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Q1 2026

Quarterly Search Report

We analyzed how brands perform in AI search and traditional search across five industries. What we found challenges the assumption that the same factors influence both.

Read the Report

A year into the shift toward AI search, much of the existing commentary is long on opinion and short on actionable recommendations. In an effort to separate the signal from the noise, we analyzed how brands perform in AI search versus traditional search across five industries, to see if we could find discernible patterns.

Our goal is to replace hot takes with data you can plan against — original research and clear thinking for marketing leaders who need to act with confidence.

01
From our founder
02
How we built this report
03
AI trusts your content. It doesn't recognize your brand.
04
Vertical benchmarks: citations vs. mentions
05
Where AI platforms source their answers
06
Authority predicts organic, not AI visibility
07
Q1 news: algorithm updates, platform changes
08
What we're watching in Q2
09
Take action: three paths forward
Michael Transon, Founder & CEO, Victorious
From our founder

Michael Transon

Founder & CEO, Victorious
Search is splitting into two systems. And the factors driving each aren't the same.

Traditional organic still drives traffic and conversions. But AI platforms are now deciding who's credible, choosing who gets cited or mentioned and who gets ignored. And the factors driving those decisions aren't the same ones that drive organic rankings.

Our analysis shows that domain authority alone doesn't determine which brands show up in AI search. We tested the correlation across 177 brands, and it's essentially zero. Authority is still necessary. It builds the foundation. But alone, it's not sufficient for AI visibility.

Methodology

How we built this report.

We cross-referenced three data sets to understand how AI search platforms evaluate brands differently from traditional organic search.

Coverage
177
Brands across five verticals
AI Visibility
107,011
AI prompt responses across 8 platforms
Organic Visibility
880
Organic data points via Semrush
Step 01

Captured the AI visibility signal

For each of the 177 brands, we tested vertical-specific prompts in eight different AI platforms. For every response, we recorded whether the platform named the brand and whether it cited the brand’s domain.

ChatGPT
Perplexity
Gemini
AI Overview
AI Mode
Copilot
Claude
Meta AI
Step 02

Pulled the organic performance data

For the same 177 brands, we tracked domain-level organic performance in Semrush over Q1 2026, capturing traffic trends and Authority Scores.

Step 03

Cross-referenced the two datasets

We joined the AI visibility signal with the organic dataset so every brand had three comparable measures.

  1. Mention rate. How often a platform named the brand in answers.
  2. Citation rate. How often a platform linked to the brand’s domain as a source.
  3. Authority Score. Semrush’s proprietary authority estimate for each domain.
Four Findings

Here's what the data told us.

Four key findings from this quarter's dataset.

  1. 01AI trusts your content. It doesn't recognize your brand.
  2. 02The gap between citations and mentions looks different in every industry.
  3. 03Each AI platform draws from a distinct set of trusted sources.
  4. 04Authority correlates to organic growth. It doesn't correlate to AI visibility.
Finding 01 · AI Visibility

AI trusts your content. It doesn't recognize your brand.

There’s a gap between how AI uses content and how it recognizes
the brands behind it.

-5,428.6%

of brands in our dataset had no AI mentions at all during Q1 2026. Of 177 businesses analyzed, only 18 had any AI mention rate above zero.

Our POV
Most businesses have yet to enter the AI visibility race. Right now, the window to unchallenged AI visibility is still open for many brands.

To understand that gap, we tracked two distinct signals for every brand in every AI response:

Metric 01

Mention Rate

How often an AI platform named a specific brand. Mentions indicate a strong entity association between the brand and the topic.

Metric 02

Citation Rate

How often a platform linked to a brand’s domain as a source. Citations measure the value and trust attributed to the content.

Some brands are mentioned but not cited. Others are cited but not mentioned. A rare few are cited and mentioned.

Finding 02 · Vertical Benchmarks

The gap between citations and mentions looks different in every industry.

Five verticals, five different mention-to-citation ratios.

