AI Overviews and Local SEO: What the Data Says in 2026

Something shifted in Google Search in 2025. AI Overviews began appearing at the top of results for more and more queries, pushing Organic Search Results further down the page. Then AI Mode arrived as a separate, fully conversational search experience. And the data that has come back since then tells a clear story about what this means for SEO, for local SEO, and for every business that relies on Google Search to reach customers.

This post pulls together the most significant findings from recent research on AI Mode to give SEO practitioners and agency teams a factual picture of what is happening. How often do AI search highlights appear in local queries? How do Google Business Profiles factor in? What do Google citations inside AI Mode look like? And what does traditional SEO still contribute to visibility inside AI summaries?

How Common Are AI Overviews Across Different Query Types?

AI Overviews are no longer a minor SERP feature. According to multiple analyses conducted, AI Search Results now appear for around 16% of all Google Search queries at the aggregate level. But that headline figure conceals significant variation by industry and query type.

In health-related categories, AI Search Explanations appear in up to 82.5% of searches according to SE Ranking data. In commercial categories like e-commerce and retail, the figure drops to around 2%. The pattern reflects how Google applies AI summaries most aggressively to informational queries where a synthesized answer can directly satisfy the user, and least aggressively where the user clearly needs to take an action, such as buying, booking, or navigating to a physical location.

The Local Search Picture

Local queries show a more nuanced picture. According to a whitepaper published by Local Falcon, the AI search appeared in 40.2% of queries across 60,000 searches for local businesses. That figure is significantly higher than the cross-category average, which means local businesses face above-average exposure to AI summaries, displacing their Organic Search Results.

The same research found in local search does not apply the same distance-based ranking logic used in traditional local packs. Proximity still influences whether a business appears as the AI Overviews result, but it has almost no effect on the order in which businesses are listed once they are included. This represents a meaningful departure from how traditional SEO and local SEO have worked for the past decade.

SEO Insight: Proximity matters less inside AI search than it does in the local pack. Content quality and profile completeness now play a bigger role in determining whether a local business appears in AI summaries at all.

What AI Overviews Are Doing to Click-Through Rates

The CTR data is the sharpest signal of how AI search is affecting SEO Traffic. When a Google summary appears, users get an answer without needing to click. That dynamic is clearly visible in the numbers.

Organic CTR drops from 1.76% to 0.61% when AI Overviews are present, a 61% decline according to Seer Interactive research covering 3,119 informational queries across 42 organizations through late 2025. Individual websites experience an average 34.5% CTR reduction for their target keywords.

The inverse also holds. Brands cited inside AI responses earn 35% higher organic CTR compared to non-cited brands in the same query. Being included in the summary lifts SEO Traffic even when the citation does not generate a direct click. That visibility drives brand recognition which converts downstream.

AI Mode Takes This Further

If AI Overviews reduce clicks, AI Mode removes them almost entirely. Around 93% of AI Mode searches end without a click; more than twice the zero-click rate associated where 43% of searches end without a click.

Users spend significantly longer inside AI Mode (49 seconds versus 21 seconds on average, according to Growth Memo data). The experience is more conversational and more complete, which means users have less reason to leave Google Search altogether. For publishers and agencies tracking SEO Traffic, this behavioral shift is the structural reason why aggregate traffic from SERPs is under sustained pressure.

Google Citations Inside AI Mode: The Self-Referencing Pattern

One of the most significant findings from recent research on AI Mode is the scale of Google self-referencing. According to SE Ranking analysis covering 1.3 million citations from 68,313 keywords in February 2026, Google accounts for 17.42% of all citations inside AI Mode answers. That is more than the next six most-cited domains combined: YouTube, Facebook, Reddit, Amazon, indeed, and Zillow.

This figure tripled in less than a year. In June 2025, Google self-citation in AI Mode stood at 5.7%. By early 2026, it had reached 17.42%. The growth is not uniform across verticals. In Travel, more than half of all Google citations point back to Google properties. In Entertainment and Hobbies, the figure is nearly 48%. Even in Finance and Insurance, where specialist sources are expected, Google holds the top citation position at 5.13% and 6.48% respectively.

Where Those Google Citations Point

What changed between 2025 and 2026 is not just how often Google self-cites but where those links go. In June 2025 research on AI Mode, 97.9% of Google citations led to Google Business Profiles with no links to traditional search results. By February 2026, the picture had shifted: 59% of Google citations inside AI Mode now point to Google organic SERPs displayed in the right-hand panel, while 36.1% still reference Google Business Profiles.

That shift matters for SEO Strategy because it confirms that traditional SEO rankings still determine citation eligibility. Pages that rank well in Google Search appear in AI Mode citation panels. The mechanism is different from direct organic traffic, but the signal that determines inclusion is the same: relevance and authority as measured through conventional SEO Efforts.

