Canonical Tags Shape LLM Content Source Selection

This analysis explains how canonical tags interact with large language models and AI overviews, arguing that rel="canonical" remains a technical signal but is no longer sufficient to guarantee attribution or visibility. It details how LLMs cluster near-duplicate pages during training and retrieval, weigh authority, performance, and relevance, and recommends aligning canonicalization, structured data, hreflang, and site performance to protect preferred URLs in AI-driven answers.