Vesna Scepanovic 
Internal links are one of those behind-the-scenes SEO tactics that quietly support everything: crawlability, authority flow, and user journeys. They define your site’s structure, guide search engines and AI systems, and help readers move naturally through your content.
For AI-optimized search, internal linking matters even more. It strengthens site structure, helps search engines crawl and understand your pages, directs link equity to where it counts, shows readers the right paths through related topics, and signals authority on the subjects you want to rank for. These are the cues AI relies on when deciding what content to show.
And yet, most sites don’t take full advantage. One study found that 82% of internal link opportunities are missed, leaving a massive, low-effort opportunity on the table.
Could AI step in to handle this often overlooked but powerful part of SEO? We put it to the test.
What We Tested
To see how AI handles internal linking, we used one of our own blog posts as the test case. We gave the draft to different AI tools and asked them to:
- Identify natural anchor text opportunities inside the content.
- Match those anchors with the most relevant pages from our website.
- Suggest a balance of links without overloading the text.
- Explain why each link should be added.
The goal was to see if AI could recognize where an internal link makes sense, choose the right destination, and suggest linking in a way that supports both SEO strategy and the reader’s journey through the content.
The Prompt
Each AI tool got the same instruction:
“You are an SEO assistant. Review this blog post draft and suggest internal links from the list of relevant pages on our website. Match anchors with the most relevant pages from our website. Make sure the links are relevant, avoid repetition, and explain why each link adds value. Limit your response to a table of no more than 8 internal link suggestions.”
This way, we could compare how each tool handled the same task, such as spotting anchor text, matching it to the right pages, and justifying its choices.
The Results
Each AI tool handled internal linking a bit differently. Some focused on structure, others on coverage, and a few surprised us with how close they came to understanding the intent behind an internal link.
ChatGPT 5
ChatGPT 5 gave a balanced list. The anchors felt natural, the destinations were relevant, and the output avoided unnecessary repetition. It understood the topic well enough to connect different clusters, making it a strong starting point for planning internal links.
Claude Sonnet 4.5
Claude Sonnet 4.5 approached the task systematically, mapping suggestions to specific sections of the blog. That structure made it easy to see where each link could fit. The links themselves were logical, but not very creative. It’s the kind of output you’d use to organize your linking plan before making final calls yourself.
Gemini 2.5 Pro
Gemini 2.5 Pro stayed focused on the essentials. Its internal links were accurate and clearly tied to the topic, but the scope felt narrow. It didn’t suggest as many cross-topic or supporting connections as other tools. It’s useful for precision work, but you’d still want a second pass to expand the linking depth.
Microsoft Copilot
Microsoft Copilot produced a practical and straightforward list of internal links. The anchors mostly aligned with key terms in the post, and several matched high-priority pages well. A few felt too general to be useful, but overall, the list was clean and relevant. With a quick manual review, it could easily become publish-ready.
Perplexity.ai
Perplexity’s list was concise and well-reasoned. Each internal link made contextual sense, and it managed to connect both technical and strategic angles. One or two suggestions felt a bit broad, but most could go straight into the draft with minimal editing. Among all tools, this one struck the best balance between clarity and practical value.
The Verdict
AI can handle the technical side of internal linking, spotting anchors, pairing them with relevant pages, and avoiding repetition. But the why behind each internal link still needs a human.
The tools made the process faster and more structured. Yet, none could decide which links carry the most weight for SEO or how to shape the reader’s path through the site.
If you used these results as a first draft, you’d save time on the manual work and focus more on refining what matters, turning links found by AI tools into strategic ones.
Zlurad PoV
We see internal linking as part of a bigger story. One that connects structure, content, and user intent. AI can help identify where those connections could happen, but it can’t understand why they matter to your business or your readers.
That’s why we treat AI suggestions as a first draft, not a final version. They help us spot patterns faster, but the strategy still depends on understanding what each internal link is meant to achieve: authority flow, visibility, or simply a smoother reader journey.
What Say We
Internal linking is one of those small, consistent actions that quietly hold your SEO together. And now, AI can make that process quicker, but not automatic.
Use it to uncover missed opportunities, not to replace your own judgment. The best results still come from people who know the content, the audience, and the goals behind every link.
AI can help you see the connections.
You still decide which ones count.