In our Rethinking SEO in the age of AI article, we briefly explored how AI might move beyond simple prompt-and-response interactions. One emerging direction is agentic AI. Systems that can take action, not just generate answers. While this space is still evolving, we’re already seeing early signs of tools that can identify gaps, suggest improvements, and adapt to changing trends with minimal input. If these capabilities continue to develop, they could reshape how we think about maintaining continuous discoverability in SEO.

Table of contents

• Understanding the coexistence of web and AI agents
• What will SEO mean in agentic web?
• Role of agentic AI in SEO
• Understanding the risks and challenges of agentic AI for SEO
• What discoverability might look like in an agent-driven web?

Understanding the coexistence of web and AI agents

Before understanding agentic SEO, let’s first look at the role of AI in shaping the web. Is it staying the same, or quietly changing?

For a long time, the web has been more than just a collection of pages. It has functioned as an interconnected graph of entities. Websites representing people, businesses, ideas, and concepts, all linked together through content, context, and trust. This structure, often referred to as the open web, has remained relatively stable for decades. Humans created content, users discovered it through search or links, and meaning was formed through exploration.

What seems to be shifting now is not the structure itself, but how that web is accessed and consumed.

Earlier, discovery was largely a direct interaction between humans and websites. You searched, clicked, read, compared, and formed your own conclusions. Today, AI systems are increasingly stepping into that journey. They sit between the user and the web, interpreting, summarizing, and sometimes even deciding which information to surface.

This is where the idea of AI agents begins to emerge. Not just as tools that generate responses, but as systems that can navigate the web, retrieve information, and potentially act on it. Early examples, such as experiments in natural language interfaces like NLWeb, hint at a web that can be interacted with more conversationally, without losing its openness and interconnectedness.

Some refer to this shift as the beginning of an “agentic web.” But it’s important to see it less as a complete transformation and more as a layer forming on top of the existing web. The open web still exists, content is still created by people, and links still matter. What’s evolving is how that content is discovered, interpreted, and used.

And that shift in interaction is where things start to get interesting for SEO.

Read more: Yoast collaborates with Microsoft to help AI understand Open Web

What will SEO mean in agentic web?

If AI agents are starting to reshape how people interact with the web, it naturally raises a follow-up question: where does that leave SEO?

For years, SEO has largely been about helping users find your content. You optimized for rankings, improved visibility on search engines, and relied on users to click, read, and navigate. But if AI agents begin to mediate that journey, not just retrieving information but interpreting and acting on it, then SEO may need to expand its role.

Not necessarily replace what exists, but build on top of it.

From ranking pages to being selected by systems

In a more agent-driven environment, discoverability may no longer depend solely on where you rank, but also on whether your content is selected, trusted, and used by AI systems.

That introduces a subtle but important shift:

• It’s not just about being visible
• It’s about being understandable, reliable, and usable by machines

AI agents don’t browse the web the way humans do. They:

• Parse structured and unstructured data
• Look for clear signals of authority and accuracy
• Combine information from multiple sources before presenting it

So instead of optimizing only for clicks, SEO may also involve optimizing for inclusion in AI-generated responses and workflows.

What stays, what evolves, what gets added

Let’s ground this a bit. Traditional SEO doesn’t disappear. Many of its fundamentals still apply, but their role may shift.

What stays relevant

• High-quality, original content
• Clear site structure and internal linking
• Strong technical SEO foundations
• Authority and trust signals (E-E-A-T)

These remain essential because AI systems still rely on the web as their source of truth.

What evolves

• Keywords → Intent modeling: Less about exact-match phrases, more about covering topics deeply and contextually
• Rankings → Presence across surfaces: Visibility may extend beyond SERPs into AI summaries, assistants, and agent outputs
• Clicks → Influence: Users may not always visit your site, but your content can still shape their decisions

What gets added

• Structured, machine-readable content: Schema, clean formatting, and semantic clarity become even more important
• Content designed for extraction: Clear answers, definitions, step-by-step explanations
• Topical authority at the entity level: Being recognized as a trusted source for a subject, not just ranking for a keyword
• Freshness and adaptability: Content that evolves as trends and information change

So, what does SEO really become?

