[Original Research] Will Your Brand Be 'Recalled' or 'Ignored' by AI?
Key facts
- [Original Research] Will Your Brand Be 'Recalled' or 'Ignored' by AI?
- EXIDEA Inc. conducted a large-scale study on how often Google's AI Overview (AIO) generates responses containing brand names for non-branded searches. Analyzing 17,693 queries, the study found that 57.7% of AIO responses to non-branded searches included specific brand names. Particularly in 'comparison-type' searches, an average of 6.6 brands were presented as candidates. These findings suggest that, in addition to traditional SEO, 'being recalled by AI' is becoming a new competitive axis for brand recognition.
- Source: PR Times
- Date: May 27, 2026
Direct answer
EXIDEA Inc. conducted a large-scale study on how often Google's AI Overview (AIO) generates responses containing brand names for non-branded searches. Analyzing 17,693 queries, the study found that 57.7% of AIO responses to non-branded searches included specific brand names. Particularly in 'comparison-type' searches, an average of 6.6 brands were presented as candidates. These findings suggest that, in addition to traditional SEO, 'being recalled by AI' is becoming a new competitive axis for brand recognition.
- Citation
- [Original Research] Will Your Brand Be 'Recalled' or 'Ignored' by AI? (May 27, 2026), PR Times
- Source
- PR Times
- Date
- May 27, 2026
EXIDEA Inc. conducted a large-scale study on how often Google's AI Overview (AIO) generates responses containing brand names for non-branded searches. Analyzing 17,693 queries, the study found that 57.7% of AIO responses to non-branded searches included specific brand names. Particularly in 'comparison-type' searches, an average of 6.6 brands were presented as candidates. These findings suggest that, in addition to traditional SEO, 'being recalled by AI' is becoming a new competitive axis for brand recognition.
📋 Article Processing Timeline
- 📰 Published: May 27, 2026 at 10:00
- 🔍 Collected: May 31, 2026 at 22:58 (108h 58m after Published)
- 🤖 AI Analyzed: June 2, 2026 at 09:05 (34h 7m after Collected)
In the field of SEO and brand management, where professionals are considering how to adapt to AI Overview (AIO), the following sentiments are often heard regarding their company's exposure to AI:
"If it's a non-branded search, it's acceptable if our site doesn't appear."
"Isn't AI Overview just for providing general, dictionary-like information?"
"As long as users come to our site through branded searches, we don't need to be recognized by AI."
EXIDEA Inc. (Headquarters: Chuo-ku, Tokyo; CEO: Takuma Ogawa) has investigated the extent to which Google Search's AIO generates responses containing brand names for searches where users do not specify a brand. The study covered 17,693 queries and approximately 30,000 brands.
This release shares four key facts that will be useful for SEO and brand managers as they consider their brand's recognition in the AIO era.
Key Findings of This Study
Whether AIO is displayed is more strongly influenced by 'how the question is asked' than by the industry.
AIO tends to be displayed more easily for searches seeking a clear answer, such as 'What is XX?'.
For AIO strategy, it is crucial to prioritize based on the 'query type' rather than treating all keywords uniformly.
Survey Overview
Item
Details
Survey Target
Japanese queries on Google Search that displayed AI Overview and did not include brand, company, or product names (non-branded queries).
Number of Analyzed Queries
17,693
Number of Analyzed Blocks
288,177 (paragraph units within AIO responses)
Number of Detected Brands
29,950 brands (total of 644,678 mentions)
Objective Variable
5-axis classification by LLM (Search Intent / Query Type / Industry / Brand Presence / YMYL Judgment)
Brand Extraction
Automatic extraction of brand, company, product, and service names from AIO response text by LLM.
Statistical Test
Chi-squared test p≈0 for all industry, search intent, and query type categories. Kruskal-Wallis test for unique brand count difference H=922.2, p=8.58e-189.
Data Acquisition Period
February - March 2026
Survey Conductor
EXIDEA Inc.
① Even in Non-Branded Searches, Being an AI Comparison Candidate Becomes a Competitive Axis
Even when users searched without including any brand names, 57.7% of AIO response blocks contained specific brand, product, or service names. An average of 4.5 brands were mentioned per query.
On a per-query basis, only 18.8% of queries had no brands appearing in the AIO, while the remaining 81.2% presented at least one brand. Furthermore, in 51.9% of queries, brand names were included in over 60% of the AI response blocks.
