Query Fan-Out Analysis Comes to Semrush Enterprise AI Optimization, Revealing the Search Signals Behind AI Responses

Semrush Enterprise has announced the release of Query Fan-Out Analysis, a new feature within AI Optimization (AIO) that reveals the Google search queries that fuel AI responses in systems such as ChatGPT.

The feature help address a growing challenge for enterprise marketers. While AI discovery is an increasingly important customer touchpoint, the background queries that AI models run to formulate their answers are hidden to brands. 

Query Fan-Out Analysis brings transparency to this process, revealing this new layer of fan-out queries to help teams understand how AI systems retrieve information, additional terms to target, and where SEO performance directly impacts AI visibility.

When users prompt AI systems, the response they see is rarely based on one search alone. Instead, large language models break prompts into multiple related terms, retrieve results from Google, and synthesize the information from these into a single answer. This is known as query fan-out.

Semrush research shows that appearing consistently across these underlying queries increases the likelihood to be cited or surfaced in AI responses, even when they are not the top-ranked result for the original prompt.

However, until now, marketers lacked visibility into what the fan-out queries were for the key prompts being tracked. As well as which of these queries matter most and which competitors were best positioned for these.

Query Fan-Out Analysis exposes the search behavior that shapes AI answers by revealing:

This allows teams to better understand and act on the search signals that influence AI responses, treating these terms as keywords and utilizing the SEO tactics they already understand and control.

The release reinforces a central pillar of the search industry: AI search and SEO are not separate disciplines. Indeed, they’re intrinsically linked.

SEO best practices have a positive influence on AI visibility. But strong rankings for a single keyword don’t guarantee visibility in AI responses. 

At the same time, brands that focus exclusively on AI prompts without strengthening search performance risk missing the underlying drivers of AI visibility.

Query Fan-Out Analysis enables teams to better:

When used alongside Enterprise SEO automations such as keyword gap analysis, content optimization, and position tracking, the feature helps foster a single, connected digital visibility strategy.

Query Fan-Out Analysis is designed for enterprise organizations or growing teams managing visibility across multiple brands, domains, and markets.

The feature provides a practical framework for navigating AI search volatility while continuing to invest in long-term SEO foundations.

As search behavior evolves, visibility is no longer earned through a single channel or tactic. Consumers move fluidly between search engines and AI, and brands must understand their performance holistically and optimize for both.

Query Fan-Out Analysis helps organizations measure, understand, and grow visibility wherever discovery happens, empowering teams to expand upon the SEO strategies that continue to drive results, while building leadership as AI search rises.