I’ve been doing SEO for 15 years. I understand Google’s trust signals - backlinks, domain authority, E-E-A-T, etc.
But AI search seems to work differently. Sites that should be “trusted” based on traditional metrics sometimes don’t appear in AI answers. Meanwhile, content from less authoritative domains gets cited.
What I’m trying to understand:
Looking for others who’ve studied this difference.
Emma, you’ve identified a crucial distinction. Let me break down what we know:
How AI trust differs from SEO trust:
| Traditional SEO | AI Systems |
|---|---|
| Backlinks = authority | Brand mentions = authority |
| Domain authority score | Citation diversity |
| PageRank-style algorithms | Semantic understanding |
| Keyword optimization | Content accuracy |
| Link building | Mention building |
What AI systems actually evaluate:
The key insight:
AI systems are trained on vast text corpora. They’ve learned patterns of what “authoritative” content looks like. A well-researched article with proper citations, expert authorship, and balanced perspective signals authority - not because of links, but because of content characteristics.
The “citation diversity” concept is interesting. So instead of building backlinks, we should focus on getting mentioned in more places?
How do you measure citation diversity? Is there a tool or methodology?
Measuring citation diversity:
There’s no single metric like Domain Authority. You need to assess:
Tools/methods:
The goal is building a web of mentions, not just links. When AI sees “multiple independent sources say X about [brand],” that builds trust.
I’ve spent years on Google’s E-E-A-T. Here’s how it translates (and doesn’t) to AI:
E-E-A-T components for AI:
Experience:
Expertise:
Authoritativeness:
Trustworthiness:
The biggest difference:
Google can crawl link graphs. AI can’t directly see links - it sees text patterns that indicate authority.
This is why Wikipedia is so powerful for AI. Being on Wikipedia signals “this entity is notable enough to have an encyclopedia entry.”
Practical content signals that build AI trust:
Content characteristics that signal authority:
Red flags that hurt trust:
The meta-signal:
AI has learned what “trustworthy content looks like” from millions of examples. Content that follows academic and journalistic conventions signals trust.
Write like Wikipedia, not like marketing copy.
PR perspective on building AI trust:
Media mentions are the new backlinks.
When journalists cite you as a source, AI systems see that as endorsement. It’s not about the link - it’s about the mention in a trusted context.
What works:
The difference:
Old PR: “Get a backlink from Forbes” New PR: “Get quoted as an expert in Forbes”
The quote builds AI trust whether it’s linked or not. AI reads the article and sees “[Expert] from [Company] says…” That’s the trust signal.
Something I’ve noticed: Author signals matter way more for AI than for Google.
Author authority for AI:
When your content has:
AI weighs this heavily. Anonymous or generic “Staff Writer” content performs worse in AI citations.
What we implemented:
The “person” behind the content matters. AI attributes trust to authors, not just domains.
Wikipedia editor here. Let me explain why Wikipedia matters for AI:
Why Wikipedia = AI trust:
What Wikipedia presence signals:
For companies seeking AI visibility:
Important: You cannot write your own Wikipedia article (conflict of interest). But you can ensure you have enough third-party coverage to BE notable enough for one.
I’ve analyzed trust signals across 1,000+ AI citations. Here’s the data:
Correlation with AI citation likelihood:
| Signal | Correlation |
|---|---|
| Wikipedia presence | 0.72 |
| Author credentials stated | 0.68 |
| Third-party mentions (non-promotional) | 0.71 |
| Content freshness (updated <6 months) | 0.54 |
| Structured data present | 0.47 |
| Domain authority (Moz) | 0.23 |
| Backlink count | 0.19 |
Key findings:
Implication:
Building for AI trust requires different investments than SEO. PR, author development, and Wikipedia notability matter more than link building.
Brand trust perspective:
AI systems develop “impressions” of brands.
Just like humans form impressions from what they read, AI systems form impressions from their training data and sources.
How AI perceives your brand:
If most mentions are:
Building positive AI brand perception:
The long game:
AI impressions are formed over time from accumulated mentions. You can’t game it short-term. You need sustained, authentic positive presence.
This thread fundamentally shifts how I think about authority building. Key insights:
What’s different for AI trust:
New metrics to track:
Strategic shifts:
What stays the same:
The 0.23 correlation for domain authority vs. 0.72 for Wikipedia presence is striking. Time to reallocate some link building budget to mention building.
Thanks everyone for the research-backed insights.
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