How to Measure and Maximize Your AI Visibility

AI has completely changed the digital landscape as we know it. An industry that once largely ran on Google’s 10 blue links now relies on personalized prompts and direct answers from AI answer engines.

This shift presents a unique challenge for brands, as workflows have evolved and the way success is measured has transformed. Today, driving success means prioritizing visibility across all search experiences and striving for improved mentions and citations within AI responses.

This transformation begs a key question: How can brands measure and maximize their presence in AI-driven environments?

Dive into our comprehensive guide to understand the critical factors that impact your AI visibility, explore actionable steps to help you maximize it, and learn how to monitor your brand’s digital presence for the long haul.

What is AI visibility, and why is it important?

AI visibility refers to how your brand appears in AI search experiences. These experiences could be chatbots, like ChatGPT, Claude, and Gemini, or it could be AI search experiences like Google’s AI Overviews and AI Mode and Perplexity. For brands, the goal of AI visibility is to understand how AI sees your brand, content, and products, and how your brand appears if it's mentioned or cited in an AI response.

AI visibility is critical for brands to consider because a growing number of people are choosing to find their information through AI search these days. AI directly answers personalized user questions, making the process of discovering information. As AI’s popularity grows, traditional search on engines like Google and Bing will continue to decline, and brands will need to adapt and improve their AI visibility, or risk being invisible in search going forward.

What makes AI visibility different from traditional search visibility?

Traditional search engine optimization (SEO) often focuses on optimizing for keywords, achieving high rankings in organic search results, and driving organic traffic through clicks on search engine results pages (SERPs). While these aspects remain relevant, AI visibility introduces new considerations.

In AI search, the objective shifts from securing a top-ranking link to becoming the trusted source that an AI model references and, in some cases, directly quotes.

The goal of your website isn’t really traffic anymore. The old funnel is kind of squishing right now. Everyone used to talk about different funnel stages, like educational, informational, consideration…

With AI search, there are only two funnel stages, educational and transactional. The goal is for the LLM to cite your brand, then ultimately people come to your site to buy something.

Is there a difference between optimizing for AI Overviews and answer engines?

No. There’s no real difference between optimizing for AI Overviews and answer engines. Again, your goals in AEO are very similar to your goals in SEO. You need to create high-quality, authoritative content that aligns with your user intent and provides your unique topical expertise. If that sounds familiar, it’s because it’s largely what you were doing for SEO.

Optimizing for LLMs or AI Overviews aligns with traditional SEO best practices. The fundamentals haven’t changed: create helpful content, structure it properly, and build brand authority. Do that, and you’ll show up in both search results and AI-driven answers. Stop overcomplicating it.

In short, if you’re optimizing for visibility on answer engines, you’re optimizing for AIO visibility, as well as SEO. Like Zack said, stop overcomplicating it.

Key factors that impact your AI visibility

To maximize your brand’s AI visibility, you first need to understand how AI platforms discover and present content and what factors within your site and content could impact that discovery.

Again, nobody knows for sure every factor that will play into your AI visibility, but we do know enough to help you get started with your site optimizations. Keep an eye on these factors when you’re focusing on AI visibility.

Content quality and authority

Just like with SEO, high-quality, authoritative content is the cornerstone of AI visibility. AI models prioritize content that is accurate, comprehensive, and well-researched. The more easily an AI model can summarize and cite your content as a reliable source, the more likely it is to appear in AI-generated answers. Focus on creating in-depth, original content that truly answers user questions and demonstrates proven insight.

Example

Say that you create content for a financial institution’s website. You notice that your competitors have content around retirement accounts for freelance professionals in 2025 and you decide to create some of your own. If your content doesn’t establish your authority and thoroughly answer your audience’s questions, it’s unlikely to get mentioned or cited above the competition. Especially for a high-stakes Your Money or Your Life (YMYL) query, AI will prioritize expertise, trustworthiness, and factual accuracy to provide a safe and reliable answer.