Brand Recall Level
Condition
Query Count
Percentage
High
Brands in >60% of blocks
9,182
51.9%
Medium
Brands in 30-60% of blocks
3,509
19.8%
Low
Brands in 1-30% of blocks
1,684
9.5%
None
Zero brand appearance
3,318
18.8%
AI is evolving from a tool that 'guides users to a specified brand' to one that 'recommends candidate brands on its own, even if not specified.' Relying solely on branded searches as a traffic source may cause businesses to overlook the new competitive axis of whether they are recalled by AI in non-branded searches.
② Prioritize Checking if You Appear as a Candidate in Comparison Searches
The tendency for brand mentions varies greatly depending on the query type. The most significant was in 'Comparison-type' queries, where users search with the premise of 'choosing from multiple options.'
Query Type
Brand Mention Rate
Avg. Unique Brands
Comparison (e.g., XX vs YY, XX difference)
75.9%
6.6
List
61.0%
5.7
How-to
56.4%
4.1
FAQ
52.0%
3.3
Definition (e.g., What is XX)
39.3%
2.7
Reference: Other
56.4%
4.2
In comparison-type queries, three-quarters of AIO responses included brands, with an average of 6.6 brands presented per response. There is a 36.6 percentage point difference in mention rate between comparison and definition types. Among the five clearly classifiable types, AI shows a tendency to actively name brands for 'choosing' searches.
From another perspective, AIO responses to comparison-type queries are akin to an AI-generated 'catalog.' Whether a brand is included as a candidate during comparison is the dividing line for being recalled by AI. Note that 'Other' is a mixed category for queries not clearly classified elsewhere and is treated as a reference value.
③ The Closer the Search is to Purchase, the More Brands AI Names
Looking at search intent, as the user's action stage moves from 'Information Gathering' to 'Comparison' and 'Purchase/Application,' the appearance of brands in AIO responses tends to increase.
Search Intent
Description
Brand Mention Rate
Avg. Unique Brands
Navigational
Reaching a specific site
73.0%
4.7
Transactional
Purchase/Application
68.3%
5.2
Commercial
Comparison
64.9%
5.5
Informational
Information Gathering
44.7%
3.0
Compared to Informational (44.7%), Commercial (comparison) is 64.9%, and Transactional (purchase/application) is 68.3%. There was a difference of over 20 percentage points between information gathering and purchase consideration.
For searches closer to purchase, the AI has already listed candidate brands before the user clicks. If your company is not a candidate in the comparison phase, you may be eliminated from the options before even getting site traffic.
④ Identify Search Conditions Where AI is Likely to Mention Brands for Each Industry
By industry, the difference between industries where AI is likely to recall brands and those where it is not reached up to 1.9 times. There is a 33.5 percentage point gap between Travel & Tourism (71.2%) and Education & Learning (37.7%).
Industry
Brand Mention Rate
Avg. Unique Brands
Analyzed Queries
Travel & Tourism
71.2%
5.4
195
Lifestyle
66.4%
5.3
1,272
Beauty & Fashion
66.1%
5.3
643
Food & Gourmet
65.5%
5.7
240
Finance & Insurance
63.9%
4.8
3,738
IT & Technology
63.1%
5.0
4,420
Housing & Renovation
57.4%
4.6
653
Marketing
55.3%
4.7
1,848
Health & Medical
47.8%
3.6
650
Real Estate
42.7%
3.2
570
Legal & Professional Services
42.0%
2.9
1,211
HR & Career
39.7%
3.2
936
Education & Learning
37.7%
3.5
592
In industries where product/service comparison is common (Travel, Lifestyle, Beauty, Food), AI tends to list candidates more easily. In industries where specialized consultation or individual service is the norm (Legal, HR, Education), AI is less likely to name specific brands. Note that for Travel & Tourism (n=195) and Food & Gourmet (n=240), the sample sizes are smaller, so the figures should be taken as indicative.
Cross-analysis of industry by search intent and query type also revealed hotspots where brand mentions are concentrated. Please use the heatmaps below to check 'under which search conditions AI is likely to list brands' for your industry.
When we compiled the top brands mentioned most frequently in AIO responses by industry, we found that 'mass-market, high-recognition brands' dominated almost every category. It is believed that AI references top-ranking sites in search results, meaning that securing a top search ranking remains a prerequisite for being recalled in the AIO era.
