The 2026 AEO / GEO Benchmarks Report: What the Data Says About AI Search Visibility Across 10 Industries

The 2026 AEO / GEO Benchmarks Report: What the Data Says About AI Search Visibility Across 10 Industries

AI search is no longer a channel brands can observe from a safe distance and plan to address later. 

 

The data from 2025 and early 2026 is clear enough: AI-generated answers are reshaping how customers discover brands, which businesses get recommended, and which ones are absent from the conversation entirely, before a user ever reaches a website.

 

This benchmark report translates that shift into specific, industry-level data. 

 

It draws on an analysis of 17 million AI-generated responses, over 100 million AI citations, and approximately 21.9 million unique Google searches to establish the first definitive industry benchmarks for AEO (Answer Engine Optimization) and GEO (Generative Engine Optimization) performance across 10 key industry sectors.

 

The goal is simple: to give brands and marketing leaders the specific benchmark data they need to evaluate their current AI search visibility, understand what strong performance actually looks like in their sector, and make informed decisions about where to invest next.

 

One finding anchors everything that follows: AI has not replaced search. It has replaced your website as the first place customers engage with your brand. 

 

The brands winning in AI search in 2026 are not necessarily the ones with the highest organic traffic; they are the ones whose information is structured, credible, and consistent enough for AI systems to trust and cite. Understanding that distinction is the starting point for every strategy recommendation in this report.

 

2026 AEO / GEO Benchmarks Report

For years, organic search was the undisputed cornerstone of sustainable brand discovery online. 

 

An optimized piece of content, well-positioned for the right queries, could drive reliable traffic, qualified leads, and compounding returns for years after publication. 

 

The investment thesis was clear: build great content, earn rankings, capture traffic.

That thesis has not collapsed. But it has become incomplete.

 

The rise of AI answer engines, ChatGPT, Perplexity, Google's AI Overviews, Microsoft Copilot, Gemini, has introduced what this report calls a parallel surface of visibility: an invisible layer of brand discovery that determines which brands are seen inside AI answers before any user ever reaches a search results page. 

 

Visibility no longer begins on a website. It begins inside the AI experiences that answer questions, guide intent, and shape brand perception in real time.

 

In this new model, a brand can rank first on Google and still be invisible to a customer who used ChatGPT to research the same category. 

 

The customer's first impression of the competitive landscape is shaped entirely by which brands the AI chose to mention, and that decision is made on signals very different from the ones that determine Google rankings.

 

For digital marketing leaders, this creates a genuine measurement challenge: how do you benchmark success and measure share of voice on AI search surfaces, especially when AI-generated answers do not necessarily generate website clicks? 

 

Standard analytics cannot see this layer of the customer journey. Traditional rank tracking does not reflect it. The organizations that figure out how to measure and optimize for it first will have a structural advantage that becomes harder to close the longer they hold it.

 

This report provides the first layer of that measurement framework, industry by industry.

 

Key Findings at a Glance

Before the full analysis, here are the headline numbers from this research:

 

AI referral traffic benchmarks:

AI Overview benchmarks:

 

 

 

AI market share surprises:

 

 

 

AEO / GEO Methodology

This report analyzed 13,770 domains from leading brands, categorized into 10 industries and 22 subindustries mapping to the Global Industry Classification Standard (GICS) framework.

 

AEO and AI search methodology: The AI search market share data comes from analysis of those 13,770 domains cited against an index of 3.5 million unique prompts between May and September 2025. 

 

The analysis covered 17 million AI-generated responses and over 100 million citations.

 

AI search traffic benchmarks were sourced from anonymized and aggregated traffic patterns across 1,215 enterprise customer domains, analyzing more than 3.3 billion total sessions, of which AI traffic from LLMs and chatbots accounted for more than 35.7 million sessions.

 

AI Overview methodology: AIO data was analyzed in the U.S. over four weeks from September 15 to October 12, 2025, examining approximately 21.9 million unique Google searches, of which nearly 5.5 million generated an AIO result.