Authorship & expertise

AI models value content that originates from credible sources and showcases genuine human expertise. This aligns with Google’s E-E-A-T guidelines (Experience, Expertise, Authoritativeness, and Trustworthiness). Clearly attributing authors with relevant credentials and ensuring your content reflects unique points of view from experts within your organization can significantly boost your content’s standing with AI.

Your brand authority and internal expertise are imperative for AI visibility. Creating helpful and relevant content is important, but what does helpful really mean? Better phrasing is: specificity, brevity, and clarity. Being as specific as possible, with your own POV or a certain data point that your brand has, is really important now.

Example

Let’s say you run a travel & hospitality site that not only helps people book their vacations, but also provides helpful content and guides around things like trip-planning basics, packing for children, and best romantic getaways. Your content is great, but you don’t have dedicated author pages on your site that establish who is writing your content, what their credentials are, and where their expertise lies. AI model will prioritize the content that demonstrates true E-E-A-T, and in this case, the AI doesn’t have a chance to understand the author's deep, hands-on Experience as a form of expertise.

User intent and content relevance

AI models strive to match content not just to specific keywords, but to the nuanced intent behind a user’s query and the broader conversational context. Content that anticipates and addresses user needs by answering questions directly and comprehensively will be favored over more generic, less semantically relevant content.

This comes back to the idea of understanding your audience’s true intent, which allows you to create more relevant and impactful content for both AI and your audience.

Example

Imagine you’re running that same travel & hospitality site and you have an article around the 10 best Caribbean resorts for families, but the intent of the page is more to drive bookings than to provide information on which resort is best and why. 

As constructed, this page isn’t relevant to any visitor who is still planning their vacation, which will negatively impact its AI visibility.

Earned media from reputable sites

Consistent, high-quality mentions of your brand across the web signal relevance and trustworthiness to AI. Similar to how backlinks historically functioned for traditional SEO, frequent and positive citations of your brand or content from reputable sources can indicate authority to AI models. Actively working to secure legitimate brand mentions helps build this crucial signal.

Example

Say you created an exclusive data-driven report for your B2B SaaS website. After you publish it, multiple outlets link back to your content and cite your brand name. Those sites are incentivized to feature your research and data because it’s exclusive to your brand and expertise. From there, you benefit from the increased exposure, brand mentions, and backlinks.

User experience

Although AI models don’t "browse" your website in the same way a human does, a strong user experience (UX) does indirectly impact your AI visibility. Like search engines, AI models crawl your website content to understand your brand and expertise. Poor UX will lead to fewer frequent website crawls.

A fast, mobile-friendly, and well-structured website signals quality and trustworthiness to traditional search engines, which in turn influences how AI models perceive your site's overall credibility and usefulness as a source.

Example

Using our same travel and hospitality site example. Let’s say your site runs really well on desktop, but on mobile, images load improperly, and the page populates in a way that requires awkward scrolling to read site content.

Compare that to a competitor site that has a strong mobile and desktop experience. Which site do you think an answer engine will be more likely to highlight on mobile experiences, and how might that impact how AI views that content and your site, going forward?

Content structure

Well-structured content with clear headings, subheadings, bullet points, and concise paragraphs is much easier for AI models to parse, understand, and extract key information from. This on-page optimization is crucial for AI to quickly grasp the essence of your content and effectively summarize or cite it in responses.

Another important content structure consideration is Schema markup . Structured data, or Schema markup, is a format that gives search and answer engines explicit information about your page and its content. This makes it much easier for search engine and AI bots to crawl and understand your site’s content. The faster your content can be crawled, the faster it can be sourced, mentioned, and cited in search.

Breaking down complex topics into digestible sections with bullets and clear H2s, H3s, and so on enhances AI’s ability to understand and leverage your content.

Example

Let’s say you run that same travel & hospitality site and you just published an in-depth article comparing three popular family-friendly resorts. The article is full of helpful, first-hand information from restaurant details to kids accommodations.

