Measuring AI Visibility in Different Industries.
Measuring AI Visibility in Different Industries.
Measuring AI Visibility in Different Industries.
Last updated 5 October 2026 by Ema Fulga
AI search has officially made its runway debut. Vogue just named “AI Visibility” fashion’s newest engagement metric, and brands everywhere are rushing to add it to their dashboards.
Here’s the problem: every industry is borrowing the term wholesale, as if it means one universal thing. It doesn’t. What counts as showing up in AI search looks completely different for a handbag label, a property developer, a SaaS platform and the bakery round the corner.
Here’s what AI Visibility actually means across different categories right now, with a reality check at the end because, like any good coach, we’d rather tell you now than at the finish line.
Picture yourself at the Olympics, on the start line of the 200 metre sprint. The pistol fires, you give it everything, and miraculously you cross the line first. Then, before the gold medal goes anywhere near your neck, an official tells you that you didn’t win.
Why? You didn’t jump high enough. The sprint and the high jump are both track and field events, but nobody would dream of scoring them the same way. That’s exactly how we need to think about AI Visibility across industries.
Vogue gave AI Visibility a name. That’s the good news
Vogue's piece did fashion a genuine favour. Brands were already circling the question "Are we showing up when people ask ChatGPT what to buy?" and Vogue gave it a label and a clean definition. Naming something is the first step to measuring it properly.
But (there's always a but!) every shiny new metric gets copied before anyone checks whether it fits their category. We saw it with engagement rate a decade ago. It meant one thing to a media publisher and something else entirely to a DTC brand, yet everyone reported it identically. AI Visibility is heading the same way, only faster, because every vertical is adopting it at once.
One term, five different mechanisms
The moment Vogue describes is a specific one: a generative engine names a product inside an answer, the way Gemini might surface a handbag label when someone asks what's trending. It's real, but it's only one of several mechanisms, and it isn't the one most brands are competing on.
Here's what "does my brand show up in AI search?" really means, category by category:
Fashion and retail: getting named in the recommendation
What visibility means: a citation inside a generated product recommendation. The model is answering “what should I buy?” and your brand is either in that answer or it isn’t. IAB research found that 72% of consumers now use general-purpose AI assistants for shopping decisions, while Adobe reports AI-referred visits to US retail sites grew 393% year on year in Q1 2026 and converted 42% better than non-AI channels.
In the EMARKETER AI Visibility Index, Levi’s appeared in 74% of ChatGPT’s denim recommendations.
What moves the needle: editorial coverage and creator content, with 65% of AI shoppers more confident when recommendations draw on credible creator reviews.
Real estate: making the shortlist
What visibility means: a citation inside a generated product recommendation. The model is answering "what should I buy?" and your brand is either in that answer or it isn't. This is the mechanism Vogue is describing.
The numbers: IAB research found that 72% of consumers now use general-purpose AI assistants for shopping decisions. The traffic is following: Adobe reports AI-referred visits to US retail sites grew 393% year on year in Q1 2026, and that traffic converted 42% better than non-AI channels. Once a brand owns the answer, it really owns it. In the EMARKETER AI Visibility Index, Levi's appeared in 74% of ChatGPT's denim recommendations.
What moves the needle: editorial coverage and creator content. The same IAB study found 65% of AI shoppers feel more confident in a recommendation when it draws on credible creator reviews.
Local and challenger retail: proving you exist
What visibility means: whether the model knows you exist at all, before a recommendation is even on the table. This is big brand bias in action. Incumbents get named by default because there's far more training data and citable coverage about them.
The numbers: a Lightspeed Commerce study of around 460,000 AI responses found ChatGPT and Google's AI tools picked a national chain over a smaller rival up to 94% of the time in head-to-head comparisons. Switching on live web search narrowed the gap but didn't close it, with chains still taking 46 to 58% of recommendations. Writing in Fortune, Lightspeed's CEO noted that large and small retailers each made up roughly 38% of the sources AI cited, yet big chains walked away with 52% of the top recommendations against 20% for smaller businesses.
What moves the needle: for a challenger, the win condition isn't beating the market leader. It's getting mentioned at all. Being cited as a source isn't enough if the model still names someone else first.
B2B and SaaS: winning the comparison
What visibility means: placement inside a comparison answer. Buyers ask for the "best CRM for a 10-person sales team" or "X vs Y", and the model pulls together review sites, G2-style listings and documentation.
