Google's New Search Console AI Reporting: What It Shows, What It Doesn't, and What to Do With It
On 3 June 2026, Google launched dedicated Generative AI Performance Reports in Search Console — the first purpose-built view into how your content appears inside AI Overviews, AI Mode, and Discover's AI features. Here's exactly what the data shows, what it's still missing, and how to use it.
Introduction
For two years, anyone trying to understand their visibility in Google's AI-powered search features was working from inference. You could see that AI Overviews were appearing for your target queries. You could see your total impressions in Search Console's Performance report. But you couldn't see how much of that impression data came from AI features versus traditional organic results, which pages were being surfaced inside AI Overviews, or whether your generative search visibility was growing or declining.
On 3 June 2026, Google launched dedicated Search Generative AI Performance Reports in Search Console — the first purpose-built view of how websites appear within AI-powered search features. The rollout is currently limited to a subset of UK websites, with a wider global rollout to follow.
For anyone working in search, this is a meaningful step forward. It's also a more limited data set than the announcement might suggest. This article covers what the reports actually contain, what they're still missing, how to access them, and what the data means in practice.
What Google launched
Performance Reports
Dedicated views of impressions within generative AI features on Search — including AI Overviews and AI Mode — as well as generative AI features in Discover. This gives you measurement.
The Opt-Out Toggle
A control that lets site owners decide whether their content appears in and grounds AI features at all — giving site owners a kill switch over their AI search presence. This gives you control.
Five dimensions of data
The Generative AI Performance Reports expose five dimensions of data — each offering a different lens on your AI search visibility.
Impressions
How often URLs from your site appeared inside generative AI features across Search and Discover. The core metric — counts surfacing inside an AI-generated response, not clicks.
Countries
A geographic breakdown of your AI visibility. Useful for international sites trying to understand where their AI presence is strongest or weakest. and Devices.
Dates
Performance over time with hourly, daily, weekly, and monthly granularity. Report data starts from 18 May 2026, with no historical backfill before that date.
Pages
Which specific URLs from your site appeared within AI features. Identifies which content is being picked up by Google's AI systems and which isn't.
Devices
The devices people were using when your content appeared in AI features. Available for Search results.
What the reports don't show — and why that matters
This is the most important thing to understand before drawing conclusions from the data.
No clicks, CTR, position, or queries
There is no click data, no CTR, no average position, and no query-level breakdown. You can see that a URL appeared in an AI-generated response. You cannot see what query triggered it, whether the user clicked through, or where in the AI response your content appeared. This creates a significant limitation for measuring business impact.
Search Labs data excluded
Search Labs experiment data is not included in the reports.
Discover AI is separate
Google Discover's AI features get a separate report from the Search report.
This isn't new data
Google confirmed this was always included in your overall performance report totals. The new reports are a breakout of existing data — your aggregate impression numbers don't change.
Should you remove your content from AI features?
For most enterprise technology brands: no
Opting out removes your content from AI-generated answers at a time when AI search is becoming the primary discovery channel for business buyers. Stepping out before you even have click data to justify the decision is a significant strategic risk. The more productive question is how to use the impression data to improve the quality and consistency of your AI-generated appearances.
When opting out does make sense
Publishers whose entire business model depends on click-through traffic. Sites with content they don't want summarised or extracted out of context. Brands with specific concerns about how AI systems are representing their products or services. For most enterprise technology marketers, none of these apply.
Why AI Mode queries are different
Google published data in March 2026 indicating that AI Mode queries average three times the length of traditional searches. These aren't keyword searches — they're multi-part questions with context, constraints, and specific requirements. A buyer asking "which SASE vendor works best for a 500-person financial services company with SOC 2 compliance requirements and an existing Microsoft stack" is expressing far more intent in a single query than any traditional keyword search would capture. Answers in AI Mode draw on multiple sources simultaneously through what Google describes as a "query fan-out" technique — a single user query can surface content from multiple URLs in a single composite response. This changes how you interpret the impression data. Your URL appearing in an AI Mode response doesn't mean you "ranked number one" — it means your content contributed to a synthesised answer alongside potentially several other sources. High AI impression counts aren't necessarily equivalent to high traditional ranking positions. The relevant question is: which queries is your content contributing to, and is your brand being represented accurately and favourably in those responses?
Five actions to take now
Baseline immediately
The data goes back to 18 May 2026. Export your current impression numbers by page before any content or technical changes are made — you need a before state to measure any improvement against.
Identify the gaps
Which pages rank well in traditional search but don't appear in the AI reports? These are your highest-priority optimisation candidates — typically explained by content structure issues, missing schema, or entity ambiguity.
Connect downstream metrics
Connect AI impression trends to AI-referred sessions in GA4, conversion rates from those sessions, and branded search volume as a proxy for AI-driven awareness. Together these build a complete commercial picture.
Identify your strongest AI pages
The Pages dimension shows which URLs are being surfaced. Audit them: are they structured with schema markup? Do they contain clear, extractable facts? Are they updated regularly? Build from what's already working.
Watch the trend
Without click or query data, the absolute impression number is hard to benchmark. Focus on direction — is your AI impression share growing or declining week on week, and is it outpacing traditional organic?
The bigger picture
Together with the May 2026 Core Update, these reports make one thing clear: search visibility is no longer just about ranking positions and clicks. It is increasingly about how content is evaluated, surfaced, and cited across both traditional and AI-driven results.Google giving Search Console its own AI reporting infrastructure is the formal acknowledgement of something that's been true in practice for two years: AI Overviews and AI Mode are distinct channels, not extensions of traditional search. They have different content requirements, different citation patterns, and different metrics.The brands that treat this as a new measurement problem — rather than a confirmation of what they should already have been building toward — are the ones who will close the gap fastest. The impression data is now there. The question is what you do with it.