 

The 10 industries covered: Communication Services, Consumer Discretionary, Consumer Staples, Financials, Health Care, Industrials, Information Technology, Materials, Real Estate, and Utilities.

 

 

AI Referral Traffic: What the Numbers Actually Mean

The 1% Number Is Not Small

AI referral traffic accounting for 1.08% of total website traffic sounds, at first, like a number too small to act on. That reading misses what the number actually represents.

 

That 1% is not 1% of the full discovery funnel; it is 1% of the traffic that makes it to a website at all. 

 

AI-mediated discovery is happening before that click, in the AI-generated answer the user read, the brand recommendation they received, and the decision they made about which brand to research further. 

 

The clicks are the downstream effect of AI visibility decisions that already happened upstream. 

 

A brand that is invisible in AI-generated answers is losing customer awareness at the very first moment of the journey, regardless of how many people eventually land on its website through other channels.

 

There is also a quality dimension to this traffic that the volume number understates.

 

 Research across multiple sources consistently shows that users referred to a website from an LLM or AI tool convert at significantly higher rates than traffic from most other channels. 

 

Visitors referred from AI search tools convert at roughly twice the rate and in approximately one-third the number of sessions compared to other traffic sources.

 

This makes sense: a user who has already received an AI-generated recommendation and then clicked through to verify or learn more is considerably further along in their decision process than a user who clicked a search result out of general curiosity.

 

The 1.08% benchmark, in other words, understates both the competitive significance of AI visibility and the quality of the audience it delivers.

 

Why Industry Variation Matters

The spread between the highest (IT at 2.80%) and lowest (Communication Services at 0.25%) AI referral traffic rates across these 10 industries reflects meaningful differences in how people use AI tools to research different types of decisions.

 

Information Technology leads because IT queries are often complex, multi-step problems where a synthesized AI answer is genuinely useful but not sufficient; users click through to documentation, how-to guides, and product pages to go deeper. The AI answer creates qualified intent that leads to a click.

 

Consumer Staples follows at 1.91% because the category contains a high volume of how-to, recipe, and comparative content where users read an AI summary and then want the full recipe, the detailed comparison, or the specific product recommendation with more context than the AI provided.

 

Communication Services and Utilities trail because these categories involve more transactional, localized, or regulatory-specific queries where AI tools are less likely to provide the definitive answer a user needs, or where users are going directly to their provider rather than researching through AI.

 

The practical implication for brands is that AI visibility strategy needs to be calibrated to category-specific behavior. 

 

An IT software company and a utility company face genuinely different AI visibility dynamics; the content depth, format, and optimization approach that drives AI citation in one category may look very different in the other.

 

ChatGPT's Dominance and What It Means for Multi-Platform Strategy

ChatGPT driving 87.4% of all AI referral traffic across these 10 industries is a striking number, but the strategic interpretation requires care. 

 

The dominance of ChatGPT in referral traffic does not mean other platforms are irrelevant; it means other platforms are part of the discovery process even when they are not the final click.

 

A user might ask Perplexity which brands are credible in a category, form a shortlist from that answer, and then ask ChatGPT for a more detailed comparison before clicking through. 

 

Both platforms shaped the discovery, but only ChatGPT generates the attributable referral. The full AI visibility picture requires tracking citation and mention frequency across all major platforms, not just the one that drives the most attributable clicks.

 

There are also meaningful industry exceptions. Gemini drove 21% of AI traffic to the Utilities industry, a significantly higher share than Gemini achieves in most other categories. Copilot accounted for 5% of Financials AI traffic. 

 

These outliers confirm that optimizing for ChatGPT alone, while necessary, is not sufficient for every industry.

 

The right approach is a holistic AI visibility strategy that builds the structural signals, entity clarity, content depth, cross-source consistency, E-E-A-T, that earn citations across all major AI platforms simultaneously, rather than platform-by-platform optimization that cannot keep up with the rapidly evolving AI search landscape.

