How AI Decides Which Brands to Trust 

AI search systems only surface brands they consider trustworthy, but how do you build that trust?

Is it like traditional SEO where link equity and logarithmic authority scores reign supreme?

The answer to that question is a definite no. 

Since LLMs are sophisticated enough to understand meaning, context, and relevance, they don’t need to rely on raw link metrics.  

Instead, they’re able to use trust signals like backlinks to establish a credibility narrative for your brand. 

Thus, some classic link-building tactics, like tiered link-building, no longer move the needle. 

Backlinks are still an important trust signal in AI search; it’s just more about contextual relevance than volume or authority scores. 

If you want to improve AI search visibility through link-building, you need to generate backlinks that demonstrate editorial depth on relevant, highly credible websites. 

In this post, we’ll break down how AI search systems decide which brands to trust, and how to optimize for the most important trust signals. 

Here’s what we’ll cover:

1. The top AI trust signals 
2. How link patterns influence AI understanding
3. Why tiered link-building doesn’t work with AI search 
4. Modern authority layers that matter for backlinks
5. How to build real trust for your brand moving into 2026 

What are the Top AI Trust Signals?

AI search systems treat brand authority as a multi-layered signal that encompasses brand mentions, editorial context, backlinks, reputation, and brand sentiment. 

In particular, there are seven primary trust signals that AI models use. 

Here’s a quick overview of them all:

1. Base ranking/core algorithm output – First, the AI system uses a traditional search engine algorithm to retrieve documents that relate to the user’s query. It’s essentially the ‘classic SEO’ layer that relies on familiar elements like content relevance, link authority signals, and on-page signals like keywords and metadata. You can think of this stage as the model’s ‘best guess’ at which documents satisfy the user query before the ‘fancier’ AI layers enter the picture. 
2. Gecko score (vector embeddings) – The Gecko score measures how close the query and each document are in semantic space. To do so, it uses embeddings in a vector database. Each embedding is a numerical representation of a chunk of meaning (words or parts of words).
3. Jetstream (cross-attention) – Vector search involves hard token limits, meaning content is ingested in short, self-contained sections. To ensure vital context isn’t lost, a cross-attention layer is applied. This is because embeddings are too coarse and often miss nuance like negation and contradictions. 
4. BM25 keyword matching – While embeddings and cross-attention are sophisticated, they can venture off topic. That’s why AI models continue to use classic lexical keyword matching via BM25. This helps ensure the results are truly relevant by grounding them in the language the user actually used in the prompt. 
5. PCTR (engagement signals) – These are classic engagement signals like dwell time, bounce rate, mobile-friendliness, and load speed. 
6. Freshness – AI models have a strong bias toward fresh content that’s frequently updated. They will check timestamps, schema markup, and current facts/terminology to determine which pieces of content are the most up to date. 
7. Boost/bury (business policies and safety overrides) – The last layer has to do with specific business policies. For instance, the model may boost results from brands the parent company partners with or views as highly authoritative. Brands with strong reputations and high credibility also receive ‘boosts’ during this stage. Conversely, the model will ‘bury’ content that violates safety guidelines and spam policies.

If you want to master AI search optimization, then you need your content to pass all these trust layers with flying colors. 

How Do Link Patterns Influence AI Understanding?

Before AI-powered search, you could build authority by generating large quantities of medium-quality backlinks. 

With the introduction of LLMs, there’s been a shift from raw link metrics to narrative credibility. 

In other words, instead of asking, “How many links does this site have?” an AI tool would want to know, “What story do these links tell?” 

In that sense, backlink quantity still matters, but only as long as each backlink is:

1. Editorially relevant and genuinely helpful 
2. From a credible, niche-adjacent website 

Therefore, if you’re able to build high-quality backlinks from lots of reputable sites, you’ll strengthen the idea that you’re the top authority figure in your field to AI models. 

Also, a backlink’s anchor text and surrounding copy help to shape the narrative. LLMs pay attention to anchors like ‘X explains’ and ‘X’s study shows’ to understand the ‘why’ behind the link. 

On a deeper level, AI models also consider the relevance of the linking domain. Ideally, your content should be topically aligned with the sites that link to you in some way. 

Next, certain link patterns help with entity clarity, which plays a huge role in AI search. 

LLMs use named entity recognition to identify and disambiguate key concepts, brands, people, organizations, and other entities. 