Industry
Top 1-3 Brands (Company names withheld)
Finance & Insurance
Dominated by 2 major consumer finance companies and 1 major credit card company (all with >2,600 mentions)
IT & Technology
Dominated by 3 mobile communication/wireless internet service companies
Beauty & Fashion
1 bridal jewelry company and 2 overseas high-brand jewelry companies
Food & Gourmet
Dominated by 3 frozen food delivery service companies
HR & Career
Dominated by 3 HR SaaS vendors
Education & Learning
Dominated by 3 programming school/online course service companies
Four Points for Managers to Check Immediately
Based on this study, here are four priorities for considering your brand's recognition in the AIO era:
1. Check if your brand appears as a candidate in non-branded searches.
Check if your company appears in AIO responses for non-branded searches like '[category name] recommendation,' '[service] comparison,' or 'XX vs YY.'
2. Prioritize checking comparison/recommendation searches.
AI tends to list brands in comparison/recommendation searches. First, you should see how your company and competitors are treated in searches where users are looking for options.
3. Find searches where only competitors appear.
Searches where competitors appear in AIO responses but your company does not are areas that should be prioritized for improvement. Look not just at 'whether you appear in AIO,' but 'whether you are included among the candidate brands.'
4. Pursue top search rankings and AI candidate inclusion together.
AIO strategy is not a replacement for traditional SEO. It is necessary to achieve top search rankings and then ensure you are picked up as a candidate by AI.
EmmaTools Supports SEO Operations in the AI Search Era
This study has shown that in the AIO era, 'how your brand is recalled by AI in non-branded searches' will be a new dividing line for gaining recognition.
EmmaTools is an SEO writing tool that supports the creation, rewriting, and improvement of SEO articles by leveraging search result data like that from this study. We assist with the necessary measures for SEO in the AI era, such as designing content structures that are easily cited by AI, organizing competitive positioning, and prioritizing keywords.
Characteristics of the Research Methodology
This study is characterized by its quantitative analysis of brand appearance trends through large-scale parsing of actual Japanese response blocks generated by Google AI Overview, rather than relying on the subjective views of SEO managers or case studies. It allows for an objective understanding of 'which industries and which searches AI currently names brands for.'
Differentiation Points
Details
Primary Data
Direct analysis of 288,177 Japanese response blocks generated by Google AI Overview, not from general SEO tool APIs.
Query Classification
Automatic 5-axis classification of each search query using LLM (Search Intent / Query Type / Industry / Brand Presence / YMYL Judgment).
Brand Extraction
Automatic extraction of brand, company, product, and service names from AIO response text by LLM. Detected 29,950 brands and 644,678 total mentions.
Definition of 'Non-branded Query'
Queries that do not contain specific company, brand, or product names (e.g., 'credit card recommendation,' 'water server comparison'). Determined by LLM.
Statistical Significance Verification
Chi-squared test p≈0 for all industry, search intent, and query type categories. Kruskal-Wallis test for unique brand count difference H=922.2, p=8.58e-189.
Handling of Reference Category
'Other' in query types is a mixed category and excluded from rankings, treated as a reference.
Japan Market Focus
Targets only Japanese search results, not global data centered on the English-speaking world.
Note
This study is based on a snapshot of Google search results (acquired Feb-Mar 2026), and AI responses may change over time. The extraction of brand/company/product/service names is by automated LLM classification and may contain some errors or omissions. Industry and search intent classifications are also automated by LLM and have certain accuracy limitations.
Some cells in the industry-specific and cross-analysis (e.g., Travel & Tourism x Navigational) have small sample sizes (n<30) and should be viewed as indicative. This analysis aggregates brand appearances within AIO blocks.
"If it's a non-branded search, it's acceptable if our site doesn't appear."
"Isn't AI Overview just for providing general, dictionary-like information?"
"As long as users come to our site through branded searches, we don't need to be recognized by AI."
EXIDEA Inc. (Headquarters: Chuo-ku, Tokyo; CEO: Takuma Ogawa) has investigated the extent to which Google Search's AIO generates responses containing brand names for searches where users do not specify a brand. The study covered 17,693 queries and approximately 30,000 brands.
This release shares four key facts that will be useful for SEO and brand managers as they consider their brand's recognition in the AIO era.
Key Findings of This Study
Whether AIO is displayed is more strongly influenced by 'how the question is asked' than by the industry.
AIO tends to be displayed more easily for searches seeking a clear answer, such as 'What is XX?'.
For AIO strategy, it is crucial to prioritize based on the 'query type' rather than treating all keywords uniformly.
Survey Overview
Item
Details
Survey Target
Japanese queries on Google Search that displayed AI Overview and did not include brand, company, or product names (non-branded queries).
