Internal linking for AI search

AI search systems still rely on crawling and the link graph to find and contextualize content. Internal links do three jobs at once: they help crawlers discover pages, they pass relevance and authority between related pages, and they map the relationships in your content so an engine can see which page is the definitive treatment of a subject.

When several supporting pages link to one canonical page with consistent, descriptive anchors, you're telling the engine 'this is the page that answers this question.' That concentration is what raises the odds that the canonical page is the one cited.

The words you link with describe the destination. 'Click here' tells an engine nothing; 'how to track AI citations' tells it exactly what the linked page covers. Treat anchor text as a short, honest label for the target page.

Organize content as clusters: a pillar page that gives the canonical answer for a broad topic, surrounded by supporting pages that go deep on subtopics. Each supporting page links up to the pillar, and the pillar links down to its supporting pages. This structure makes the topical relationships legible and tells engines where authority sits.

The most common mistake is linking only outward to other sites or only forward to newer posts. Authority flows along links, so deliberately route it back toward the pages you most want cited - your pillars and your highest-converting answers.

A few recurring problems quietly suppress AI visibility.