RAG (Retrieval-Augmented Generation)
Retrieval-Augmented Generation (RAG) is a method in which an AI language model retrieves current external sources before composing an answer and builds them into the generated response as a factual basis, instead of relying on trained knowledge alone.
In practice
Google AI Overviews, Perplexity and many company chatbots use RAG to answer more currently and more verifiably than a language model on its own could. For website owners this means that well-structured, clearly discoverable content is preferred and cited during the retrieval phase.