Has anyone actually tested how internal linking affects AI citations? Seeing some surprising results

This matches what I’ve been seeing with clients. Internal linking is hugely underrated for AI visibility.

The key insight people miss:

AI systems don’t just crawl individual pages - they try to understand your entire site’s knowledge graph. When your internal links create clear topical relationships, you’re essentially building a map that tells AI: “Here’s how all my content on [topic] connects.”

What I’ve found works:

1. Thematic clustering - Group all content on a topic with clear parent-child relationships
2. Consistent anchor text - Use the same terminology across your site for key concepts
3. Hub page authority - Make sure your most important pages have the most internal links pointing to them

The data point that convinced me:

One client had a comprehensive guide that should have been cited everywhere but wasn’t. We discovered it had almost no internal links pointing to it. After adding 15+ contextual internal links from related articles, it started appearing in AI responses within 6 weeks.

The 2-3x improvement you’re seeing is consistent with what I’d expect. AI systems favor sites where the structure clearly communicates expertise.

I’ve been tracking this with Am I Cited for 4 months. Here’s what the data shows:

Pages with strong internal linking profiles:

• Average of 12+ internal links pointing to them
• Cited 2.5x more frequently than pages with <5 internal links
• Position in AI responses also tends to be higher (mentioned earlier)

The timeline question:

From my data, changes take about 4-8 weeks to show up in AI citation patterns. This probably correlates with when AI crawlers revisit your site and when their indices get updated.

Depth matters less than you’d think:

I tested this specifically. Pages 4 clicks from homepage can still get cited well IF they have strong internal linking from related content. It’s the topical cluster strength that matters, not the raw click depth.

Pro tip: Create a visual map of your internal links. If you can’t see clear topic clusters forming, neither can AI systems.

We’ve productized internal linking audits specifically for AI visibility. Here’s what we’ve learned from 50+ client sites:

The correlation is real:

Sites with intentional topic cluster architecture are cited 3x more frequently than sites with flat or random internal linking structures. This held true across B2B, ecommerce, and publishing clients.

Common mistakes we fix:

1. Orphan pages - Critical content with no internal links. AI systems struggle to understand how it fits into your expertise
2. Inconsistent terminology - Calling the same thing different names across articles confuses semantic understanding
3. Over-linking to homepage - Every internal link to homepage is a missed opportunity to build topic authority
4. No contextual linking - Only relying on navigation menus instead of in-content links

The biggest wins:

Usually come from identifying your most valuable content and then aggressively building internal links to it from all related pages. It’s like telling AI: “This is my best, most authoritative content on this topic.”

News publisher here with a different perspective.

We have thousands of articles and internal linking at scale is a nightmare. But we’ve found that automated related links at the bottom of articles don’t work nearly as well as contextual links within the content.

Added a process for editors to manually add 2-3 contextual internal links when publishing new articles. It’s more work, but our AI visibility improved noticeably.

The algorithmic “related articles” sections seem to be treated differently by AI systems - maybe because they’re obviously automated and not editorial decisions about content relationships?

Ecommerce angle: Category page internal linking is crucial for AI product recommendations.

What works for us:

• Category pages linking to subcategories and top products
• Product pages linking to related products AND back to category
• Buying guides linking to specific products they recommend
• FAQ pages linking to relevant product categories

The result:

When someone asks AI “best running shoes for flat feet,” our buying guide gets cited because it’s well-integrated into our site’s topical structure around running shoes, foot types, and specific product recommendations.

The internal links create a web of context that AI systems can follow to understand: “This site has comprehensive expertise on running shoe selection.”

Technical implementation question - does the HTML structure of internal links matter?

I’m wondering if:

• Links in main content vs sidebar
• Links in semantic HTML (nav, article) vs generic divs
• Placement early vs late in content

Anyone tested these variables specifically?

Great insights from everyone. Let me summarize what I’m taking away:

Key learnings:

1. Topical clustering is essential - AI systems evaluate your entire site structure, not just individual pages
2. Anchor text consistency matters - Use descriptive, consistent terminology for internal links
3. Contextual > Navigational - Links within content body carry more weight than sidebar/footer links
4. Timeline is 4-8 weeks - Changes take time to reflect in AI citation patterns
5. Quality over quantity - A few well-placed contextual links beat many automated related links

My next steps:

• Going to track internal link changes more systematically with Am I Cited
• Test the contextual vs navigational hypothesis on our sites
• Build out missing links to our most valuable hub content

Thanks for all the data points. This is clearly an underexplored area that deserves more attention.

For anyone starting from scratch - what’s the minimum viable internal linking strategy?

We’re a small team and can’t do everything. What’s the 80/20?