 

AEO Market Share Leaders: What the Industry Data Reveals

This section summarizes the brands and domains winning the most AI citations and brand mentions across 17 million AI-generated responses. 

 

The patterns across industries reveal consistent principles about what drives AI search market share.

 

Communication Services: Authority Platforms and Video Dominate

Top domains by AI citation share: YouTube, Reddit, Google, Investopedia, Reuters

Top brands by AI mention share: Google, YouTube, Investopedia, Roku, Forbes

The dominance of YouTube in Communication Services citation data reflects a structural advantage: 

 

AI models frequently cite video content as an authoritative source for how-to guides, explainers, and news clips, and YouTube is the hosting domain that receives the citation credit regardless of which brand produced the video. 

 

The implication for any brand in this category is that YouTube-hosted video content, properly optimized with titles, descriptions, and transcripts that are AI-legible, represents one of the highest-ROI AI visibility investments available.

 

Reddit's strong showing confirms what content strategists have been observing: AI systems frequently draw on forum discussions to provide authentic, user-experience-grounded answers to questions where corporate content sounds too promotional to be trusted. 

 

Brands that participate genuinely in community platforms where their customers are discussing real problems are building indirect AI visibility signals through those communities.

Consumer Discretionary: A University Rewrites the Playbook

Top domains by AI citation share: Clemson University, Walmart, Target, Four Seasons, Cornell.

 

Top brands by AI mention share: Walmart, Target, Miele, Sonos, Nike.

 

The most striking finding in Consumer Discretionary is the presence of Clemson University at the top of the citation list, not a retailer, not a brand with massive advertising spend, but a university that deliberately invested in an AI visibility content strategy. 

 

Clemson's approach, AI-powered topic research, strategic content prioritization, AI-assisted creation, and structured data implementation, produced 91% AIO market share in its category.

 

This is the clearest available proof that AI citation market share is not simply a function of brand size or domain authority. 

 

It is a function of how well content is structured, how clearly expertise is demonstrated, and how systematically AI visibility is managed as a discipline. Clemson beat much larger competitors because it treated AI visibility as a strategy rather than an accident.

 

The presence of Miele, Sonos, and Nike alongside Walmart and Target in brand mentions also reveals that AI is fielding highly specific, branded queries in this category, users are asking for specific brands, not just generic categories, which rewards brands that have built clear, consistent entity signals.

 

Financials: Publishers Are Beating Banks at Their Own Game

Top domains by AI citation share: NerdWallet, Bankrate, Kiplinger, Vanguard, Experian.

 

Top brands by AI mention share: NerdWallet, PayPal, Bankrate, Vanguard, Fidelity.

The Financials finding is counterintuitive and important: publisher and comparison sites are significantly outperforming major banks in AI citation share, despite many of those same sites losing ground in traditional search. 

 

NerdWallet and Bankrate lead the citation rankings over JPMorgan, Bank of America, and other household-name institutions, because their extensive libraries of long-form, educational financial content are exactly the kind of authoritative, Q&A-structured material that AI systems prefer to cite for YMYL (Your Money Your Life) queries.

 

This is both a warning for traditional financial institutions and an opportunity. 

 

The banks that start building the kind of deep, specific, clearly expert financial content that AI systems can confidently cite, rather than relying on brand recognition and paid distribution, will close this gap over time. 

 

The ones that do not will continue to see publishers capture the AI discovery moments that should belong to them.

 

Health Care: Depth and Institutional Authority Win

Top domains by AI citation share: Mayo Clinic, Cleveland Clinic, Healthline, GoodRx, WebMD.

 

Top brands by AI mention share: Mayo Clinic, Cleveland Clinic, Pfizer, Labcorp, Baptist Health.

 

Health Care has the highest AIO trigger rate of any industry at 48.75%, which reflects the complexity and research-intensity of health-related queries. 

