I’ve been testing a few AI-assisted internal linking workflows across a couple of niche sites over the last few months, and I’m starting to think the “fully automated internal linking” pitch is a bit overstated.

What I’ve seen so far:

– **Basic relevance matching works fine** for obvious links. If an article is about “best standing desks” and another page mentions “ergonomic office setup,” the suggestions are usually decent.
– **Contextual precision is still hit or miss.** The tools often recommend links that are semantically related but not actually useful for the reader.
– **Anchor text can get repetitive** if you let the system run too freely. I’ve had to manually clean up over-optimized anchors more than once.
– **Money pages benefit more when the workflow is curated.** On one affiliate site, I saw better movement after using AI to surface link opportunities, but I still manually decided where the links should go.

My current setup is basically:
1. Crawl the site.
2. Use AI or a linking tool to suggest opportunities.
3. Review the top-priority URLs manually.
4. Add links in clusters around topical hubs.
5. Re-test after a few weeks.

That seems to work better than trying to automate the entire process end-to-end.

What I’m curious about is whether anyone here has seen:
– measurable ranking improvements from AI-generated internal linking at scale,
– better results with entity-based linking vs keyword matching,
– or a workflow that doesn’t create a mess of weak, repetitive links.

Also interested in how people are handling this on WordPress. Are you using plugins, custom scripts, or just doing it manually in batches?

My take is that internal linking is still one of the easiest SEO wins, but it’s also one of the easiest things to over-automate. The tools are useful, but only if you treat them as assistants, not decision-makers.

Would be good to hear real-world results, especially from anyone running affiliate sites or using AI content systems with a fairly large URL footprint.