But you have all of that information in several large blocks of text with few paragraph breaks, minimal H2s, and no Schema markup. That makes it difficult for both humans and AI bots to read and understand.

Clear headings make it easy for readers to comb through an article to find the information they need. Plus, nobody wants to try and remember where they were while reading through a block of text, it’s poor UX. It also makes it easier for AI bots to crawl your page, understand its purpose, and decide whether to use it as a source.

How to measure your AI visibility?

Measuring your AI visibility comes down to tracking and understanding how your brand is mentioned, cited, and summarized in AI search. Success in search is no longer about rankings and organic traffic; brands need to adapt and redefine how they measure their performance in search.

Understanding and tracking your AI presence

In a world where AI engines often provide direct answers, traditional organic search metrics don’t tell the full story anymore. Instead, focus on tracking direct mentions, direct citations, summaries of your content, and the sentiment of those mentions within AI responses.

This assessment provides a clearer picture of your AI presence and offers greater direction on what opportunities to prioritize in order to maximize your visibility.

Manual AI visibility tracking methods

Again, just like in traditional SEO, there are some DIY ways that brands can start to get a sense of their AI visibility. Specifically, you can directly query AI models to see if you appear. Enter common questions related to your industry, products, or services into AI platforms like ChatGPT, Perplexity, Gemini, and AI Mode, and take note of which brands and offerings are mentioned. Then, keep a record of which queries resulted in a mention, the context of the mention, and whether your brand was a primary source.

This will give you a solid starting point in understanding your visibility, but it’s not a scalable solution. This method doesn’t give you a full picture of your performance, only offering insights into how you’re performing in that moment for specific queries. Long-term, to understand your AI visibility at scale, you’ll need a dedicated tool or platform to keep track of it.

Getting your brand to show up in AI search is really going to come down to whether or not you have a technology that can give you visibility into where you're mentioned and where you're cited by AI.

AI visibility measurement tool examples

AI visibility tools allow you to measure and understand your presence in AI search at speed and scale, making them essential for brands both large and small. The most impactful AI visibility tools should have some, and preferably all, of the following capabilities:

• Real-time AI search performance tracking: Monitor how your brand appears in AI search, including AI Overviews and LLM responses.
• Citation analysis: Identify when and how your content is cited by AI models.
• Competitive intelligence: Compare your AI visibility against competitors to identify gaps and opportunities.
• Topic-level insights: Understand which topics your brand is considered authoritative on by AI.
• Automated alerts: Receive notifications when your content is mentioned or if there are significant changes in your AI presence.

It feels like every day, a new AI brand tracking and visibility tool or start-up hits the market, but how do you know which actually delivers on their promises? Below are some details about a few of the top players in the space, but be sure to dive deep into each platform and tool's capabilities to see which one best meets your specific organizational needs.

Several tools and platforms are now available to measure and maximize AI visibility for small and enterprise-level companies. Below are some details about a few of the top players in the space, as well as some rankings broken down by use case that we created with the help of ChatGPT. Since we’re comparing our own solution against other top tech, there’s an inherent Conductor bias here that we’d like to acknowledge, but we’re confident that our unique features and holistic platform are the top offering on the market.

Best AI visibility for enterprise

Conductor: For enterprise-level teams, your AI strategy can’t be siloed across teams and workflows. It needs to be a part of a holistic website optimization, SEO, and AI search strategy where AI search visibility is key. Conductor is the only platform with a unified view of your entire website, from AI mentions and keywords to traffic, conversions, impressions, and technical health.

Best AI visibility tool for SMB

Geneo : For small-to-medium-sized businesses, startups, or teams just beginning to invest in AI visibility, Geneo stands out. Its competitive pricing, including a free starting tier, makes it easy for teams of any size to get started. Plus, Geneo excels at providing actionable content suggestions based on its analysis, helping teams move quickly from insight to impact without draining resources.