 

When nearly half of all relevant Google searches trigger an AI Overview, being consistently cited in those overviews is not a competitive advantage; it is table stakes.

 

Mayo Clinic and Cleveland Clinic lead both citation and brand mention rankings because they have built what are effectively AI citation machines: comprehensive, regularly updated, expert-attributed health libraries that answer thousands of specific medical questions with the depth, accuracy, and institutional authority that AI systems weight heavily in YMYL categories. 

 

Their traditional SEO and AI visibility performance reinforce each other, confirming that the signals driving strong traditional search performance and strong AI citation frequency are largely the same.

 

Industrials: Thought Leadership Infrastructure Pays Off

Top domains by AI citation share: Deloitte, Indeed, McKinsey, Wolters Kluwer, Siemens.

 

Top brands by AI mention share: Deloitte, Amazon Web Services, Siemens, ADP, McKinsey.

 

In Industrials, the citation leaders are the brands that have invested most heavily in original thought leadership: white papers, industry analysis, market reports, and research that goes well beyond promotional content. 

 

Deloitte and McKinsey lead because their published content addresses the complex, B2B-specific questions that AI systems encounter when users research business strategy, industry trends, and professional services decisions.

 

The high rank of Amazon Web Services in brand mentions signals that AI conversations in the Industrials sector are heavily weighted toward digital transformation and cloud infrastructure, a content opportunity for technology and services brands positioning themselves in this space.

 

Information Technology: Technical Depth and Documentation Drive Citations

Top domains by AI citation share: Google, Microsoft, SAP, Dell, Adobe.

 

Top brands by AI mention share: Google, Microsoft, SAP, Apple, Adobe.

 

IT brands benefit from a structural advantage in AI citation: their products generate enormous volumes of technical queries, and their official documentation, support content, and how-to guides are exactly the kind of specific, verifiable, structured information that AI systems prefer to cite. 

 

Google and Microsoft lead because they are the authoritative source on their own products, and their products generate a disproportionate share of the category's queries.

 

The lesson for mid-market and smaller IT brands is that documentation-quality content, specific, accurate, well-structured, and regularly updated, is one of the highest-ROI content investments available for building AI citation frequency in technical categories.

 

Real Estate: Brand Recognition Outperforms Domain Citation

Top domains by AI citation share: Hines (11.62%), Public Storage (10.49%), CBRE (7.37%), Extra Space (7.28%), Colliers (5.15%).

 

Top brands by AI mention share: Hines, Public Storage, CBRE, Zillow, Colliers

Real Estate has the lowest AIO trigger rate of any industry at 4.48%, consistent with the localized, transactional nature of most real estate queries where AI-generated summaries add less value than specific, current local data.

 

The Zillow finding is instructive: Zillow does not appear in the top 5 cited domains, but it does appear prominently in brand mentions, meaning AI systems recognize Zillow as the go-to brand for residential real estate queries without necessarily citing its domain as the authoritative source for those answers. 

 

This brand recognition effect, where AI models discuss a brand without necessarily linking to it, represents a form of AI visibility that standard referral traffic measurements cannot capture, and that makes brand mention tracking as important as domain citation tracking.

 

AI Overview Benchmarks: Which Industries Are Most Affected

The 25% Trigger Rate Benchmark

Of the 21.9 million Google searches analyzed, 25.11% triggered an AI Overview result, just over one in four searches. This establishes the base benchmark against which every industry's AIO exposure can be evaluated.

 

The distribution across industries is far from uniform, and the pattern reflects a clear principle: AI Overviews are triggered most heavily for informational, research-intensive, and YMYL queries, and least heavily for transactional, localized, or highly specific queries.

 

Industries with the highest AIO trigger rates:

 

 

 

Industries with the lowest AIO trigger rates:

 

For brands in high-trigger-rate industries like Health Care and Financials, appearing in AIO results is already a primary driver of zero-click brand awareness, and the brands that are not appearing are losing awareness at significant scale. 