It starts to look less like a discipline focused purely on rankings and more like one focused on continuous discoverability.

Or, as Alex Moss puts it in his article The Same But Different: Evolving Your Strategy For AI-Driven Discovery, the web itself may be evolving into two parallel experiences:

This has created a split from a completely open web into two – the ‘human’ web and the ‘agentic’ web… SEOs will have to consider both sides of the web and how to serve both.

That framing makes the shift clearer.

Your content still needs to rank. But it also needs to work at a second layer of the web, where AI systems interpret, select, and sometimes act on information before a human ever sees it.

So now, your content needs to be:

• Understood without ambiguity
• Trusted enough to be referenced
• Structured well enough to be reused

In that sense, SEO doesn’t disappear in an agentic web. It stretches.

From helping users find information…

to helping systems choose it.

Role of agentic AI in SEO

If the web is gradually being experienced through both humans and AI agents, then it’s worth asking what role these agents might begin to play in SEO itself. Not as a replacement for SEO teams, but as a new layer within how SEO work gets done.

What we’re starting to see is a shift from SEO as a set of periodic tasks to something more continuous, assisted, and adaptive. Some early tools already hint at this. They don’t just analyze data, they suggest actions. In some cases, they even implement changes. If this direction continues, agentic AI could become less of a tool you use and more of a system you collaborate with.

Let’s break down where this role might start to take shape.

How agentic AI may reshape SEO workflows

Shift	Traditional SEO approach (how it typically works today)	With agentic AI (emerging direction)
Audits → Always-on optimization	SEO teams run audits at set intervals (monthly, quarterly) using tools such as site crawlers. Issues such as broken links, missing metadata, or slow pages are identified and then manually fixed over time. Improvements often depend on when the audit is conducted.	Systems continuously monitor site performance, flag issues as they arise, and may suggest or implement fixes in real time. Optimization becomes ongoing rather than dependent on manually scheduled audits.
Reacting → Anticipating	Actions are usually triggered by visible changes. For example, a drop in rankings leads to an investigation, or an algorithm update prompts content revisions. SEO is often a response to what has already happened.	AI systems analyze patterns in search behavior and performance data to detect early signals. This could mean identifying emerging topics, shifting intent, or declining engagement before it significantly impacts performance.
Manual execution → Guided systems	Tasks such as keyword research, clustering, content optimization, and internal linking are performed manually or with tools. SEO specialists interpret the data and execute changes step by step.	AI assists with these tasks by identifying keyword opportunities, grouping topics, suggesting optimizations, and even applying specific changes. SEOs shift toward guiding strategy, reviewing outputs, and setting priorities.
Static content → Adaptive content	Content is created, published, and revisited occasionally. Updates are often triggered by performance drops, outdated information, or scheduled content refresh cycles.	Content evolves more dynamically. Systems can recommend updates based on performance, refine sections for clarity, or restructure content to better match user intent and AI consumption patterns.
Generic UX → Contextual journeys	Most users experience the same content and navigation structure. Personalization is limited or rule-based, such as basic recommendations or segmented landing pages.	Experiences become more contextual. Content, navigation, and recommendations can adapt based on user behavior, intent, or journey stage, creating more relevant and engaging interactions.
Technical maintenance → Intelligent infrastructure	Technical SEO involves periodic checks for issues such as crawl errors, indexing problems, and schema gaps. Fixes are prioritized manually based on impact and resources.	AI systems continuously monitor technical health, automatically prioritize issues, suggest fixes, and, in some cases, implement them. Structured data, internal linking, and site architecture can be dynamically optimized.

A quick example: structuring content for machines, not just humans

If agentic systems rely on structured, connected, and machine-readable content, then this isn’t entirely new territory for SEO.

In many ways, we’ve already been moving in this direction through structured data and schema. What’s changing is how important and foundational it may become.