Best overall AI visibility tool

Conductor: Conductor combines 10+ years of search intelligence data with comprehensive AI search performance insights, and a powerful AI-driven content creation engine, all within a unified platform that also manages traditional SEO and technical health. Designed for the entire marketing organization, Conductor is the most complete offering for businesses serious about mastering their total digital presence.

Honorable mention

Athena : Athena has established itself as a powerful and dedicated "Generative Engine Optimization" (GEO) platform, offering robust monitoring across a wide range of LLMs and providing deep analytics. For companies seeking a strong, specialized tool focused purely on the AI search landscape, AthenaHQ is a top contender.

Visibility in AI is all about being hyper-focused on your users and understanding your users, and we, as a platform, are leveraging large language models in order to simulate this empathy for you, so to make sure you're visible, and you're resonating with the needs of your audience.

Interpreting your AI visibility

Once you gather data, interpreting your AI visibility means looking beyond mentions. Consider the following insights, too:

• Direct citations vs. summarized answers: Is the AI directly quoting or linking to your content, or just summarizing information found on your site without explicit citation? Direct citations can indicate stronger authority, but aren’t necessarily more valuable than mentions. Think of mentions as a billboard ad; it’s tough to track the actual purchases driven by the billboard, but it’s still a valuable brand recognition opportunity.
• Sentiment of mentions: Is your brand mentioned in a positive, neutral, or negative light? The sentiment of the mention provides context for how the AI sees your site and content.
• Frequency and prominence: How often is your brand mentioned, and how prominent is that mention within the AI's response?
• Competitive benchmarking: How does your AI visibility compare to key competitors? Are they being cited for topics where you also have strong content?
• Share of voice for key topics: Tracking your share of voice for a given topic involves tracking the total number of citations and mentions across a set of relevant queries and determining what percentage belongs to you versus your competitors. A low share of voice on a core business topic, even with some mentions, means you have an opportunity to build more authority.

Both mentions and citations are important, but I actually think that getting mentioned is probably more important than getting cited, because people don't look at the citations on AI responses that much. Oftentimes, citations are hidden at the bottom, or on the sidebar on the right-hand side of the page.

You’re relying on someone scrolling the rest of the page to see the citation, to see you. However, as a user, I am reading the AI response, for sure. It’s almost like you’re seeing a billboard or a commercial. Brand awareness is pretty big in AI search right now.

Understanding these nuances helps you refine your content strategy to maximize the quality and impact of your AI mentions.

Steps to improve your AI visibility

Improving your AI visibility requires a two-pronged approach, combining robust content strategies with essential technical optimizations.

Content strategies to improve AI visibility

To start, let’s get into some of the content-focused strategies you can employ to improve AI visibility.

Highlight your unique expertise in specific and authoritative content

Google’s helpful content system and E-E-A-T principles remain highly relevant for AI search. Remember what Pat said earlier and prioritize creating highly specific and relevant content that provides comprehensive, accurate, and unique information. The more expertise your content shows, the better its chances of being recognized and cited by AI.

Optimizing for LLMs is not that different from a traditional search engine. You just have to be more targeted. The best way to optimize is to be original. Do this by having folks in your organization provide a unique POV on a relevant topic.

This should be the focus because that is what all of these LLMs and answer engines are trying to do: connect real people with real experts’ opinions. Because AI doesn't make things up yet, right? It just regurgitates and stitches things together that already exist.

Example

You’re writing a data-driven research report for a B2B tech company around customer behavior and market trends in the SaaS space. You publish it to your site, knowing that you satisfied user intent and answered relevant questions, but you also decide to drop in a few pro tips on how to interpret the information and how to create actionable strategies based on the data you provided. You offer unique, relevant insights that help inform your audience’s strategy while also providing them with actionable tips from a seasoned professional.

Your specific expertise should be your brand’s stamp or signature. Let your readers know exactly who you are, what your experience is, and why you’re uniquely qualified to help them. In other words, be authentic.

Prioritize satisfying user intent

Go beyond keywords; they aren’t telling you the whole story. In order to create content that resonates with AI and audiences, you need to understand the underlying questions and goals of your audience and predict their future needs.