The numbers: G2's survey of 1,076 B2B software buyers found that half now start their software research with an AI chatbot. The single most common use? Weighing up vendors' strengths and weaknesses against each other (41%), ahead of basic product research or finding vendors in the first place.
What moves the needle: structured, comparison-ready content. Cultural buzz counts for far less here than clear pricing, feature tables, honest use-case pages and a healthy presence on review platforms.
Regional and local services: surfacing in your area
What visibility means: turning up at all when someone asks a location-based question, like the best physio near them or a family lawyer in their city.
The numbers: BrightLocal's Local Consumer Review Survey 2026 found 45% of consumers used ChatGPT or other AI tools for local business recommendations, up from just 6% the year before. That makes AI the third most popular source for local recommendations. But doing well on Google doesn't carry over automatically. Across more than 200,000 localised searches, BrightLocal found Google Maps mentioned a tracked business in 66% of searches, compared with 32 to 38% across AI platforms.
What moves the needle: local citations, structured business data and consistency. According to SOCi's 2026 Local Visibility Index, as summarised by BrightLocal, only 68% of business contact details on ChatGPT and Perplexity match what's on Google Business Profiles, and fewer than half of the businesses leading Google's local results also appear in AI recommendations.
Same word. Five completely different events.
Remember our Olympic sprinter? Turns out the stadium is hosting a full athletics programme. Sprinters, high jumpers and marathon runners all wear the same kit, but each one is judged on something different.
One blended score will mislead you.
Now, before you paste a single AI Visibility number into next month's board deck, a few warnings:
It hides which game you're playing. A real estate brand tracking visibility with a fashion-style recommendation model is optimising for a moment that barely exists in its category.
It sends your content budget to the wrong place. Press and creator buzz move a recommendation metric. Comparison content moves a consideration-set metric. Consistent local business data moves a geographic one. Get the mechanism wrong and you'll do a lot of GEO work for very little citation gain.
It makes benchmarks meaningless. A 15% mention rate could be a strong result for a challenger fighting incumbent bias and a weak one for a category leader. Without knowing the mechanism, the number tells you almost nothing (and single snapshots are closer to noise than signal anyway).
It turns a useful insight into a vanity metric. Reporting AI Visibility as one line item to a board flattens a valuable distinction, the exact trap engagement rate fell into.
So where does that leave brands? Here are the three takeaways that matter to business:
AI Visibility is real, but Vogue's definition describes one mechanism (product recommendation), not a universal standard.
The same phrase covers at least five mechanisms: recommendation, consideration set, brand existence, comparison placement and geographic surfacing. Your category decides which one you're competing on.
This is the bit most people miss. Brands won't win by chasing one generic score. They'll win by identifying their category's mechanism first, then matching what they publish, structure and monitor to it.
Not sure whether your AI Visibility number is measuring a recommendation, a consideration set or just whether the model knows you exist? Drop decipher. a line. We'll tell you which race you're really running.
Last updated 5 October 2026 by Ema Fulga
AI search has officially made its runway debut. Vogue just named “AI Visibility” fashion’s newest engagement metric, and brands everywhere are rushing to add it to their dashboards.
Here’s the problem: every industry is borrowing the term wholesale, as if it means one universal thing. It doesn’t. What counts as showing up in AI search looks completely different for a handbag label, a property developer, a SaaS platform and the bakery round the corner.
Here’s what AI Visibility actually means across different categories right now, with a reality check at the end because, like any good coach, we’d rather tell you now than at the finish line.
Picture yourself at the Olympics, on the start line of the 200 metre sprint. The pistol fires, you give it everything, and miraculously you cross the line first. Then, before the gold medal goes anywhere near your neck, an official tells you that you didn’t win.
Why? You didn’t jump high enough. The sprint and the high jump are both track and field events, but nobody would dream of scoring them the same way. That’s exactly how we need to think about AI Visibility across industries.
Vogue gave AI Visibility a name. That’s the good news
Vogue's piece did fashion a genuine favour. Brands were already circling the question "Are we showing up when people ask ChatGPT what to buy?" and Vogue gave it a label and a clean definition. Naming something is the first step to measuring it properly.
But (there's always a but!) every shiny new metric gets copied before anyone checks whether it fits their category. We saw it with engagement rate a decade ago. It meant one thing to a media publisher and something else entirely to a DTC brand, yet everyone reported it identically. AI Visibility is heading the same way, only faster, because every vertical is adopting it at once.