For example, features like schema aggregation in Yoast SEO bring together different pieces of structured data across a site and connect them into a more unified graph. Instead of treating pages as isolated units, they help search engines better understand how entities, content types, and relationships fit together.

This might seem like a technical detail, but it reflects a broader shift.

If AI agents are parsing, combining, and interpreting content across multiple sources, then clarity and connection at the data level become more important. Not just for visibility in search results, but for how content is understood and reused.

So while agentic AI may feel like a new layer, some of the foundational work, like structuring content, defining entities, and building semantic relationships, is already part of modern SEO. It just becomes more critical in this context.

So, where does this leave SEO teams?

If there’s one pattern across all of this, it’s not replacement, but redistribution.

Agentic AI may take on:

• Repetitive tasks
• Data-heavy analysis
• Continuous monitoring

Which leaves humans to focus more on brand-building aspects like:

• Strategy and positioning
• Editorial judgment and brand voice
• Deciding what should be done, not just what can be done

In that sense, agentic AI doesn’t redefine SEO overnight. But it does start to reshape how it’s practiced.

Understanding the risks and challenges of agentic AI for SEO

So far, agentic AI might sound like a natural evolution of SEO. But, as with most shifts in technology, it may also come with trade-offs.

Not because the technology is inherently problematic, but because it introduces new dependencies, new layers of complexity, and new decisions for SEO teams to navigate. In that sense, adopting agentic AI isn’t just about adding a new capability. It may also involve rethinking how much control to delegate and where human judgment continues to play a critical role.

Here are some of the challenges that could emerge as this space evolves:

1. High technical and integration complexity

Agentic systems are unlikely to operate in isolation. They may need to connect with your CMS, analytics tools, and multiple data sources.

This could introduce challenges such as:

• Managing integrations across platforms
• Ensuring consistent and reliable data flow
• Defining clear workflows across systems

For many teams, this might not be plug-and-play. It could require time, experimentation, and coordination across different roles.

2. Data quality and dependency

Agentic AI may be heavily dependent on the quality of data it receives. If the data is:

• Outdated
• Incomplete
• Poorly structured

Then the outputs could reflect those gaps.

At scale, even small inconsistencies might influence multiple recommendations or decisions. Which is why maintaining clean, reliable data sources may become even more important in an agent-driven setup.

3. Risk amplification and the need for governance

One of the strengths of agentic AI is speed. But that same speed might also amplify unintended outcomes.

Without clear guardrails:

• Content updates could introduce inaccuracies
• Technical changes might lead to issues like broken links or indexing errors
• Best practices may not always be consistently followed

This is where governance frameworks and approval checkpoints may become essential, not to slow things down, but to keep them aligned.

4. Hallucinations and accuracy considerations

AI systems can sometimes generate outputs that sound plausible but aren’t entirely accurate.

In an SEO context, this might look like:

• Misinterpreted data
• Inaccurate keyword insights
• Fabricated or blended information

The challenge is that these outputs can be difficult to spot at a glance. This suggests that validation and source-checking may remain an ongoing part of the workflow.

5. Limited understanding of nuance

SEO often goes beyond data and structure. It includes tone, context, and intent. Agentic systems may not always fully capture:

• Brand voice and positioning
• Legal or compliance nuances
• Subtle differences in user intent

This could result in outputs that are technically sound, but not always contextually aligned. Human input may still play a key role here.

6. Balancing automation with human judgment

A broader question that may arise is how much to automate.

• Too much automation might: Reduce control over strategy or brand
• Too little might: Limit efficiency and scalability

Most teams may find themselves balancing the two. Using agentic AI to extend their capabilities, while still guiding direction and decision-making.

7. High initial investment and learning curve

While agentic systems may offer long-term efficiency, getting started could take time. This might involve:

• Learning how the systems work
• Setting up workflows and integrations
• Aligning outputs with business goals

There’s also a level of uncertainty here. The technology is still evolving, and so are the tools built around it. Which means costs, capabilities, and best practices may continue to shift.

