AI Search explained
AI search describes search experiences that use large language models to interpret a question, retrieve relevant information and generate an answer. Examples include Google’s AI Overviews and AI Mode, ChatGPT search, Perplexity, Google Gemini and Microsoft Copilot.
Most AI search products combine two things: a retrieval system (a search index or crawler that finds relevant pages) and a language model that writes an answer grounded in what was retrieved. Many show citations to the sources they used.
AI search differs from traditional search in three practical ways: answers are generated fresh for each request, so they vary; users can ask follow-up questions in a conversation; and the answer may satisfy the question without any click. It doesn’t replace the web — it reads it.
AI Search: an example
Instead of ten links, someone asking Perplexity "which project management tool suits a 10-person design studio?" gets a written recommendation with numbered sources, and can ask follow-up questions.
Why it matters for search and AI visibility
When answers are written for the user, being named and cited inside the answer becomes as important as ranking in the list of links below it.
Last reviewed by the Prisol team.