AI keyword clustering should reduce page count, not explode it.
Clustering is one of the best uses of AI in SEO because language models can recognize semantic relationships across large keyword sets. The output still needs a page-level decision based on user intent.
Start with broad recall
Collect keyword exports, competitor topics, Search Console queries and related questions. Let AI propose conceptual clusters and identify likely parent/child relationships.
Validate intent
Terms that sound similar can still require different pages, while very different wording can share the same destination. Check what the searcher wants to accomplish and whether one strong page can satisfy the family.
Build cluster briefs
For each accepted page, record the primary intent, supporting questions, related entities, parent hub, sibling pages and the natural next action. This gives writers and automation systems a stable boundary.
Re-cluster with live data
Search Console often reveals query families the original research missed. Add sections to the existing page when the intent overlaps; create a new URL only when the search destination is genuinely different.