Mention rate vs. citation rate, by vertical

Mentions Citations
Healthcare
29.1%
19.8%
+9.3pt gap
SaaS
24.3%
13.8%
+10.5pt gap
Financial Services
20.1%
21.9%
-1.8pt gap
E-commerce / Retail
18.1%
6.0%
+12.1pt gap
Legal Services
0.9%
11.3%
-10.4pt gap
Mentioned & Cited

Healthcare, SaaS, Financial Services

These brands are getting mentioned and linked as sources. Healthcare benefits from clear entity identifiers like names, locations, specialties, and network affiliations. SaaS draws from heavy third-party presence on G2, Reddit, and LinkedIn. Financial Services benefits from strong editorial media presence on platforms like MarketWatch, Bankrate, and NerdWallet.

Healthcare
29.1% Mention
19.8% Citation
SaaS
24.3% Mention
13.8% Citation
Financial Services
20.1% Mention
21.9% Citation
Cited but Rarely Mentioned

Legal Services

AI platforms use legal content as source material but almost never credit the brand behind it. The content performs, but the brand identity doesn't travel with it. Closing the gap means building the entity signals that connect content to a recognizable brand.

Legal Services
0.9% Mention
11.3% Citation

*Our prompts for legal services were informational in nature. Recommendation prompts, particularly those with local intent, would likely return results that mention specific firms more frequently.

Mentioned More Than Cited

E-commerce / Retail

This represents the widest gap in our dataset. AI platforms mention these brands but don't link to their content. Recognition comes from marketplace presence and consumer familiarity, but their content doesn't provide the substance AI platforms source from.

E-commerce / Retail
18.1% Mention
6.0% Citation
Finding 03 · Platform Intelligence

Where AI platforms source their answers.

AI platforms demonstrated preferred sources for their answers.
Ground your strategy in the platforms your buyers actually use.

Mention rates by platform and vertical

Deeper shading means a higher mention rate. — = data not reported.
Claude and Meta AI reflect training data, not real-time sourcing.

Platform Healthcare SaaS Financial E-commerce Legal
ChatGPT 34.2% 27.8% 23.4% 19.7% 1.2%
Perplexity 31.5% 26.1% 18.9% 17.4% 0.8%
Gemini 28.6% 24.9% 21.3% 18.2% 1.4%
Google AI Overview 26.4% 22.6% 23.8% 18.9% 0.7%
Google AI Mode 27.1% 21.4% 19.6% 17.1% 0.6%
Microsoft Copilot 25.8% 22.9% 18.1% 17.8% 0.9%
Claude 23.7% 20.2% 17.4% 16.5% —
Meta AI 21.3% 18.6% 14.2% 16.9% —

Most cited sources by platform

Each platform seems to pull from different sources. Ground your strategy in the platforms your buyers actually use.

ChatGPT
28% of tested brands

Reddit, Wikipedia, and industry-specific publications dominate. Editorial media and community-generated content drive the majority of citations.

Perplexity
34% of tested brands

Heavily favors news outlets and specialist publishers. Cites primary source material more often than any other platform we tested.

Gemini
22% of tested brands

Pulls from Google-indexed content with a strong preference for established brand domains and official documentation.

Google AI Overview
19% of tested brands

Mirrors traditional organic signals. If you rank in the top 3 organically, you're likely cited. Brand-owned content is favored.

Microsoft Copilot
26% of tested brands

LinkedIn, Microsoft-adjacent properties, and B2B publications over-index. Reflects Copilot's business-oriented user base.

Claude

Our data collection method couldn't access Claude's web search, so we don't have citation data for Claude in this report.

Finding 04 · Platform Intelligence

Authority correlates to organic growth. It doesn't correlate to AI visibility.

This table compares organic traffic growth to average domain authority for each vertical.

Vertical Avg. Authority Score Organic Traffic Trend
Healthcare 68 +12.4%
SaaS 62 +7.9%
Financial Services 71 +9.3%
E-commerce / Retail 58 -8.6%
Legal Services 54 +2.1%

*Data from Semrush US.

