"“Indexing for grounded AI answers is not a reinvention of search - it is a major evolution of it. Grounding commits to an answer.”"
"“The shift we described at the opening is worth restating plainly: search indexing was built to help humans decide what to read. Grounding indexing is being built to help AI systems decide what to say. The infrastructure required to do those two things well is not the same - even when it starts from the same foundation,” Microsoft Bing's team wrote."
"“A common misconception is that grounding replaces search. It does not. Grounding builds on the same foundational infrastructure - the same crawlers, the same quality signals, the same deep understanding of the web - but it adds a new optimization layer on top,” they also wrote."
"“Search optimizes for likelihood of relevance. Grounding must measure strength of evidence. Understanding that difference is not just an engineering concern. It is the starting point for building AI systems that people can actually trust.”"
Indexing for grounded AI answers is positioned as a major evolution of search rather than a reinvention. Search indexing is built to help humans decide what to read, while grounding indexing is built to help AI systems decide what to say. Grounding focuses on what information an AI system can responsibly use to construct a response, requiring a different definition of index quality. Grounding builds on the same foundational infrastructure used for search, including crawlers, quality signals, and deep understanding of the web, but adds a new optimization layer. Search optimizes for likelihood of relevance, while grounding must measure strength of evidence to support trustworthy AI responses.
Read at Search Engine Roundtable
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