 

For brands in low-trigger-rate industries, the current AIO opportunity is smaller but growing, and the brands that build the content infrastructure now will be positioned for the trigger rate increases that the data suggests are coming.

 

Which Content Types Win the Most AIO Citations

Across all 10 industries, five page types dominate AIO citation results:

 

  1. Blog content: long-form, informational content that addresses specific questions with depth.
  2. Video content: particularly YouTube-hosted video with transcripts and strong metadata.
  3. Article content: journalistic and editorial coverage by recognized publishers.
  4. News content: current, dated, source-attributed news and announcements.
  5. Product pages: specific, well-structured product information with clear attributes and specifications.

This distribution confirms that AI Overviews function primarily as synthesizers of informational and educational content. 

 

The brands appearing most frequently in AIO results are not those with the most product pages or the most aggressively promotional content; they are the ones with the deepest, most specific, most credibly sourced educational content in their categories.

 

The practical direction for brands is not to create entirely new content categories but to build on what already drives traditional search performance: authoritative blog content, video with full transcripts, expert-attributed articles, and well-structured product information. 

 

The optimization difference is in ensuring that content is structured for AI legibility, with schema markup, clear entity relationships, and specific factual claims, not just for human readability and keyword matching.

 

What the Benchmarks Tell Us About Winning AI Visibility Strategy

Looking across all 10 industries and both the AEO referral traffic data and the AIO trigger rate data, five consistent strategic patterns emerge among the brands leading their categories in AI search market share.

 

Pattern 1: Educational Content Depth Beats Promotional Volume

In every industry where publishers or educational institutions appear alongside or above brand names in citation rankings, Financials, Health Care, Industrials, Communication Services, the underlying pattern is the same. 

 

The leaders built comprehensive, expert-attributed, question-answering content libraries that address the specific queries users bring to AI systems, rather than content designed primarily to promote their own products.

 

The implication is direct: AI citation market share is earned through content that is genuinely useful to a user asking a question, not through content primarily designed to drive conversion. 

 

Brands that reorient even a portion of their content investment toward educational depth, specific, accurate, expert-attributed answers to the questions their customers actually ask, will see AI citation frequency improve over time.

 

Pattern 2: Structural Signals Matter as Much as Content Quality

The Clemson University case study demonstrates that a deliberate AI visibility strategy, structured data implementation, entity optimization, and content prioritization based on AI citation research, can produce market-leading outcomes even in competitive categories. 

 

Clemson achieved 91% AIO market share not because its brand was dominant but because its content was more clearly structured for AI legibility than its competitors'.

 

For brands using tools like the Yieldberg AI Visibility Tool from Yieldberg Studios, this pattern suggests a specific workflow: use the gap analysis output to identify which content areas have the highest AI citation opportunity, prioritize structural improvements (schema markup, entity linking, content depth) over volume, and track citation frequency changes as those improvements are deployed.

 

Pattern 3: Brand Mention Visibility and Domain Citation Visibility Are Different Problems

Zillow in Real Estate and New Fortress Energy in Utilities both demonstrate a pattern where brand mention frequency in AI answers significantly outpaces domain citation frequency. 

 

This means AI systems are discussing these brands as subjects without necessarily linking to their websites, a form of visibility that creates brand awareness and influences consideration but generates no attributable referral traffic.

 

This distinction matters for how brands set up their AI visibility measurement. Tracking only AI referral traffic misses the significant brand awareness impact of AI answers that mention a brand without generating a click. 

 

A complete AI visibility measurement framework tracks both domain citation frequency and brand mention frequency, and recognizes that the gap between the two often reveals the most important optimization opportunities.

 

Pattern 4: Traditional SEO and AI Visibility Reinforce Each Other

Across every industry analyzed, the brands with the strongest traditional organic search performance tend to also lead in AI citation frequency. 

