AI SEO Glossary
What is Grounding?
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TL;DR — Grounding is the process by which an AI model anchors its answer in retrieved, verifiable sources — live web pages, documents, or a search index — instead of relying solely on what it memorized during training. When ChatGPT browses, Perplexity searches, or Gemini consults Google's index before answering, the answer is grounded. Grounded answers cite sources, which is precisely why grounding matters for marketers: a brand can influence a grounded answer this quarter by publishing citable content, whereas influencing training-data memory takes model-release cycles.
Definition & scope
Engines ground selectively. Stable encyclopedic questions are often answered from model memory; fresh, comparative, or shopping-flavored prompts trigger retrieval. Commercial queries — "best X for Y", "X vs Y", pricing questions — are grounded far more often than not, which puts them within reach of ongoing optimization work.
Grounding is implemented with RAG: retrieve candidate sources, rank them for relevance and trustworthiness, then generate the answer from the retrieved set. Being retrievable (crawlable, fast, structurally clear) and being quotable (crisp first-sentence answers) are the two halves of earning a place in that retrieved set.
Related terms
- RAG — the architecture that implements grounding.
- Citation Share — measures how often grounded answers cite you.
- AI Crawler — the retrieval agents that fetch sources at answer time.
Related services
- ChatGPT SEO Services — optimizing for ChatGPT's grounded-answer mode.
- AEO Services — the full grounded-citation program.
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