For many teams, adoption may not be immediate. It could happen gradually, through testing, iteration, and figuring out what actually works in practice.

8. Zero-click experiences and shifting traffic patterns

As AI systems become more involved in surfacing information, zero-click experiences may become more common.

Users might:

• Get answers directly within AI interfaces
• Interact without visiting the original source

This doesn’t necessarily reduce the importance of SEO, but it may shift how success is measured. Visibility and influence could become just as relevant as traffic.

What discoverability might look like in an agent-driven web?

Agentic AI may open up new possibilities for how SEO is done. But alongside that, it may also introduce new considerations.

It could require:

• Stronger data foundations
• Clear governance and review processes
• A thoughtful balance between automation and human input

In many ways, the goal may not be full automation. It may be a better collaboration.

Even if agents take on more execution, the responsibility for direction, accuracy, and trust is likely to remain human. And maybe that’s the more interesting shift here. Not whether AI agents will “take over” SEO, but how they might reshape what good SEO looks like.

If discoverability is no longer just about ranking, but also about being selected, interpreted, and reused by systems, then the role of SEO starts to expand. It becomes less about optimizing for a single interface and more about preparing content to exist across multiple layers of the web.

So the question isn’t just:

“How do we rank?”

It might slowly become:

• How to stay understandable across multiple LLMs?
• Do we remain trustworthy enough to be referenced?
• How do we design content that works for both humans and machines?

We don’t have all the answers yet. And maybe that’s okay.

Because this isn’t a fixed destination. It’s something that’s still taking shape.

And as it does, SEO may continue to evolve alongside it. Not disappearing, not being replaced, but adapting to a web that is becoming more dynamic, more layered, and a little less predictable.

The post Ensuring continuous discoverability with agentic AI for SEO appeared first on Yoast.

Read more at Read More

AI is changing search and rewriting the rules. If your brand isn’t visible in AI-generated answers, you have a bigger problem than just traffic. You’re missing out on trust, credibility, and customers who now expect AI to recommend the best options everywhere.

Table of contents

• Why modern SEO is about AI visibility
• AI search is a blind spot for most
• Controlling the narrative of your brand
• Yoast AI Brand Insights is here to help
• Understanding the AI visibility metrics
• 5 Ways to improve your AI brand visibility
• How to influence LLMs to mention your brand
• The future of brand visibility is AI-driven
• Ready to take control of your AI brand visibility?

We see that traditional SEO isn’t enough anymore. Today, it’s possible to rank #1 on Google and still be invisible in the AI responses people now often turn to for recommendations.

Yoast AI Brand Insights is a great tool that shows you exactly how your brand appears in AI-generated answers from ChatGPT, Perplexity, or Google Gemini. It tracks sentiments and benchmarks against competitors. What’s more, it doesn’t just help build your AI visibility, but also helps control your brand’s narrative.

Why modern SEO is about AI visibility

People are no longer just searching on Google. Every day, more people are asking AI tools and Large Language Models (LLMs) like ChatGPT, Gemini, and Perplexity for recommendations. Unlike classic search engines, these tools don’t just list links; they curate answers by combining trained knowledge with information they’ve learned from the web.

AI platforms combine information from multiple sources to provide a single, context-aware, and custom answer. People even start treating these AI answers as personal advice, not just generic search results. This will happen more and more as search engines like Google increasingly integrate AI into their search results. As a result, the boundaries between traditional search and AI-generated answers are blurring.

AI search is a blind spot for most

Classic SEO tools track rankings, but they don’t track how your brand appears in AI answers. This leads to blind spots where your competitors might be all over the AI recommendations in your market without you realizing it.

What’s more, you might rank well on Google, but you could be invisible to a growing audience if AI systems ignore your brand. Your competitors can appear more often or more positively in AI recommendations. Or there’s negative sentiment in AI responses that can harm your reputation without you even knowing.

Controlling the narrative of your brand

AI platforms like ChatGPT, Perplexity, and Gemini piece together your brand’s story from scattered sources, like reviews, news articles, social media, and your own content. If these send mixed signals, the answers an AI gives will too. That’s why you need to send a unified, consistent message. This is one of the most effective ways to reinforce your narrative across every platform.

