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Increasing Brand Visibility in AI Search: How Authority Signals Drive AI Citations

To get your brand cited in AI search results, you need content that LLMs trust. That means earning placements on authoritative sites, not just optimizing owned content.


AI platforms like ChatGPT, Claude, and Perplexity heavily weigh third-party validation when deciding what to cite. In addition to having clear methodology and sourcing, content that appears in AI-generated answers often lives on websites with high domain ratings and is linked to by other high-authority sites.


Those placements could come via news articles published by journalists. But they could also come via earned distribution, where a brand’s owned content is syndicated by authoritative news sites.

Why Earned Media Drives Brand Mentions and Citations

If you want your brand to appear more frequently in AI search results, prioritize earned media.


Muck Rack’s research on what AI decides to cite has consistently found that more than 80% of AI citations come from earned media. Muck Rack defines “earned media” as journalistic articles, academic research, government and NGO sources, encyclopedic sites like Wikipedia, and third-party corporate content.


Meanwhile, Stacker’s March 2026 research with AI monitoring and measurement company Scrunch found that earned distribution produces a median 239% lift in AI search visibility. The two companies analyzed 87 stories published by 30 different companies and queried more than 2,600 prompts across 8 AI platforms in order to arrive at this conclusion.


AI platforms were trained on publications that have a long track record of accurate reporting and editorial independence, so it makes sense that LLMs would view these sources as credible authorities on a given topic. A brand publishing content that says positive things about itself would be seen as inherently less credible, while a third-party publication doing the same would be less so.


For PR teams, this means that placements on high-authority sites — or having your brand mentioned in articles published by reputable publications — are valuable to building AI visibility.


And for marketing teams building out robust owned content operations, this also suggests that distributing that content as earned media could support efforts to have your brand appear as an authority in AI search results.

Why Authority Signals Matter in AI Search Results

Gaining brand authority in AI search results depends on where your content lives as well as how many credible sites reinforce it.

There are two types of AI visibility: citations and mentions. Being cited means that the AI platform identifies your brand as a credible source, often including a link to an article. This signals that your brand has authority in the eyes of the LLM. Being mentioned but not cited means that the AI platform named your brand as part of its response, but it didn’t include a link. Being included in a response signals message reach, meaning that your brand’s narrative reached the user even if the brand wasn't directly cited.

The authority profile of where your brand appears is important to driving both citations and mentions. One way of measuring authority is by looking at domain rating, or DR. DR is a metric created by Ahrefs that grades a website’s authority on a scale of 0-100. It’s calculated by looking at how many domains link to a particular site and weighting those domains’ own DRs.


DR was created for SEO, but it’s relevant to GEO as well. LLMs don’t actually check DR, but they do make judgment calls about what content seems trustworthy. High-DR publications tend to be the sites that AI trusts the most — not because they have a high DR, but because they follow high editorial standards, use clear sourcing practices, and are frequently cited by other trusted sources (all of which helped them earn a high DR in the first place).


If your goal is for your brand to be mentioned by name (even without a link), domain diversity — or being placed on many different, high-authority sites — matters for maximizing reach. Semrush research has found that AI platforms treat information as more reliable when it appears across multiple authoritative domains. Each mention of your brand reinforces your messaging and expands the surface area where LLMs can encounter it.


Looking at DR can serve as a proxy to understand which earned placements contribute most to AI visibility. Getting placements on sites with higher DRs increases your chances of acquiring both mentions and citations.

How to Build Content LLMs Want to Cite

Stacker's research found that brand content cited by LLMs tends to be editorially selected, not paid promotion or optimized for keywords. That means owned content needs to earn its way into AI answers.


Here's what that looks like in practice:


  • Using data and research to back up claims
  • Having clear, easy-to-understand methodology
  • Structuring pieces so they’re easy to parse, using bullet points, numbered lists, subheadings, and FAQs where relevant
  • Including author bios on each post to establish credibility

Overall, content should uphold high editorial standards and not be promotional in nature.


Brand content teams also have distribution — like through Stacker’s earned distribution model — as a tool to build authority in AI search. Stacker found that syndicating content through a third-party newswire multiplies the number of high-authority sites citing your brand as a credible source on a particular topic, increasing the surface area where LLMs can encounter your brand. This compounds the third-party authority signals that LLMs look for when deciding what to cite.


Tracking where your content gets picked up — and the authority profile of those placements — is how you can measure how much your distribution efforts are moving the needle on AI visibility. Stacker’s model enables brands to distribute their content to high-authority sites and then measure how effectively that syndication boosts their AI visibility.