (e.g., asking 1,000 homeowners about their home-buying journey)
Audience research (e.g., most and least common homebuyer demographics, according to your CRM data)
Internal studies (e.g., analysis of lead form data to present trends in average home loan amount requested over the last 20 years)
Industry statistics (e.g., home loan interest rate trends during times of economic uncertainty)
When an AI system needs to answer a question related to that subject, unique findings give it a source that offers information beyond the standard answers already circulating online.
For content teams, this makes original research worth considering during the planning process. A page that contributes a new finding can offer more value than one that simply summarizes information already available on competing sites.
Where Information Appears Can Affect Its Visibility
The research also found that information appearing earlier on a page was more likely to receive an AI citation.
That finding gives marketers another factor to consider when organizing content. If an important statistic is buried several sections into an article, an AI system may have a harder time identifying it as one of the page’s key contributions.
This doesn’t mean every page should follow a rigid formula. It does suggest that important findings deserve prominent placement.
When a piece of original research is central to a page, introducing the finding earlier can make the information easier for both AI systems and readers to locate.
Why Content Structure Matters for AI Visibility
Publishing unique information is only part of the opportunity. The research also highlights the role that page structure plays in making that information accessible.
An AI system needs to identify and interpret information before it can use that information in an answer. Clear, well-organized writing can make that process easier.
Consider a page containing an original statistic. Instead of making readers work through several paragraphs before reaching the finding, state the result clearly under a relevant heading. Then explain what the number represents, how it was collected, and why it matters.
This gives the statistic enough context to stand on its own.
The goal isn’t to create content specifically for machines. Good structure makes important information easier for everyone, especially your human readers, to understand.
Put Your Strongest Insights Near the Top
The findings also support a practical recommendation for content teams: consider bringing your strongest original insights closer to the beginning of the page.
NP Digital recommends surfacing important original statistics within roughly the first third of educational and commercial pages. This helps crawlers and readers find the most critical information early on.
The exact placement will depend on the page. A product page may need introductory information before presenting a research finding, while an educational article might be able to lead with the data.
The important point is to avoid hiding the information that makes your content distinctive.
How to Make Original Data More Visible in AI Search
The research provides a useful direction for content teams, but putting it into practice starts with looking at the information a brand already has. If we look at the examples below, we can see how proprietary data appears both on a brand site and in an AI overview citing it.
Start by auditing existing content for topics that could benefit from original research. Look for pages that touch on trends, make claims, or target keywords that include phrases like “how many” or “how much.”
Customer research, surveys, internal studies, and product usage data can all provide useful fodder. Some of these insights may already exist within an organization but have never been published publicly.
There may also be opportunities to conduct original research to create new content. A study focused around an important industry question can produce findings that other websites don’t have.
The goal is to contribute information that adds value to the topic. Adding statistics simply to make a page appear more authoritative won’t create the same benefit.
Structure Data for Humans and AI Systems
Once you identify original information, look at how it is presented.
Use descriptive headings that tell readers what a section contains. State important findings clearly instead of making readers search for them. When a statistic needs additional context, provide that explanation close to the finding.
Schema markup gives AI systems another way to interpret your content beyond the visible text. Dataset schema helps identify original research as structured data. FAQ schema helps format question-and-answer content so AI systems can extract it directly.
Comparison tables also give AI systems a clear structure to work with. Instead of describing several data points across multiple paragraphs, a table presents categories, numbers, and time periods in one place. This makes the information easier to scan for readers and easier to extract for AI systems.
FAQs create another opportunity for direct citation. Framing a key finding as a question and answer offers a self-contained unit that AI systems can reference without interpreting surrounding paragraphs. Adding FAQ schema reinforces that structure at the code level, not just in the visible layout.
These practices support AI search while improving the reading experience at the same time. Readers can scan the page more easily, and AI systems have clearer information to interpret.
Apply the Strategy Beyond Blog Content
Original data doesn’t need to live exclusively in blog posts.
Product pages can incorporate relevant customer or usage research. Service pages can include industry findings that demonstrate expertise. Commercial pages can use proprietary statistics to provide evidence for the claims they make.
This is particularly important for pages that contribute directly to business goals. Hard numbers that prove the effectiveness of your product are much more likely to get someone to convert than a bit of clever copywriting.
As AI search becomes part of the discovery process, brands should consider whether their most valuable pages contain information that gives AI systems a reason to reference them.
Original Data Is Becoming an SEO Advantage
AI search is changing the value of information on the web.
AI systems can summarize information that has been published many times before. Original findings give brands an opportunity to contribute something less easily replicated.
That makes proprietary research a potentially valuable asset for both traditional SEO and emerging AI experiences. But the research discussed here suggests that publishing unique information is only part of the equation. The information also needs to be accessible.
In the AI era, unique data creates authority, but only structured content turns that authority into visibility.
The opportunity for marketers is to bring these ideas together. Find information your organization can uniquely contribute, then make those findings clear and easy to locate on the page.
That approach can give original research a longer life as search continues to change.
FAQs
What is proprietary data in SEO?
Proprietary data is information a brand has collected or produced itself that isn’t readily available from competing sources. It can include original research, customer insights, surveys, internal studies, and company-specific statistics.
Can original data improve AI citations?
Original data can give AI systems information that is difficult to find elsewhere. Research discussed by Search Engine Land found that unique information was more likely to receive AI citations when it appeared early on the page and was presented clearly.
Where should original data appear on a page?
Important findings should generally be placed where they are easy to find, particularly when they are central to the page’s purpose. NP Digital recommends considering the first third of educational and commercial pages for significant original statistics.
How should I structure content for AI search?
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Make important findings easy to identify and understand. Use clear headings, state statistics directly, and provide relevant context close to the information. These practices also make pages easier for people to scan and navigate.
Conclusion
Original data gives brands an opportunity to contribute something unique to AI search. But having proprietary information doesn’t guarantee that it will be discovered or cited.
The research suggests that presentation matters. Important findings should be easy to locate, clearly explained, and placed prominently on the page.
Brands can start by auditing existing content for first-party insights and original research, then revisiting the structure of their highest-value pages. As AI search continues to influence discovery, combining proprietary data with clear content structure can give brands another way to build AI visibility while providing more useful information to their audiences.
If you want to strengthen your visibility in AI search, reach out to the NP Digital team to learn how original data, content strategy, and AI search optimization can work together to support your long-term growth.
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