Your content should aim to fully satisfy user intent by providing direct, clear answers to common questions and comprehensively addressing related subtopics. When your content directly answers what users are looking for, AI models are more likely to present it as a solution.

Example

Using our same travel & hospitality example, let’s you create a piece of content on how to the 10 best US cities to travel to on a budget, and during your research, you notice that a common question is: Which US cities are the most walkable/pedestrian-friendly? Which makes sense for your target audience, if a city is more walkable, tourists are less likely to need to spend money on cabs and fuel.

Despite noticing this as a common question, you publish your guide without answering this question. Now, you’re content is not only providing your audience a less helpful piece of content, but it’s much less likely that AI will mention or cite your content, because it doesn’t fully answer the question, and therefore, can’t be fully summarized in an AI response.

Structure your content for readability and crawlability

Optimizing for on-page SEO fundamentals is crucial for AI. Use clear headings (H1, H2, H3) and subheadings to organize your content logically. Incorporate bulleted or numbered lists to present information concisely, and keep paragraphs short—ideally no more than four to five sentences.

This structure makes it easier for AI models to parse, understand, and summarize your information effectively. It also makes it easier for AI bots to crawl your content and understand it. Like with SEO, the easier your site is to crawl, the faster the model can understand the purpose of the content, what questions it answers, and whether it’s going to pull information from the content. In short, you need to ensure your website is optimized for humans and AI.

Example

Take a look at the screenshots above of an AI Overview and one of our own academy articles Google used to source the output. You’ll see that it surfaces the insights in a clearly broken down and digestible format, complete with clear headers and subheads in a bullet list. It even pulls information, including headers, directly from the article source.

Now, imagine that you have a similar page that answers this same question, but it does so in a large block of text with multiple sentences. Your formatting structure makes it more difficult for both audiences and AI models to understand and summarize your content, making it much more likely for the AI to highlight someone else’s content and effectively making you invisible for this query.

Leverage a human-in-the-loop approach when creating content

While AI writing assistants can significantly boost content creation efficiency, human oversight is 100% required. To ensure your content has the best chance of being mentioned or cited in AI search, always ensure a human thoroughly reviews all AI-generated work. But this also goes beyond basic visibility concerns. Since AI models are known to hallucinate and completely fabricate information, if you don’t have a human-in-the-loop of your AI content creation, then you’re opening yourself up to significant risks to your brand. Publishing content with incorrect or biased information can cause your brand to lose the authority and expertise you’ve worked so hard to build.

A human-in-the-loop approach guarantees accuracy, introduces unique perspectives, maintains brand voice, and ensures transparency. AI should be a powerful assistant, not a complete replacement for human creativity and judgment.

Example

Using our travel example, let’s say that you are promoting a new best-seller at your shop, and you use AI to write a quick summary to add to your site. You publish the blurb without reading it, and the AI has managed to misrepresent the author’s name, as well as get key plot details incorrect in the blurb.

In this scenario, your content will be very unlikely to appear in AI search, simply because the content is incorrect. Make sure you have a human review ALL AI content before publishing.

Expand digital PR (AKA earned media)

Strategic public relations plays can also significantly boost your brand’s AI visibility. By earning high-quality brand mentions and backlinks from authoritative publications, platforms, and influencers, you increase your content’s authority and citation velocity across the web, which signals trustworthiness and relevance to AI models, making your brand more likely to be cited.

You can do this in a number of ways, including:

• Publish original research and data: If you can provide content that has exclusive research, data, or expert viewpoint, like our 2025 AI Search Trends Report, it means other outlets have to download and cite your research, which helps establish your expertise and domain and topical authority.
• Promote expert sources and thought-leadership: This idea ties back to Pat’s quote about ensuring your content is providing a unique POV. How can you create content that nobody else can? Leverage your internal subject matter experts and contact prominent influencers and thought-leaders outside your organization to create one-of-a-kind content. For example, if a fintech company published an annual State of Household Savings Report, it would provide a much more unique perspective if it included quotes from the company’s CFO and other financial experts.
• Develop strategic guest content: Write bylined articles for respected industry publications rather than just your own blog. This directly associates your brand and authors with a platform that’s already developed it’s own authority. Imagine the head of your cybersecurity firm contributed an article for a major tech journal about the future of AI in threat detection. This establishes their personal expertise and boosts your company’s visibility.