Number of Analyzed Queries
17,693
Number of Analyzed Blocks
288,177 (paragraph units within AIO responses)
Number of Detected Brands
29,950 brands (total of 644,678 mentions)
Objective Variable
5-axis classification by LLM (Search Intent / Query Type / Industry / Brand Presence / YMYL Judgment)
Brand Extraction
Automatic extraction of brand, company, product, and service names from AIO response text by LLM.
Statistical Test
Chi-squared test p≈0 for all industry, search intent, and query type categories. Kruskal-Wallis test for unique brand count difference H=922.2, p=8.58e-189.
Data Acquisition Period
February - March 2026
Survey Conductor
EXIDEA Inc.
① Even in Non-Branded Searches, Being an AI Comparison Candidate Becomes a Competitive Axis
Even when users searched without including any brand names, 57.7% of AIO response blocks contained specific brand, product, or service names. An average of 4.5 brands were mentioned per query.
On a per-query basis, only 18.8% of queries had no brands appearing in the AIO, while the remaining 81.2% presented at least one brand. Furthermore, in 51.9% of queries, brand names were included in over 60% of the AI response blocks.
Brand Recall Level
Condition
Query Count
Percentage
High
Brands in >60% of blocks
9,182
51.9%
Medium
Brands in 30-60% of blocks
3,509
19.8%
Low
Brands in 1-30% of blocks
1,684
9.5%
None
Zero brand appearance
3,318
18.8%
AI is evolving from a tool that 'guides users to a specified brand' to one that 'recommends candidate brands on its own, even if not specified.' Relying solely on branded searches as a traffic source may cause businesses to overlook the new competitive axis of whether they are recalled by AI in non-branded searches.
② Prioritize Checking if You Appear as a Candidate in Comparison Searches
The tendency for brand mentions varies greatly depending on the query type. The most significant was in 'Comparison-type' queries, where users search with the premise of 'choosing from multiple options.'
Query Type
Brand Mention Rate
Avg. Unique Brands
Comparison (e.g., XX vs YY, XX difference)
75.9%
6.6
List
61.0%
5.7
How-to
56.4%
4.1
FAQ
52.0%
3.3
Definition (e.g., What is XX)
39.3%
2.7
Reference: Other
56.4%
4.2
In comparison-type queries, three-quarters of AIO responses included brands, with an average of 6.6 brands presented per response. There is a 36.6 percentage point difference in mention rate between comparison and definition types. Among the five clearly classifiable types, AI shows a tendency to actively name brands for 'choosing' searches.
From another perspective, AIO responses to comparison-type queries are akin to an AI-generated 'catalog.' Whether a brand is included as a candidate during comparison is the dividing line for being recalled by AI. Note that 'Other' is a mixed category for queries not clearly classified elsewhere and is treated as a reference value.
③ The Closer the Search is to Purchase, the More Brands AI Names
Looking at search intent, as the user's action stage moves from 'Information Gathering' to 'Comparison' and 'Purchase/Application,' the appearance of brands in AIO responses tends to increase.
Search Intent
Description
Brand Mention Rate
Avg. Unique Brands
Navigational
Reaching a specific site
73.0%
4.7
Transactional
Purchase/Application
68.3%
5.2
Commercial
Comparison
64.9%
5.5
Informational
Information Gathering
44.7%
3.0
Compared to Informational (44.7%), Commercial (comparison) is 64.9%, and Transactional (purchase/application) is 68.3%. There was a difference of over 20 percentage points between information gathering and purchase consideration.
For searches closer to purchase, the AI has already listed candidate brands before the user clicks. If your company is not a candidate in the comparison phase, you may be eliminated from the options before even getting site traffic.
④ Identify Search Conditions Where AI is Likely to Mention Brands for Each Industry
By industry, the difference between industries where AI is likely to recall brands and those where it is not reached up to 1.9 times. There is a 33.5 percentage point gap between Travel & Tourism (71.2%) and Education & Learning (37.7%).