One term, five different mechanisms
The moment Vogue describes is a specific one: a generative engine names a product inside an answer, the way Gemini might surface a handbag label when someone asks what's trending. It's real, but it's only one of several mechanisms, and it isn't the one most brands are competing on.
Here's what "does my brand show up in AI search?" really means, category by category:
Fashion and retail: getting named in the recommendation
What visibility means: a citation inside a generated product recommendation. The model is answering “what should I buy?” and your brand is either in that answer or it isn’t. IAB research found that 72% of consumers now use general-purpose AI assistants for shopping decisions, while Adobe reports AI-referred visits to US retail sites grew 393% year on year in Q1 2026 and converted 42% better than non-AI channels.
In the EMARKETER AI Visibility Index, Levi’s appeared in 74% of ChatGPT’s denim recommendations.
What moves the needle: editorial coverage and creator content, with 65% of AI shoppers more confident when recommendations draw on credible creator reviews.
Real estate: making the shortlist
What visibility means: a citation inside a generated product recommendation. The model is answering "what should I buy?" and your brand is either in that answer or it isn't. This is the mechanism Vogue is describing.
The numbers: IAB research found that 72% of consumers now use general-purpose AI assistants for shopping decisions. The traffic is following: Adobe reports AI-referred visits to US retail sites grew 393% year on year in Q1 2026, and that traffic converted 42% better than non-AI channels. Once a brand owns the answer, it really owns it. In the EMARKETER AI Visibility Index, Levi's appeared in 74% of ChatGPT's denim recommendations.
What moves the needle: editorial coverage and creator content. The same IAB study found 65% of AI shoppers feel more confident in a recommendation when it draws on credible creator reviews.
Local and challenger retail: proving you exist
What visibility means: whether the model knows you exist at all, before a recommendation is even on the table. This is big brand bias in action. Incumbents get named by default because there's far more training data and citable coverage about them.
The numbers: a Lightspeed Commerce study of around 460,000 AI responses found ChatGPT and Google's AI tools picked a national chain over a smaller rival up to 94% of the time in head-to-head comparisons. Switching on live web search narrowed the gap but didn't close it, with chains still taking 46 to 58% of recommendations. Writing in Fortune, Lightspeed's CEO noted that large and small retailers each made up roughly 38% of the sources AI cited, yet big chains walked away with 52% of the top recommendations against 20% for smaller businesses.
What moves the needle: for a challenger, the win condition isn't beating the market leader. It's getting mentioned at all. Being cited as a source isn't enough if the model still names someone else first.
B2B and SaaS: winning the comparison
What visibility means: placement inside a comparison answer. Buyers ask for the "best CRM for a 10-person sales team" or "X vs Y", and the model pulls together review sites, G2-style listings and documentation.
The numbers: G2's survey of 1,076 B2B software buyers found that half now start their software research with an AI chatbot. The single most common use? Weighing up vendors' strengths and weaknesses against each other (41%), ahead of basic product research or finding vendors in the first place.
What moves the needle: structured, comparison-ready content. Cultural buzz counts for far less here than clear pricing, feature tables, honest use-case pages and a healthy presence on review platforms.
Regional and local services: surfacing in your area
What visibility means: turning up at all when someone asks a location-based question, like the best physio near them or a family lawyer in their city.
The numbers: BrightLocal's Local Consumer Review Survey 2026 found 45% of consumers used ChatGPT or other AI tools for local business recommendations, up from just 6% the year before. That makes AI the third most popular source for local recommendations. But doing well on Google doesn't carry over automatically. Across more than 200,000 localised searches, BrightLocal found Google Maps mentioned a tracked business in 66% of searches, compared with 32 to 38% across AI platforms.
What moves the needle: local citations, structured business data and consistency. According to SOCi's 2026 Local Visibility Index, as summarised by BrightLocal, only 68% of business contact details on ChatGPT and Perplexity match what's on Google Business Profiles, and fewer than half of the businesses leading Google's local results also appear in AI recommendations.
Same word. Five completely different events.
Remember our Olympic sprinter? Turns out the stadium is hosting a full athletics programme. Sprinters, high jumpers and marathon runners all wear the same kit, but each one is judged on something different.
One blended score will mislead you.