Repeat your main message, whether that’s “affordable luxury” or “sustainable innovation,” everywhere, from your site content to press releases and from social media to external interviews.

Quickly address misinformation and respond to inaccurate reviews by publishing clarifications online. By doing this, you prevent the AI from amplifying outdated or incorrect details.

Support your brand’s most important attributes with structured data. Add the awards your brand won, or its unique selling points, so you can give the AI platform an all-encompassing framework to reference.

Remember, consistency is about repeating your most important brand aspects everywhere. Shape the narrative in such a way that the AI has no choice but to reflect the brand the way you want it to project.

Yoast AI Brand Insights is here to help

Yoast AI Brand Insights is a helpful tool that tracks how your brand appears in AI answers. It provides a clear, actionable view of your brand’s visibility, sentiment, and credibility across major AI platforms.

Yoast AI Brand Insights helps you:

• Understand if and how your brand is mentioned in AI responses
• Track sentiment and see if AI platforms describe your brand positively or negatively
• Identify the sources to see what AI references when mentioning your brand
• Benchmark against competitors to see how you stack up

We didn’t build this to get you some data, but to turn that AI black box into actionable insights.

Understanding the AI visibility metrics

Using the Yoast AI Brand Insights metrics helps you measure and improve your brand’s visibility in AI platforms. To make the most of it, you have to understand what metrics mean and why they matter.

AI Visibility Index (AIVI)

The AI Visibility Index (AIVI) scores (on a scale of 100) how visible your brand is on AI platforms such as ChatGPT, Perplexity, and Gemini. It consists of the following metrics:

• Mentions, or how often your brand is cited in AI answers
• Citations, or the number of authoritative sources referencing your brand
• Sentiment, or the rate of positive vs. negative keywords associated with your brand
• Rankings, or the relative position of your brand mentions compared to your competitors

The higher the AIVI score (on a scale of 0-100), the more visible your brand is in AI search results for the tracked terms. If you find that your score is low, you should focus on getting more mentions and citations. You should also work on positive sentiment around your business.

You build your relevance by publishing authoritative content. Try to get featured on relevant sites and monitor and improve negative sentiment around your brand. Learn more about how AI shapes brand perception.

Mentions

The Mentions section tracks the specific queries for which your brand appears in AI responses. So, if someone asks, “What is the best low-cost CRM system for small businesses?” and your brand is in the results, that is a mention.

It’s not hard to understand why this is important. More mentions generally lead to greater visibility. If you don’t show up for the terms and queries relevant to your brand, you need to start improving your content.

Use the built-in AI-generated brand queries to find high-intent questions and write content that answers those questions thoroughly. These could be blog posts or FAQ pages, or whatever makes sense. Also optimize for conversational queries, such as “Is brand X good for startups?”

Sentiment

Sentiment measures the percentage of negative vs. positive words in the query results associated with your brand. So, if the AI describes your brand as “innovative” or “reliable”, that counts as positive sentiment. However, if they use terms like “overpriced” or “unreliable”, that’s negative sentiment.

Positive sentiment helps build trust, while negative sentiment can drive potential customers away. That’s why you should always actively address negative sentiments online. Don’t leave those bad online reviews unresponded to. You can also publish testimonials on your site to amplify positive voices, and you can do the same in your marketing messaging by talking about “a brand loved by thousands” or “award-winning” products.

Keep an eye on trends in your online sentiment and catch and fix issues early.

Citations

Citations refer to the sources that AI platforms explicitly reference when generating an answer, not the brands mentioned within those sources. For example, if Gemini answers a query about “the best credit cards” and cites a New York Times article about best credit cards, that New York Times page is the citation. Even if the article includes brands like American Express or Chase, the citation is attributed to the publisher, not to the individual brands.