Traditional link building is changing to digital PR. This is the right way to build links. A lot of great companies have already been doing this for a while.

Yet, I still see so many wasting money on buying links every month. Everyone should stop that immediately.

Think of link building more as a brand authority-building play and work with your content and marketing teams to create these opportunities.

Technical strategies to improve AI visibility

If your website isn’t technically sound, users won’t want to visit, and search engines won’t surface it. The following technical website strategies are key to improving your user experience and AI visibility.

Leverage Schema

Leveraging Schema helps AI understand the context and purpose of your content, making it more likely to be mentioned, summarized, or cited in AI search. Since Schema is basically just your site’s raw data, it makes it much easier for an LLM to access your site, grab what it needs, and spin up an answer.

Some kinds of Schema you should consider leveraging include:

• Organization Schema: Essentially your organization’s digital name tag. This identifies your website as being run by a legitimate organization and establishes authority.
• Person/Author Schema: This identifies the human author of a piece of content. It is critical for demonstrating expertise because it proves your content was written by a real person with credentials and a digital footprint.
• Article Schema: This Schema structures your content itself, clearly establishing headings, publication date, and connecting the article to an organization and author.
• HowTo Schema: A common question answer engines get is “how to” complete a given task. HowTo Schema structures step-by-step instructions for a process into a clean, logical sequence that the AI can easily reformat into a list for the user.
• Product Schema: Provides detailed, structured information about a specific product. This allows the AI to pull facts like price, availability, and ratings directly from the page data, so it can confidently answer questions like: How much does X product cost?

This list isn’t exhaustive; there are plenty of other kinds of Schema markup that may make sense for you to leverage on your site. Do some research on what may work best for you, but make sure you leverage it somehow, because Schema is critical for AI visibility.

I think Schema markup is the number one [technical factor to prioritize]. Schema markup is raw data, so you could actually put your raw data right into Schema. Then, LLMs may go and just use your schema markup versus looking through your entire page.

And you know what? [That sends a signal to the LLM that] ‘these folks have this structure. It’s very quick for me. I’ll come back here.’ Because they’ll recognize that this site has a good schema structure. LLMs just want to come in, get the answer, and leave, right? So the easier we can make that, the better off we’ll be.

Example

Author Schema is a fairly common form of Schema. Our travel & hospitality website could significantly improve its AI visibility by implementing author Schema on its website, because it allows search engines and AI platforms to associate a piece of content with a real person and verify their credentials and expertise through their other content. This also ties a specific author to a specific organization, which also helps to reinforce expertise and topical and domain authority.

For instance, by marking up a classic chocolate chip cookie recipe with structured data, the bakery can enable voice assistants like Google Assistant or Siri to directly read out the recipe steps when a user asks for a cookie recipe.

Monitor your website for technical issues

Very similar to traditional SEO, technical issues on your website can seriously harm your AI visibility. Make sure that your site runs smoothly, is easily crawlable, and is free of broken links or server errors.

Just like in traditional SEO, the goal of AI search is to give users the answers or resources they need to solve their problems. They want to be as helpful as possible, and sending someone to a broken link or slow-moving site isn’t very helpful.

That means that manual monitoring isn’t going to cut it anymore no matter what size your site is. All of your other work will be for nothing if you have significant technical issues that are going undetected for any amount of time.

A well-maintained and technically sound website ensures that AI models can efficiently access and process your content, giving it the best chance of appearing in AI search. Conductor Website Monitoring helps you maximize your website’s potential and limit the risks of technical issues, at any scale. 24/7 website monitoring surfaces issues, changes, and optimization opportunities in real-time so you can resolve them before your revenue and reputation take a hit.