Industry
Brand Mention Rate
Avg. Unique Brands
Analyzed Queries
Travel & Tourism
71.2%
5.4
195
Lifestyle
66.4%
5.3
1,272
Beauty & Fashion
66.1%
5.3
643
Food & Gourmet
65.5%
5.7
240
Finance & Insurance
63.9%
4.8
3,738
IT & Technology
63.1%
5.0
4,420
Housing & Renovation
57.4%
4.6
653
Marketing
55.3%
4.7
1,848
Health & Medical
47.8%
3.6
650
Real Estate
42.7%
3.2
570
Legal & Professional Services
42.0%
2.9
1,211
HR & Career
39.7%
3.2
936
Education & Learning
37.7%
3.5
592
In industries where product/service comparison is common (Travel, Lifestyle, Beauty, Food), AI tends to list candidates more easily. In industries where specialized consultation or individual service is the norm (Legal, HR, Education), AI is less likely to name specific brands. Note that for Travel & Tourism (n=195) and Food & Gourmet (n=240), the sample sizes are smaller, so the figures should be taken as indicative.
Cross-analysis of industry by search intent and query type also revealed hotspots where brand mentions are concentrated. Please use the heatmaps below to check 'under which search conditions AI is likely to list brands' for your industry.
When we compiled the top brands mentioned most frequently in AIO responses by industry, we found that 'mass-market, high-recognition brands' dominated almost every category. It is believed that AI references top-ranking sites in search results, meaning that securing a top search ranking remains a prerequisite for being recalled in the AIO era.
Industry
Top 1-3 Brands (Company names withheld)
Finance & Insurance
Dominated by 2 major consumer finance companies and 1 major credit card company (all with >2,600 mentions)
IT & Technology
Dominated by 3 mobile communication/wireless internet service companies
Beauty & Fashion
1 bridal jewelry company and 2 overseas high-brand jewelry companies
Food & Gourmet
Dominated by 3 frozen food delivery service companies
HR & Career
Dominated by 3 HR SaaS vendors
Education & Learning
Dominated by 3 programming school/online course service companies
Four Points for Managers to Check Immediately
Based on this study, here are four priorities for considering your brand's recognition in the AIO era:
1. Check if your brand appears as a candidate in non-branded searches.
Check if your company appears in AIO responses for non-branded searches like '[category name] recommendation,' '[service] comparison,' or 'XX vs YY.'
2. Prioritize checking comparison/recommendation searches.
AI tends to list brands in comparison/recommendation searches. First, you should see how your company and competitors are treated in searches where users are looking for options.
3. Find searches where only competitors appear.
Searches where competitors appear in AIO responses but your company does not are areas that should be prioritized for improvement. Look not just at 'whether you appear in AIO,' but 'whether you are included among the candidate brands.'
4. Pursue top search rankings and AI candidate inclusion together.
AIO strategy is not a replacement for traditional SEO. It is necessary to achieve top search rankings and then ensure you are picked up as a candidate by AI.
EmmaTools Supports SEO Operations in the AI Search Era
This study has shown that in the AIO era, 'how your brand is recalled by AI in non-branded searches' will be a new dividing line for gaining recognition.
EmmaTools is an SEO writing tool that supports the creation, rewriting, and improvement of SEO articles by leveraging search result data like that from this study. We assist with the necessary measures for SEO in the AI era, such as designing content structures that are easily cited by AI, organizing competitive positioning, and prioritizing keywords.
Characteristics of the Research Methodology
This study is characterized by its quantitative analysis of brand appearance trends through large-scale parsing of actual Japanese response blocks generated by Google AI Overview, rather than relying on the subjective views of SEO managers or case studies. It allows for an objective understanding of 'which industries and which searches AI currently names brands for.'
Differentiation Points
Details
Primary Data
Direct analysis of 288,177 Japanese response blocks generated by Google AI Overview, not from general SEO tool APIs.
Query Classification
Automatic 5-axis classification of each search query using LLM (Search Intent / Query Type / Industry / Brand Presence / YMYL Judgment).
Brand Extraction
Automatic extraction of brand, company, product, and service names from AIO response text by LLM. Detected 29,950 brands and 644,678 total mentions.
Definition of 'Non-branded Query'
Queries that do not contain specific company, brand, or product names (e.g., 'credit card recommendation,' 'water server comparison'). Determined by LLM.
Statistical Significance Verification
Chi-squared test p≈0 for all industry, search intent, and query type categories. Kruskal-Wallis test for unique brand count difference H=922.2, p=8.58e-189.
Handling of Reference Category
'Other' in query types is a mixed category and excluded from rankings, treated as a reference.
Japan Market Focus
Targets only Japanese search results, not global data centered on the English-speaking world.
Note
This study is based on a snapshot of Google search results (acquired Feb-Mar 2026), and AI responses may change over time. The extraction of brand/company/product/service names is by automated LLM classification and may contain some errors or omissions. