What is grounding in AI and why does it matter for reputation?

Grounding refers to anchoring an AI response to specific identifiable sources rather than allowing the model to generate freely from its training. Retrieval-augmented systems are grounded by design: Perplexity, ChatGPT Search, and Google AI Overviews all show citations and constrain answers to the retrieved sources. Higher-grounded systems are easier to influence through source-layer work, because the engine is explicitly drawing from a small set of identifiable sources that can be improved. The trade-off is that those same systems propagate source errors more directly: if the retrieved source is wrong, the answer is wrong, with the citation giving it apparent authority. Ungrounded systems hallucinate more but are harder to anchor with new content. A reputation program works on both, with awareness of the different mechanics.