That said, appearing in those cited sources still matters a great deal. If your brand is consistently featured in relevant, high-authority publications like The New York Times, it increases the likelihood that AI systems will surface your brand in their responses over time. In other words, you may not receive a direct citation, but you benefit from being part of the content that AI platforms trust and rely on.

Over time, your brand (say, American Express or Chase) becomes more likely to be included in AI responses to queries like “best credit cards,” especially if it consistently appears in trusted sources.

AI platforms use citations to validate their answers. Citations from top sources, such as industry publications, enhance credibility. Find where there’s a natural match between your customers and their audience, and publish the type of content people will want to link to.

5 Ways to improve your AI brand visibility

Now that you understand the metrics, here’s how to use insights from Yoast AI Brand Insights to improve your AI visibility.

Optimize for AI citations

AI platforms like Gemini, Perplexity, and ChatGPT use citations to validate their responses. So, citations increase the likelihood of your brand being included and trusted in AI-generated answers

Try to get featured on relevant, authoritative sites and publish guest posts on industry sites, news sites, or educational domains. Get mentioned in roundup articles, like “Top 10 tools for doing X”. Ask customers to write reviews on platforms like Capterra, G2, and Trustpilot. All of these tactics can act as proof that your brand is a well-trusted source. Remember, it must be relevant citations.

Make sure your content is structured so the AI can read it easily. Use clear, hierarchical headings and bullet points to make the content easy to scan. Add FAQs and publish direct answers to common questions. It is also a good idea to add schema markup to help the AI crawlers understand your content.

Don’t forget to update old content regularly. The AI platforms prioritize fresh, up-to-date information when retrieving sources, so refresh your content regularly to stay relevant.

Monitor and improve brand sentiment

By mentioning your brand, the AI platforms also shape how people see it. If those sentiments in the AI’s answers are negative, it can hurt your trustworthiness and cost conversions. This could signal the need for a broader reconsideration of business strategy priorities.

Once you find AI platforms associate your brand with negative terms (like “slow customer service”), respond to this issue publicly. For instance, you could contact customers on review sites to resolve complaints. You can also publish case studies and testimonials to steer the AI towards positive perceptions.

In your monitoring, you’ll also find the positive terms AI platforms associate with your brand, such as “trusted” or “innovative”. Use these terms in your marketing, in your site content, and on social media.

The weekly scans in Yoast AI Brand Insights track sentiment shifts for your queries over time. If sentiment drops, investigate the cause, like a recent PR issue or a product recall.

Benchmark against competitors

AI visibility is also about how you compare to the competition. If they are mentioned more often or in a better light than you, they will appear more often in recommendations made by AI platforms.

See how your brand stacks up against competitors. Use Yoast’s Competitor ranking tab to see which brands show up a lot in AI answers. Analyze their content strategy. Do they publish more case studies? Are they active on review sites?

This tool shows how AI describes your brand compared to others in your market. For example, if you’re a coffee company like Taylor’s of Harrogate, you might find that Lavazza is consistently labeled as “the Italian espresso expert.” Now you know exactly what to highlight, whether it’s your heritage, roasting process, or sustainability, to stand out. Use these insights to sharpen your messaging and compete more effectively.

Don’t forget to check your weekly competitor analyses to see if your AI visibility is improving. Double down on the strategy that works for you. The tool also includes an historical view. This lets you look back at earlier analyses by selecting a past date, helping you compare visibility and sentiment across different points in time.

Answer brand-specific questions

AI platforms are very good at answering specific questions, such as “Is brand X reliable?” or “What’s the best tool to do Y?” You’re missing out on a lot of potential customers when your brand isn’t in these answers.

Yoast AI Brand Insights suggests queries you should monitor based on your input, such as “Is [Your Brand] good for small businesses?” In addition, do deep research into the common questions asked in your industry using tools like AnswerThePublic, AlsoAsked, or simply by checking Google’s People Also Ask section.

With the insights gathered, publish blog posts, FAQs, or landing pages and directly answer those brand-related queries. Support the content with properly structured data, such as FAQ and how-to schema, to give AI platforms more tools to understand your content.

