Bing separates grounding from indexing for AI answers

What happened

Per Search Engine Journal, Microsoft's Bing team has published a framework that formally separates "grounding" for AI-generated answers from traditional search indexing, identifying five distinct measurement areas where the two diverge.

The framing matters because Bing is the retrieval layer behind Copilot and, by extension, a meaningful share of ChatGPT's web answers through Microsoft's partnership infrastructure. When Bing's engineers say grounding is a different discipline from ranking, they are telling publishers that the SEO playbook does not automatically transfer to the surfaces where most B2B buyers now ask their first question.

The five areas Bing draws out cover how content is selected, scored, attributed, and surfaced inside a generated answer rather than a list of blue links. The signal: pages that rank can still fail to ground, and pages that ground can sit well outside the top ten organic results.

Why it matters for your brand

For a CMO at a bank, an industrial group, or a multilateral, this is the moment to stop treating "AI search visibility" as a downstream effect of SEO. The Bing post is an explicit admission from the index owner that the two systems optimise for different things. If your team is still reporting on keyword rankings as a proxy for Copilot citations, the proxy is broken.

Grounding rewards content that answers a specific user intent in a self-contained, attributable passage. Indexing rewards relevance and authority signals across a whole page. The practical consequence: a 3,000-word thought leadership PDF that ranks well for "sustainable cement" may never be grounded inside a Copilot answer about Scope 3 emissions in construction, because no single passage cleanly resolves the prompt. A 400-word explainer with a clear definition, a named author, and a date stamp will. Financial services brands publishing regulatory commentary, and UN agencies publishing policy briefs, are particularly exposed here. Long, dense institutional formats are the worst fit for grounding even when they are the best fit for credibility.

Distribution strategy shifts too. Grounding pulls from sources the model already trusts for the specific topic at hand, which means topical concentration beats topical breadth. A philanthropic institution that publishes on twelve themes will lose ground to one that publishes consistently on three. For industrial groups, the implication is that corporate newsrooms that try to cover everything from earnings to sustainability to HR will fragment their grounding signal across surfaces. Pick the two or three topics where you must be the cited source, and build depth there.

There is also a measurement gap opening up. Most enterprise SEO platforms still report on rank, impressions, and clicks. None of those metrics describe whether your content was selected as a grounding source for an AI answer. Comms and marketing leaders should expect to commission a parallel measurement stack over the next two quarters, one that monitors citations across Copilot, ChatGPT, Perplexity, and Gemini for a defined set of branded and category prompts. If your agency is not already producing this, ask why.

For multilaterals specifically, the grounding question is existential. UNDRR, the World Bank, and the IMF are exactly the kind of high-trust, high-authority sources that LLMs prefer for grounded answers on policy, risk, and development finance. But that preference only activates if the content is structured for retrieval: short, dated, attributable, and topic-specific. Most UN system content is not. The institutions that fix this first will dominate the grounded answer layer for the next decade of policy queries.

The signal in context

Bing's framework lands in a year when every major model vendor has begun publishing partial guidance on how their retrieval and citation systems work. Google has described how AI Overviews select sources. OpenAI has detailed which publishers ChatGPT search prioritises through its licensing deals. Anthropic has been quieter but has confirmed Claude's web search uses Brave's index with its own re-ranking layer. The pattern is convergent: the grounding layer is becoming a distinct, named function inside each AI product, with its own rules, separate from whatever crawler or index sits underneath.

For senior marketers, the takeaway is that AI visibility is now a portfolio problem, not a single-platform problem. Each model grounds differently, weights sources differently, and updates its preferences on different cycles. Brands that built one SEO function ten years ago and never restructured will need a grounding function that sits closer to editorial and PR than to technical SEO. The teams that figure this out before their competitors will own the answers their buyers see when they ask the questions that matter.