How AI answers are made
Semantic search
Semantic search tries to understand what a question means, so it can find useful pages even when they don’t use the exact same words.
In plain words
Older search looked mostly for matching words. Semantic search looks for matching meaning.
Google describes one of its systems, neural matching, as AI that understands representations of concepts in queries and pages and matches them to each other.
Example
Someone searches "why does my phone get hot while charging". A helpful page might be titled "Battery overheating: causes and fixes". The words differ, but the meaning matches.
Why it matters for AI search
Google says its AI systems understand synonyms and general meaning. So you don’t have to cover every possible way of phrasing a question.
Clear meaning matters more than repeating a keyword.
What you can do
- Answer the real question behind a search, in plain language.
- Name things clearly: people, products and places.
- Skip keyword stuffing and say each idea once, clearly.
Often confused with
- LSI keywords
- "LSI keywords" is an old SEO label for related words. Related words can support meaning, but semantic search is about the meaning itself.
Sources
- Google Search Central: A guide to Google Search ranking systems
- Google Search Central: Optimizing your website for generative AI features on Google Search
Facts and sources last checked on 19 October 2026.
Related terms
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