In Yoast AI Brand Insights, track which questions get the most mentions from AI platforms. Don’t forget to keep your content up to date to keep it accurate and relevant.

Track progress with the AI Visibility Index

Improving the AI visibility of your brand isn’t a one-time task, but a recurring effort. Luckily, Yoast’s AI Visibility Index gives you an easy-to-understand metric that you can use to track your progress over time.

Run your first scan to establish the starting point for your AI Visibility Index. Note which areas, like citations or sentiment, are strongest and weakest.

Yoast AI Brand Insights runs weekly scans. Please review them to track progress. Check the historical view, but remember these cannot be viewed together. Select the week before and then reselect this week to spot changes. Look for trends, such as improvements in sentiment or a sudden increase in citations.

If your score doesn’t improve, revisit the strategies above, such as optimizing for citations and improving sentiment. Be sure to experiment with new tactics and publish original research to secure more earned media.

How to influence LLMs to mention your brand

Imagine this: A potential customer asks ChatGPT, “What’s the best CRM for small businesses?” If your brand isn’t mentioned in the answer, you’ve lost a customer before they even knew you existed.

LLMs like ChatGPT, Gemini, and Perplexity don’t just pull answers out of thin air. They rely on data, citations, and patterns to generate responses. If your brand isn’t part of those patterns, it’s far less likely to be mentioned, no matter how well you rank on Google.

Publish authoritative content

LLMs are looking for well-structured, factually accurate content. These AI platforms love sources that provide unique insights or expert opinions, so be sure to focus on that.

Start with original research. Publish surveys, case studies, or industry reports with unique data. For example, “2026 State of [Your Industry] Report: Key Trends and Insights” positions your brand as an authority and gives AI platforms a reason to cite you.

Use the proven inverted pyramid structure in your content. Start with the most important information, like key findings and conclusions, follow with supporting details, and end with background information. This makes it easier for AI to extract, digest, and use your content.

Don’t forget to optimize for facts. Include statistics, quotes from experts, and actionable insights. For example, instead of “Our tool is great for marketers,” say “Our tool increased conversion rates by 30% for 500+ marketers in 2025, according to our latest case study.”

For example, HubSpot built its authority by publishing ultimate guides, like “The Ultimate Guide to Inbound Marketing.” These guides became go-to resources for marketers, earning backlinks from industry blogs, news sites, and even competitors. As a result, HubSpot is now frequently cited in AI responses about marketing tools.

Get mentioned on relevant, high-authority sites

LLMs trust reputable sources like industry publications, news sites, and review platforms. The more your brand is mentioned on these sites, the more likely it is to appear in AI responses. Please keep in mind that relevance is key here. For instance, if Yoast gets mentioned in Gardeners’ World or Home and Garden, it will do little to nothing for our brand. Find the most important and relevant sources and focus on those.

Pitch stories to journalists or industry blogs. For example, try to get featured in “Top 10 [Your Industry] Tools in 2026” lists.

Encourage customers to leave reviews on G2, Capterra, Trustpilot, or Google Reviews. Don’t forget to respond to (negative) reviews to show engagement and transparency.

If possible, try to reach out to sites like HubSpot, Search Engine Journal, or industry-specific blogs and ask to write for them. Be sure to include a bio with your brand name to reinforce recognition.

Optimize for conversational queries

LLMs are designed to answer natural language questions. This means you have to optimize your content for conversational queries. Conversational queries are things like “What’s the best CRM for startups?” rather than “best CRM”.

In your content, you should use question-focused headings. For example, answer the question “Is [Your Brand] good for small businesses?” directly in the first paragraph to make it clear and easy to understand.

LLMs often answer long-tail questions, so you should target long-tail keywords. For example, instead of “project management tool,” target “best project management tool for remote teams in 2026.”

In support of all of this, create FAQ pages with schema markup to help AI better understand your content.

Build citations

Build up a network of high-quality mentions that reinforce your brand’s authority. The more high-quality, relevant citations you have, the more likely LLMs are to mention your brand.