What we tested Correlation (r) What it means
Authority Score vs. mention rate 0.108 Negligible. DA does not predict whether AI names a brand.
Authority Score vs. citation rate 0.017 Essentially zero. DA does not predict whether AI links to a brand.
Organic traffic vs. mention rate 0.385 Moderate. Brands with more traffic are mentioned more often.
Organic traffic vs. citation rate 0.391 Moderate. Brands with more traffic are cited more often.

*Correlation (r) measures how closely two variables correspond, on a scale from -1 to 1.

Takeaway

Authority Score doesn't predict AI visibility.

In Q2, we'll test whether ranking keyword count is a stronger correlate than traffic volume alone, and whether entity signals like Knowledge Graph presence predict AI visibility more reliably.

Q1 2026 Industry News

Algorithm updates, platform changes, and market data.

The changes shaping the AI and organic search landscape this quarter.

  • January 22

    Google launches Personal Intelligence in AI Mode

    AI search results now pull from Gmail and Photos to deliver personalized answers based on a searcher's history and behavior.

    Why it matters: If a brand appears in a searcher's first AI interaction on a topic, personalization signals suggest it's more likely to keep appearing in future queries. For named-and-cited brands, this could widen their lead over time.

  • January 27

    AI Mode rolls out worldwide

    AI-powered search is now available to users worldwide.

    Why it matters: AI Mode is no longer an experiment or a US-only feature. Brands with international audiences can no longer treat AI visibility as a future problem.

  • February 5–27

    February 2026 Discover Core Update

    The first-ever Discover-specific core update, focused on surfacing more locally relevant content, reducing clickbait, and prioritizing in-depth original reporting in Discover feeds.

    Why it matters: Discover rewards content quality and editorial depth. Brands publishing thin content optimized for engagement metrics are now competing against brands publishing substantive reporting.

  • March 4

    AI Mode Canvas goes public in the US

    Before Canvas, AI search was read-only. Searchers can now pull from cited sources to write documents, build tables, and work with content directly inside Google Search.

    Why it matters: If a brand's content is one of those sources, it gets embedded in a working document the searcher keeps, shares, and uses to make a decision. Being cited in Canvas outputs creates durable brand exposure in the exact moment someone is making a decision.

  • March 24–25

    March 2026 Spam Update

    Completed in under 24 hours, the fastest confirmed spam update on record. Focused on detecting and demoting content violating spam policies.

    Why it matters: Google is moving faster on quality enforcement. Brands relying on AI-generated content at scale, low-quality backlinks, or keyword-stuffed pages have less runway between violation and penalty.

  • March 27 – April 8

    March 2026 Core Update

    A 12-day rollout with higher volatility than December 2025. Visibility shifted away from aggregators and comparison sites toward official sources, specialist publishers, and established brands.

    Why it matters: Google is rewarding brands that it recognizes as distinct, authoritative sources, which is consistent with what our data shows about entity clarity.

  • March 31

    ChatGPT enables location sharing

    ChatGPT now offers localized "near me" results based on user-shared location data.

    Why it matters: Any vertical where local intent drives volume now has a new competitive arena inside ChatGPT. Brands with strong local presence can compete directly with national brands on local queries.


Additional news

The market signals behind the headlines.

Reach
0B+

Monthly users reached by AI Overviews, across 200+ countries and 40 languages

Source: TechCrunch
Retail
+393%

Year-over-year growth in AI-driven traffic to US retail sites in Q1 2026.

Source: Search Engine Land
Adoption
0%

More AI platform visits in January 2026 vs. January 2025

Source: Similarweb
Behavior
0%

US consumers using AI at the product discovery stage

Source: Similarweb
Impact
0%

CTR reduction on top-ranking organic results when AI Overviews are present

Source: Ahrefs
Market Signals

What the market is asking.

We reviewed 200 prospect and client conversations this quarter. These themes came up consistently.