Once they’ve identified an entity, they’ll connect it to entries in knowledge databases to learn more information. For instance, by tying the brand entity Sony to database entries, AI models can retrieve information like:

• Core company attributes (founding date, headquarters, industry, and key personnel) 
• Products and major subsidiaries (PlayStation, Sony Music, etc.)  
• Relationships and facts 
• Connected entities at the edges of the graph (competitors, executives, related products, etc.) 

Entity recognition is how AI models are able to anchor their generated answers to concrete, verifiable facts. It also helps disambiguate similar terms, like distinguishing jaguar the animal from Jaguar the vehicle manufacturing company. 

Why Does Tiered Link-Building Not Work in AI Search?

We mentioned before that tiered link-building doesn’t provide any benefits for AI search visibility, but why is that?

It’s because what constitutes online authority has completely changed. 

Before AI systems, PageRank-style link signals were the primary way to establish authority and improve search rankings. 

Each hyperlink carried a certain amount of ‘link juice’ that passed authority to your site. Links from credible websites carried the most juice, but links from medium and even low-quality sites still carried some juice. 

Tiered link-building capitalized on this fact by artificially boosting the link juice of your top backlinks by building links that pointed at other links. 

Here’s a quick recap of the technique if you aren’t familiar:

1. Your most authoritative backlinks are tier 1 and point directly at your website. 
2. Medium-quality backlinks are tier 2 and point at your tier 1 links, not at your actual site. 
3. Lower quality backlinks are tier 3, and they direct to your tier 2 links, and so on. 

The reason why this system no longer works is that LLMs don’t count link graph signals. Therefore, any backlink that isn’t contextually relevant or from a credible website isn’t worth pursuing anymore. 

How Can Brands Build Real AI Trust in 2026?

Now that you know which trust signals and link patterns actually matter for AI search, let’s translate them into some real optimization tactics. 

Harness the power of editorial storytelling 

One of the most effective ways to build high-quality backlinks is to tell engaging stories that contain link-worthy assets. 

Here are some examples:

• Original data from in-house studies, surveys, and experiments (like ‘we found X by analyzing 100,000 ChatGPT responses’) 
• Framework posts that teach new information and skills (‘The 4-Step Guide to B2B GEO’) 
• Deep informative breakdowns for trending new topics (‘How do AI Overviews work?’) 

For each piece, use the narrative framework of:

1. Setup 
2. Challenge
3. Solution
4. Outcome

This type of storytelling-focused content can attract links without any outreach required. 

Speaking of outreach, you should take a story-based approach to it, too. 

When you reach out to journalists and media professionals, have an editorial angle in mind. Lead with trends you’ve spotted, counterintuitive findings, or unique case studies that present original narrative ideas. 

This approach is effective because you’re not just telling outreach targets that ‘you exist,’ you’re helping brainstorm engaging stories, which are exactly what they need.   

Focus on high-quality link acquisition over quantity   

Remember, quality matters more than quantity in AI search. For this reason, you should target a short list of high-value publications in your niche. 

These should be credible news outlets, expert blogs, podcasts, newsletters, and online communities that directly relate to your field of expertise. Irrelevant backlinks will be ignored, even if they’re from extremely authoritative domains. 

Granted, it’ll take more effort to earn links from these sources, but they’re worth the work. 

At the same time, you won’t have to worry about building hundreds of lower-quality links, so you’ll have more time to focus on the big targets. 

While medium-quality backlinks from social media sites and forum comments used to pass tiny amounts of link juice in PageRank-style systems, all they do now is inflate noise. 

Also, link insertions can still be enormously effective when done properly. As long as a link insertion genuinely enhances a piece of content on a credible domain, it’ll improve your authority on AI search platforms. 

Here are some effective ways to use link insertions:

1. Make sure they’re contextually relevant and not self-promoting 
2. Aim to enhance the narrative of a piece of content (like with relevant research, case studies, and free tools) 
3. Link to your products whenever it’s helpful to the audience to do so 

Concluding Takeaways: Brand Authority Signals and AI Trust Factors 

Online authority is no longer about how many links you have or how high your domain authority score is; it’s about editorial quality, context, and narrative depth. 

This means that your link-building campaigns should shift from raw link metrics to news coverage, editorial authority, and consistent brand mentions. 

Do you need help putting together a winning link-building campaign for your needs?

Check out ABC AI Plus, our fully managed link-building campaign service.