 

This is not a coincidence, the signals that make content trustworthy and authoritative for Google's traditional ranking algorithm (depth, accuracy, expert attribution, cross-source corroboration) are largely the same signals that make content trustworthy and citable for AI systems.

 

This means brands do not face a binary choice between traditional SEO and AEO/GEO investment. 

 

The most effective strategies treat them as a unified discipline: creating content that is deeply researched, expertly attributed, well-structured, and consistently accurate across all digital touchpoints. That content earns traditional search rankings and AI citations through the same underlying quality signals.

 

Pattern 5: YMYL Categories Face the Highest Stakes

Health Care, Financials, and other Your Money Your Life categories have both the highest AIO trigger rates and the most concentrated citation patterns, where a small number of highly authoritative sources dominate AI citations by a wide margin. 

 

The stakes for brands in these categories are correspondingly higher: the difference between appearing in an AI Overview that triggers for nearly half of all relevant queries and being absent from those overviews is enormous in terms of reach and brand awareness.

 

For brands in YMYL categories, AI visibility is not a nice-to-have optimization, it is a core brand presence issue. 

 

And the authority signals required to win in YMYL AI citations (verified expertise, institutional credibility, cross-source corroboration) require sustained, deliberate investment rather than tactical content campaigns.

 

How to Benchmark Your Brand's AI Search Visibility

The industry data in this report establishes where the market currently stands. The question for any individual brand is: where do I stand relative to these benchmarks, and what is the most efficient path to improving?

 

Answering that question requires measurement that most brands are not yet running.

 

AI referral traffic in a standard analytics dashboard captures the clicks that happen after an AI recommendation, but it misses the citations, mentions, and brand awareness that happen before any click. 

 

It cannot show whether a brand is being described accurately, whether competitors are gaining citation share in relevant query categories, or which specific content gaps are preventing the brand from appearing in AI answers where competitors are already present.

 

This is the measurement gap the Yieldberg AI Visibility Tool from Yieldberg Studios is built to close. 

 

By tracking citation frequency, brand representation accuracy, and competitive positioning across ChatGPT, Perplexity, and Google's AI Overviews, and surfacing a prioritized gap analysis tied directly to actionable content and structural improvements, it provides the measurement foundation that turns AI visibility benchmarking from a one-time snapshot into an ongoing, manageable discipline.

 

For brands looking to benchmark their own performance against the industry data in this report, the starting point is a systematic audit: query the AI platforms your customers use with the questions they are actually asking, document where your brand appears and where it does not, evaluate the accuracy of AI representations of your brand, and compare your citation frequency to the competitors appearing in the same answers. 

 

That baseline is the necessary foundation for any strategy designed to improve on it.

 

AI Visibility Is the Next Performance Channel

The data in this report paints a consistent picture across 10 industries and more than 3 billion analyzed sessions. 

 

AI search is still a small share of total web traffic, but it is a large and growing share of the brand discovery moments that happen before any traffic is generated. 

 

The brands winning AI citation market share today are building awareness and consideration advantages that traditional analytics cannot see, but that show up in search volume, direct traffic, and conversion rates downstream.

 

The benchmarks established here- 1.08% average AI referral traffic, 25.11% AIO trigger rate, ChatGPT driving 87.4% of AI referrals- are starting points, not endpoints. 

 

Every industry will see these numbers shift as AI adoption accelerates, as new AI platforms mature, and as the brands that have invested early in AI visibility infrastructure pull further ahead of those that have not.

 

The organizations that adapt first, measuring AI visibility as rigorously as they measure SEO performance, investing in the content depth and structural clarity that AI systems require, and tracking citation share alongside traditional rankings as a core KPI, are building positions that will compound in value as this shift continues.

 

The parallel surface of visibility is real; it is growing, and the brands on it are shaping the customer journey before it ever reaches a website. The question is whether your brand is one of them.

 

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