Now, before you paste a single AI Visibility number into next month's board deck, a few warnings:
It hides which game you're playing. A real estate brand tracking visibility with a fashion-style recommendation model is optimising for a moment that barely exists in its category.
It sends your content budget to the wrong place. Press and creator buzz move a recommendation metric. Comparison content moves a consideration-set metric. Consistent local business data moves a geographic one. Get the mechanism wrong and you'll do a lot of GEO work for very little citation gain.
It makes benchmarks meaningless. A 15% mention rate could be a strong result for a challenger fighting incumbent bias and a weak one for a category leader. Without knowing the mechanism, the number tells you almost nothing (and single snapshots are closer to noise than signal anyway).
It turns a useful insight into a vanity metric. Reporting AI Visibility as one line item to a board flattens a valuable distinction, the exact trap engagement rate fell into.
So where does that leave brands? Here are the three takeaways that matter to business:
AI Visibility is real, but Vogue's definition describes one mechanism (product recommendation), not a universal standard.
The same phrase covers at least five mechanisms: recommendation, consideration set, brand existence, comparison placement and geographic surfacing. Your category decides which one you're competing on.
This is the bit most people miss. Brands won't win by chasing one generic score. They'll win by identifying their category's mechanism first, then matching what they publish, structure and monitor to it.
Not sure whether your AI Visibility number is measuring a recommendation, a consideration set or just whether the model knows you exist? Drop decipher. a line. We'll tell you which race you're really running.
Last updated 5 October 2026 by Ema Fulga
AI search has officially made its runway debut. Vogue just named “AI Visibility” fashion’s newest engagement metric, and brands everywhere are rushing to add it to their dashboards.
Here’s the problem: every industry is borrowing the term wholesale, as if it means one universal thing. It doesn’t. What counts as showing up in AI search looks completely different for a handbag label, a property developer, a SaaS platform and the bakery round the corner.
Here’s what AI Visibility actually means across different categories right now, with a reality check at the end because, like any good coach, we’d rather tell you now than at the finish line.
Picture yourself at the Olympics, on the start line of the 200 metre sprint. The pistol fires, you give it everything, and miraculously you cross the line first. Then, before the gold medal goes anywhere near your neck, an official tells you that you didn’t win.
Why? You didn’t jump high enough. The sprint and the high jump are both track and field events, but nobody would dream of scoring them the same way. That’s exactly how we need to think about AI Visibility across industries.
Vogue gave AI Visibility a name. That’s the good news
Vogue's piece did fashion a genuine favour. Brands were already circling the question "Are we showing up when people ask ChatGPT what to buy?" and Vogue gave it a label and a clean definition. Naming something is the first step to measuring it properly.
But (there's always a but!) every shiny new metric gets copied before anyone checks whether it fits their category. We saw it with engagement rate a decade ago. It meant one thing to a media publisher and something else entirely to a DTC brand, yet everyone reported it identically. AI Visibility is heading the same way, only faster, because every vertical is adopting it at once.
One term, five different mechanisms
The moment Vogue describes is a specific one: a generative engine names a product inside an answer, the way Gemini might surface a handbag label when someone asks what's trending. It's real, but it's only one of several mechanisms, and it isn't the one most brands are competing on.
Here's what "does my brand show up in AI search?" really means, category by category:
Fashion and retail: getting named in the recommendation
What visibility means: a citation inside a generated product recommendation. The model is answering “what should I buy?” and your brand is either in that answer or it isn’t. IAB research found that 72% of consumers now use general-purpose AI assistants for shopping decisions, while Adobe reports AI-referred visits to US retail sites grew 393% year on year in Q1 2026 and converted 42% better than non-AI channels.
In the EMARKETER AI Visibility Index, Levi’s appeared in 74% of ChatGPT’s denim recommendations.
What moves the needle: editorial coverage and creator content, with 65% of AI shoppers more confident when recommendations draw on credible creator reviews.
Real estate: making the shortlist
What visibility means: a citation inside a generated product recommendation. The model is answering "what should I buy?" and your brand is either in that answer or it isn't. This is the mechanism Vogue is describing.
The numbers: IAB research found that 72% of consumers now use general-purpose AI assistants for shopping decisions. The traffic is following: Adobe reports AI-referred visits to US retail sites grew 393% year on year in Q1 2026, and that traffic converted 42% better than non-AI channels. Once a brand owns the answer, it really owns it. In the EMARKETER AI Visibility Index, Levi's appeared in 74% of ChatGPT's denim recommendations.