Q

How do we measure AI search impact?

A

Marketing teams see their brand appearing in AI-generated answers but can't connect that visibility to pipeline or revenue. Traditional analytics tools were not built to track how AI platforms use content. The methodology behind this report, tracking mention rates and citation rates across platforms, is one approach to measuring AI visibility at the brand level. But tying that visibility to downstream revenue remains an industry-wide challenge.

Q

What is entity SEO and why does it apply now?

A

Traditional SEO treats a website as a collection of pages competing for keywords. Entity SEO treats a brand as something search platforms can recognize and associate with specific products, topics, and areas of expertise. It's the difference between ranking for terms people search for and being known for what you do.

The reason it matters now is that AI systems use entity signals to connect ideas and generate credible answers to user questions. When your brand is clearly associated with what you do, your content is more likely to be trusted and cited in AI platforms, and by extension, your brand is more likely to be present at moments of customer consideration.

Looking Ahead

What we're watching for next quarter.

Three open questions we'll be tracking as we head into Q2.

Q1

Does personalization compound early AI visibility?

Google's Personal Intelligence update lets AI search pull signals from users' own Gmail and Photos, including past purchases and brand interactions. That means once a user engages with a brand, AI Mode is more likely to surface that brand again in future responses.

Our hypothesis

Brands that win a user's first AI-mediated interaction compound visibility faster than new entrants, because Personal Intelligence biases future results toward brands already present in that user's Google data.

Q2

Does Canvas shift the balance between mentions and citations?

Canvas in AI Mode gives searchers a side panel for drafting documents, building dashboards, and organizing projects over multiple sessions. Users can share and reference those outputs, unlike the conversational summaries AI Mode typically produces. That raises the bar on sourcing: when a user is building something they'll use later, AI needs to back its claims with citations, not just name-drop brands in passing.

Our hypothesis

Citation rates will rise relative to mention rates in Q2 as Canvas adoption grows and more AI Mode responses get routed through a document-first workflow.

Q3

What does the March core update mean for AI visibility?

Core updates reshape which content performs in traditional search. Whether that extends to AI-generated answers is an open question.

Our hypothesis

The brands rewarded by the March core update, those with clear authority and distinct identity, will show corresponding gains in AI mentions and citations in Q2.

Q4

How long until the measurement gap closes?

The tools to connect AI visibility to revenue are maturing quickly.

Our hypothesis

If GA4 integrations from AI visibility platforms deliver reliable data in Q2, it changes the conversation for every marketing team trying to tie AI search to pipeline.

Take Action

What to do next.

Start with one of these three paths, based on where you stand today.

Mentioned & Cited

Maintain and Expand

  • Audit AI crawl activity. Review server logs with your dev team to see which AI bots are crawling the site, which pages they prioritize, and how often they return.
  • Expand into adjacent topics. Build content around related questions and subtopics AI tends to group with your core themes.
  • Monitor by platform. Different AI systems trust different sources. Use tools like Scrunch, SEMrush AI Visibility Toolkit, or Ahrefs Brand Radar to monitor and adjust.
Cited but Not Mentioned

Strengthen Entity Signals

  • Improve structured data. Add organization schema. Keep brand details consistent and machine-readable across your site.
  • Build cross-platform brand presence. Establish visibility on platforms like Wikipedia, Wikidata, directories, and review sites to reinforce entity recognition.
  • Create content that ties directly to your brand. Original research, proprietary data, and expert commentary increase the likelihood that your brand will be mentioned.
Mentioned but Not Cited

Build Foundational Content

  • Invest in content AI can source. AI answers rarely cite product or category pages. Focus on buying guides, comparisons, expert reviews, and educational resources.
  • Improve structured data and brand signals. Use schema and consistent brand signals so AI systems can connect your authority to your content.
  • Lead with clear answers. Put direct, useful information at the top of the page. Nearly half of AI citations come from the first third of a page.

AI is changing how buyers discover brands.

Make sure you're visible wherever they search.

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