Improve your site’s UX

Strong site UX indirectly helps your AI visibility. Search engines factor UX signals like bounce rate and time on page into their ranking algorithms. A fast, intuitive, and mobile-responsive website improves UX, and also signals to search engines that your site is a valuable and trustworthy resource, which can positively influence how AI models perceive its quality.

Example

These UX and technical monitoring sections have some overlap, so we’ll tackle one example for both.

Say that you run a fintech website that specializes in consumer loans and mortgages. One day, you notice that multiple links on your site are broken and are returning 404 errors to all visitors. You don’t notice the issue immediately, so it remains, blocking users from navigating to pages, booking calls with your sales team, and ultimately converting. Not only is this frustrating for users, but it’s also actively costing you conversions and visibility. Instead of contending with a broken link, your audience will go to a competitor to get the financial help they need. These technical issues will also signal to search and answer engines that your site isn’t as authoritative as your competitors' with technically sound sites.

Prioritize LLM accessibility

If you want your content to appear in AI search, you need to first make sure that it’s accessible to LLM crawlers. That means ensuring that all of your content, including guides and reports that are usually gated to drive downloads, is crawlable by LLMs.

A lot of the optimization methods we’ve covered already will positively impact your LLM accessibility. For instance, a clear content structure, Schema markup, and UX all help make your site more accessible to LLMs. Some other methods include:

• Include citations and external sources to establish expertise: Just like you would do with SEO, citing an expert source helps establish your credibility.
• Improve load speed & mobile accessibility: Optimizing your website’s performance makes it easier for AI bots to crawl your website properly and efficiently. It also helps improve UX. if your site runs quickly and smoothly, it sends positive signals to search engines.
• Leverage robots.txt: Robots.txt is used to control how web crawlers access specific parts of a website, highlighting content to crawl first, and noting content that shouldn’t be crawled. If your robots.txt file accidentally blocks one of Google’s crawlers, your content may be invisible to AI Overviews and other Google AI search experiences.
• Leverage llms.txt: LLMs.txt aims to give website owners specific control over the use of their content as training data for LLMs. With llms.txt, you can allow bots to crawl your site for real-time search answers, while also blocking bots from using that content to train their models. This helps you actively manage how you’re appearing in search, while also protecting your brand.

While many brands rely on gating content for lead generation, blocking AI crawlers from this valuable content can negatively impact your topical and domain authority, significantly reducing the chances of your brand being mentioned or cited. Instead of a hard gate, you could consider a hybrid approach and make portions of your content crawlable on your site, with clear opportunities for users to access the full version of the download. Plus, even if your content can be crawled by AI bots, you can still keep that content non-indexable to retain those form fills.

Example

Imagine you create content for a cybersecurity company, and you’re working on a data-driven report on security threats by industry. The content is strong and satisfies a user need, but if has a lot of unique and exclusive research that you want to gate in order to drive more downloads and leads.

But with AI search, gating your most valuable content and data may actually harm your authority and expertise. Think about it, if your best content is behind a gate and LLMs can’t crawl it, then your most expert, unique, and authoritative content is invisible to AI bots. Plus, enabling the content to be crawled in AI search helps generate earned media from sites who link to your page from their articles on topic.

AI visibility in review

Ultimately, improving your AI visibility is an ongoing process that requires a combination of strategic content creation and technical optimization. It’s a continuous process, and like SEO, we’ll likely never know for sure exactly how to optimize every aspect of our sites for AI visibility. But a good start is focusing on helpful, authoritative, and well-structured content, supported by a technically sound and accessible website.

About the authors

Conor Baker

Conor is a Marketing Copywriter at Conductor. He started his journey in Customer Success, where working directly with customers drove his passion for customer-first content. With several years of content experience, Conor is excited to help Conductor build the best content possible.

Read Conor's bio

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