Attribution Gap

The attribution gap is the numerical difference between how many relevant sources an AI system actually consults while forming an answer and how many of those sources it visibly cites in the response a user sees.

Why it matters

AI systems typically read more sources than they credit, which means a brand's content can genuinely influence an answer's substance without that brand ever appearing in the visible citation list. It's a reminder that citation counts alone can understate a brand's real influence on what these systems say.

Related terms

• Citation Gap

  A citation gap is a query where a brand ranks well in traditional search results but its content is omitted or misrepresented in the AI-generated answer for that same query.

• Citation Rate

  Citation rate is the percentage of relevant AI-generated answers that cite a brand's domain as a source, out of every answer where citing that brand would have been relevant. It's the most commonly cited single performance metric across the GEO and AEO industry.

• Retrieval-Augmented Generation (RAG)

  Retrieval-Augmented Generation (RAG) is the architecture behind most AI search: the system retrieves a set of relevant documents or passages at query time, then generates its answer grounded in that retrieved material, rather than purely from what it learned during training.