What is grounding in AI search?
Grounding (also called source attribution) is the process by which an AI system anchors its generated answer to specific retrieved sources rather than relying solely on knowledge from training data. A grounded response cites the pages it drew from, making those citations the unit of visibility in grounded AI search.
Grounding is central to RAG-based AI search systems like Perplexity and ChatGPT search. Before generating an answer, the system retrieves live web pages, extracts relevant passages, and grounds its output in that content. The cited source pages benefit from both the citation link and the brand impression inside the answer.
How grounding affects content and brand strategy
For brands, grounding means two things. First, content must be retrievable: if a page is not indexed, behind authentication, or too slow to crawl, it cannot ground an AI answer. Standard technical SEO hygiene is the entry ticket. Second, content must be extractable: AI systems lift specific passages, so pages with clear, self-contained factual statements ground more reliably than those with vague or discursive prose.
Ungrounded responses — answers generated purely from training data without live retrieval — are where brand representation risk is highest. If a model’s training data contains outdated or inaccurate information about a brand, grounded responses can be corrected by accurate current pages, but ungrounded responses reproduce whatever the training data encoded.
Example
Example
Perplexity answers "what is the best way to reduce blended CAC" and cites a specific passage from a Grow With Gradient article that directly addresses the question. The article is grounded in the answer: it is the source the model is attributing. Without that page being indexed and retrievable, a competitor’s page grounds the answer instead.
Frequently asked questions
Is grounding the same as AI citation?
Related but distinct. Grounding is the technical process of anchoring an answer to retrieved sources. An AI citation is the visible outcome — the link shown in the answer. Grounding produces citations, but some grounded information is paraphrased without a visible citation link.
How do I make my content ground AI answers more reliably?
Ensure indexability (no crawl blocks, fast load), write direct factual statements that answer specific questions, use clear entity references, and publish on a domain with authority signals. The passage that gets retrieved is the one that most precisely answers the query in a self-contained way.