SEO Insight: 59% of Google citations in AI Mode now point to organic SERPs, not just GBPs. This means a site that ranks well in traditional search has a direct path to appearing in AI Mode citation panels, even without any dedicated GEO optimization.

AI Overviews vs AI Mode: Key Differences for SEO

The table below outlines the most important practical differences for teams managing organic visibility.

Why Google Business Profiles Now Feed AI Overviews

For local businesses, Google Business Profiles has always been the foundation of local SEO. What has changed in 2026 is that a well-maintained profile is now also a direct input into AI responses. Google pulls business information, reviews, categories, photos, and service descriptions from Google Business Profiles to construct AI summaries for local queries.

The implication is that Google My Business optimization is no longer separate from SEO Strategy for AI visibility. They are the same task. A profile that is incomplete, outdated, or inconsistent with the business website creates gaps that Google may fill with inaccurate data from other sources or omit entirely AI responses.

What the Research on Local AI Visibility Shows

According to Sterling Sky, Google is actively rolling out AI-powered local packs that appear on mobile and increasingly influence call volumes and direction requests from Google Business Profiles. The research tracked 179 profiles across 34 law firms and found consistent declines in calls from Google My Business listings, even where profile rankings had not dropped.

The 2026 Whitespark Local Search Ranking Factors report, cited in the same Sterling Sky research, found that three of the top five AI search visibility factors are citation-based, including mentions in expert-curated lists, unstructured mentions in news and blogs, and overall mention volume across the web. This means Google Business Profiles form part of a broader trust signal network. A profile in isolation is not enough. It needs consistent supporting signals from third-party directories, review platforms, and structured web mentions to perform inside AI summaries.

One 2025 report found that 48% of local-intent searches led to a Google Business Profiles interaction within 24 hours, and businesses that include photos saw 45% more direction requests and 31% more website clicks. These engagement signals feed back into Google's assessment of profile authority, which in turn affects inclusion for local queries.

SEO Insight: Local queries pull directly from GBPs. A profile that has not been updated in 30 days, is missing categories, or has responded reviews sends weaker authority signals to Google's AI than one that is actively managed.

How to Track AI Overviews Visibility?

The core challenge is attribution. Google Search Console Now counts AI Mode clicks as Web search traffic, and AI Overviews clicks appear in the same performance data as standard organic clicks. There is no native filter that separates them. This makes it difficult for any SEO specialist to understand how much of a client's SEO Traffic is coming from AI summaries versus traditional SEO positions.

Dedicated AI Mode tracking tool platforms fill that gap. These tools monitor which keywords trigger a domain, track citation frequency, and identify which pages are referenced in AI responses. Some platforms also track competitor citation rates, showing how often rival brands appear inside AI summaries for shared keywords.

• AI Overviews Tracker: Start monitoring which of a site's keywords trigger AI search in Google Search and whether the site is cited within them. Because Google Search Console does not filter this data separately, a dedicated Tracker is the only way to see this at scale.

• AI Mode Rank Tracking Online: Standard rank tracking reports a URL's position in SERPs. AI Mode Rank Tracking Online tools go further, reporting whether a domain appears in AI Mode citation panels, how often it is mentioned, and whether mentions include direct links or unlinked brand references.

• Citation source monitoring: Understanding which domains Google cites most in each niche is strategic intelligence. Different industries rely on different authority platforms. Knowing where Google citations come from in a category guides content placement and outreach decisions.

• Google Business Profiles performance data: Profile impressions, direction requests, call volumes, and photo views from Google My Business dashboards reveal how AI summaries are affecting local engagement. Declines in these metrics without corresponding ranking drops often indicate AI Overviews intercepting user intent before a profile click occurs.

What Traditional SEO Still Does in the AI Era

There is a persistent narrative that AI Overviews has made traditional SEO irrelevant. The data does not support that. 76.1% of URLs cited in AI Overviews also rank in the Google top 10. The correlation between Organic Search Results performance and AI search citation is stronger than the correlation between organic performance and any other AI platform.

This means the foundation of eligibility for AI summaries is the same as the foundation of traditional SEO: authoritative content, strong backlink signals, technical performance, and demonstrated E-E-A-T. A page that would rank well in organic SERPs is the same page most likely to be cited. The channel is different. The underlying signal is not.

Start Optimizing for AI Overviews

The research from 2025 and early 2026 makes several things clear. AI Overviews are now a standard part of Google Search for a significant share of queries, especially in local categories. Google Business Profiles have become a content input for AI summaries, not just a local pack of signal. And Google citations inside AI Mode increasingly lead back into Google's own ecosystem rather than third-party sites.

For SEO practitioners, the practical conclusion is that traditional SEO remains the mechanism that determines AI Overviews citation eligibility, while Google Business Profiles management, brand citation building, and AI Mode Rank Tracking Online now form the expanded toolkit. Visibility inside AI summaries does not replace SEO Efforts. It extends them into a new measurement layer that requires different tools and different success metrics to manage properly.

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