What moves the needle: editorial coverage and creator content. The same IAB study found 65% of AI shoppers feel more confident in a recommendation when it draws on credible creator reviews.
Local and challenger retail: proving you exist
What visibility means: whether the model knows you exist at all, before a recommendation is even on the table. This is big brand bias in action. Incumbents get named by default because there's far more training data and citable coverage about them.
The numbers: a Lightspeed Commerce study of around 460,000 AI responses found ChatGPT and Google's AI tools picked a national chain over a smaller rival up to 94% of the time in head-to-head comparisons. Switching on live web search narrowed the gap but didn't close it, with chains still taking 46 to 58% of recommendations. Writing in Fortune, Lightspeed's CEO noted that large and small retailers each made up roughly 38% of the sources AI cited, yet big chains walked away with 52% of the top recommendations against 20% for smaller businesses.
What moves the needle: for a challenger, the win condition isn't beating the market leader. It's getting mentioned at all. Being cited as a source isn't enough if the model still names someone else first.
B2B and SaaS: winning the comparison
What visibility means: placement inside a comparison answer. Buyers ask for the "best CRM for a 10-person sales team" or "X vs Y", and the model pulls together review sites, G2-style listings and documentation.
The numbers: G2's survey of 1,076 B2B software buyers found that half now start their software research with an AI chatbot. The single most common use? Weighing up vendors' strengths and weaknesses against each other (41%), ahead of basic product research or finding vendors in the first place.
What moves the needle: structured, comparison-ready content. Cultural buzz counts for far less here than clear pricing, feature tables, honest use-case pages and a healthy presence on review platforms.
Regional and local services: surfacing in your area
What visibility means: turning up at all when someone asks a location-based question, like the best physio near them or a family lawyer in their city.
The numbers: BrightLocal's Local Consumer Review Survey 2026 found 45% of consumers used ChatGPT or other AI tools for local business recommendations, up from just 6% the year before. That makes AI the third most popular source for local recommendations. But doing well on Google doesn't carry over automatically. Across more than 200,000 localised searches, BrightLocal found Google Maps mentioned a tracked business in 66% of searches, compared with 32 to 38% across AI platforms.
What moves the needle: local citations, structured business data and consistency. According to SOCi's 2026 Local Visibility Index, as summarised by BrightLocal, only 68% of business contact details on ChatGPT and Perplexity match what's on Google Business Profiles, and fewer than half of the businesses leading Google's local results also appear in AI recommendations.
Same word. Five completely different events.
Remember our Olympic sprinter? Turns out the stadium is hosting a full athletics programme. Sprinters, high jumpers and marathon runners all wear the same kit, but each one is judged on something different.
One blended score will mislead you.
Now, before you paste a single AI Visibility number into next month's board deck, a few warnings:
It hides which game you're playing. A real estate brand tracking visibility with a fashion-style recommendation model is optimising for a moment that barely exists in its category.
It sends your content budget to the wrong place. Press and creator buzz move a recommendation metric. Comparison content moves a consideration-set metric. Consistent local business data moves a geographic one. Get the mechanism wrong and you'll do a lot of GEO work for very little citation gain.
It makes benchmarks meaningless. A 15% mention rate could be a strong result for a challenger fighting incumbent bias and a weak one for a category leader. Without knowing the mechanism, the number tells you almost nothing (and single snapshots are closer to noise than signal anyway).
It turns a useful insight into a vanity metric. Reporting AI Visibility as one line item to a board flattens a valuable distinction, the exact trap engagement rate fell into.
So where does that leave brands? Here are the three takeaways that matter to business:
AI Visibility is real, but Vogue's definition describes one mechanism (product recommendation), not a universal standard.
The same phrase covers at least five mechanisms: recommendation, consideration set, brand existence, comparison placement and geographic surfacing. Your category decides which one you're competing on.
This is the bit most people miss. Brands won't win by chasing one generic score. They'll win by identifying their category's mechanism first, then matching what they publish, structure and monitor to it.
Not sure whether your AI Visibility number is measuring a recommendation, a consideration set or just whether the model knows you exist? Drop decipher. a line. We'll tell you which race you're really running.
Need a reality check on your AEO efforts?
Need a reality check on your AEO efforts?
or simpy…
Until then… Tah-tah, darling!
Until then… Tah-tah, darling!
