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Google Tests Dedicated AI Search Reports In Search Console

Photo of David Park David Park June 4, 2026 · 6 min read

Google is now testing two dedicated AI search reporting features in Search Console for select UK websites, providing new visibility into how URLs surface in AI-driven search modules, according to Searchenginejournal. The features let site owners view impressions data, broken down by page, country, device, and even hourly intervals. Click and query-level metrics are not yet available in this early test phase. Demand for this analytics surge began when Google launched AI-related search summaries in the US in 2024. Per Google, a broader rollout will follow if UK testing proves reliable and useful. This shift brings a new level of transparency to AI-driven search analytics for digital publishers. Data-driven strategies are changing the digital publishing playbook worldwide.

According to Searchenginejournal, Google is rolling out dedicated AI search reporting in phases, starting with a subset of UK websites. Global expansion is promised if early feedback and technical targets are achieved. Microsoft Bing followed a similar roadmap. Its AI Performance dashboard launched for select users in February 2026, and the Citation Share preview went live in March.

2024: Google launches AI-driven search summaries in the US, sparking calls for AI-specific search reporting.

Feb 2026: Bing’s AI Performance dashboard debuts for selected users.

March 2026: Bing previews Citation Share at an industry conference to demo page-level grounding.

Q2 2026: Google starts testing AI-centric Search Console features with UK site owners.

Coming months: Planned global expansion for dedicated AI metrics, based on trial results.


The AI Visibility Toggle

Letsdatascience reports Google’s new AI visibility toggle in Search Console gives website owners control over whether their URLs appear in generative AI summaries.

Marketers can now include or exclude specific URLs from AI-driven results, gaining a powerful new tool for campaign planning. Before this test, Varn (via Letsdatascience) notes Search Console users couldn’t filter impressions triggered by AI summaries versus classic organic links. Publishers long wanted that clarity to see how their URLs fuel AI answers—spotting both audience gains and unseen data loss.


What The New Reports Show

According to Searchenginejournal, Google’s new AI search how often site URLs are seen in generative modules—covering both Search and Discover. Impressions break down by page, country, device, and hour.

Bing’s AI Performance dashboard, first released in February, already offers click-based metrics and query-to-page mapping as of March. This gives Bing users partial data on AI-driven referral traffic. For Google users, impressions from AI modules now show as distinct counts.


Background

According to Searchenginejournal, marketers have ranked AI-specific reporting as a top need since Google first embedded generative summaries in core search in 2024. Previously, no tool could isolate engagement or impressions inside AI panels. Site owners had to estimate traffic from incomplete data, often guessing about missed opportunities. Letsdatascience says AI module effects sometimes leaked into total Search Console stats, but separating classic search from generative performance was impossible without a dedicated filter.

Google has launched AI-assisted configuration for Search Console, letting users describe analysis in natural language. Bing’s Citation Share and fine-grained metrics show the new analytics arms race. Both giants want to make AI summary impacts measurable for SEO.


Why This Matters

Jaseem points to that performance in generative AI modules splits off from old-school organic rankings as users click less and read more summaries. Research shows AI-sourced summaries often answer queries directly, so brands can gain visibility while losing trackable site visits. Searchenginejournal explains that the historic lack of AI exposure filters left marketers confused about what content captured real audience attention and what simply powered unseen backend answers.


What’s Driving Traffic Now

Searchenginejournal documents how publishers and brands now must audit both classic and AI-driven rankings. The new AI search reports solve a blind spot: until now, editorial teams struggled to see what really powers web traffic as generative modules split off from traditional links.

Opting specific content in or out of AI citation and tracking which topics get the most AI exposure are now basic decisions. Deciding how to model ROI as clicks shift from publisher sites to search results requires new methods. Upcoming click and query metrics will sharpen these choices. Both Searchenginejournal and Letsdatascience emphasize that finding the exact driver of referrals—classic links or AI summaries—now defines digital analytics.


AI Search and Multi-Location Visibility

AI search engines such as Google and Bing now cite region- and topic-specific content, as well as community posts, in their generative summaries, according to Searchenginejournal.

Letsdatascience outlines how participating in communities—like Reddit forums or user Q&A hubs—raises your chances of being cited by AI.

Optimize local landing pages: Distinct, well-structured landing pages for every location, with detailed schema markup, help AI engines spot and cite regional content.

Engage with community platforms: Participation in active discussions can bolster a brand’s credibility and raise citation chances.

Provide thorough answers: FAQs, explainers, and debate-style posts appeal to AI selectors looking for detail-rich sources.

Track new AI impression metrics: Use hourly data to identify top-performing content types, then update underperformers as trends shift.

Audit opt-in/opt-out choices: Regularly review metrics before excluding site sections from generative modules.

Google’s dedicated AI search reports in Search Console, first offered to select UK sites, mark a new era for digital analytics. Marketers now get hourly impression tracking and a long-awaited visibility toggle for AI modules. These tools move measurement closer to business impact. Searchenginejournal and Letsdatascience say more features—wider rollout, click and path data, deeper engagement insights—are on the horizon as both Google and Bing expand public testing.


For deeper Google Tests Dedicated AI Search reviews, comparisons, or hands-on reporting, contact our tech desk.

This article is for informational purposes only. Always verify information independently before making any decisions.

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David Park

Analytics and Measurement Lead

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David Park is the Analytics and Measurement Lead at AdvantageBizMarketing with 9 years of experience in data-driven SEO. He holds an MS in Statistics from UC Berkeley and previously worked as a data scientist at Google, where he contributed to search quality measurement frameworks. David specializes in SEO attribution modeling, log file analysis, and building custom reporting dashboards that connect organic search to revenue. He is a certified Google Analytics 4 expert and has published research on click-through rate modeling in peer-reviewed marketing journals.

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