Publish assets like ultimate guides, templates, or tools that others want to reference and link to. For example, “The Ultimate Guide to [Your Industry] in 2026.”

Reach out to bloggers, journalists, and influencers to reference your content. For example, “We noticed you mentioned [Competitor] in your article. Here’s why [Your Brand] might be a better fit.”

Get featured in press releases, podcasts, or webinars. For example, “[Your Brand] Announces Groundbreaking Feature for [Industry].”

Make sure AI crawlers can reach your site

It’s important to ensure that AI crawlers can discover and index your content. If your site is invisible to them for whatever reason, your brand won’t appear in AI responses.

Your site should be technically sound, but you can also help LLMs in other ways. Make sure your site loads fast and is mobile-friendly. Use clean URLs, good meta tags and descriptions, and alt text for images. Also, use schema on your site to help AI crawlers understand what your site is about and how it all ties together.

In Yoast SEO, you can activate an llms.txt file. This proposed standard helps point AI crawlers to your most important content. Also, check whether your robots.txt file inadvertently blocks AI crawlers from accessing your content.

Be active in online communities

LLMs are trained on and can retrieve information from forums, social media, and community platforms such as Reddit, Quora, and LinkedIn. It can improve your brand’s visibility on AI platforms if you participate there.

Answer questions on Quora and Reddit. Provide valuable, non-promotional answers that naturally mention your brand. For example, “As a [Your Industry] expert, I recommend [Your Brand] because…”

Join discussions on Slack, Discord, or niche forums. Share insights and link to your content when relevant. Post thought leadership content on LinkedIn, Twitter, or Facebook. For example, “Here’s why [Your Industry] is changing in 2026, and how [Your Brand] is leading the way.”

The future of brand visibility is AI-driven

We’ve seen that AI is changing how people discover brands. There’s a simple rule: if your brand isn’t visible in AI responses, you are missing out on an ever-growing audience.

Luckily, Yoast AI Brand Insights gives you the tools to:

• Track mentions, sentiment, and citations across AI platforms
• Benchmark against competitors to identify gaps
• Optimize for high-intent queries to capture more attention
• Monitor progress with the AI Visibility Index

Plus, we have more tips to help you optimize your content for AI LLM comprehension using Yoast’s tools.

Ready to take control of your AI brand visibility?

AI is the future of search, and brands that adapt early will win the race for AI visibility. Don’t wait for your competitors to take the lead.

Start by running your first scan in Yoast AI Brand Insights. Identify your weak spots, implement these strategies, and watch your AI visibility grow.

The time to act is now, so start your brand’s future in AI today.

The post 5 ways to improve your AI brand visibility (Using Yoast AI Brand Insights) appeared first on Yoast.

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Eligible Yoast customers can now run a free Yoast AI Brand Insights scan and get a personalized report showing how ChatGPT, Perplexity, and Gemini see your brand. Your brand is part of the AI conversation whether you’re monitoring it or not. Yoast AI Brand Insights, part of the Yoast SEO AI+ plan gives you visibility into what AI tools say about you, how often you appear, and whether the picture they paint matches reality. To help you see that for yourself, we’re offering eligible customers a free, one-time scan. 

What you’ll see

• Your AI Visibility Index: a clear score showing how present your brand is across ChatGPT, Perplexity, and Gemini 
• Sentiment analysis: whether AI describes you positively, neutrally, or in a way that needs attention 
• Competitor benchmarking: how often your competitors appear alongside you, so you know where you stand 
• Citation tracking: which sources AI is drawing on when it talks about your brand 

How it works

Add your brand details, set your location, and generate your queries. Your personalized report is ready in minutes.

Who is eligible

Existing customers on one of the following plans can log in and try a brand scan for free today.

• Yoast SEO Premium 
• Yoast WooCommerce SEO 
• Yoast SEO Google Docs add-on 

Look out for your invitation inside the product the next time you log in. 

Claim your free scan for the Yoast AI Brand Insights tool from your MyYoast. 

The post See how your brand appears in AI-generated answers, for free appeared first on Yoast.

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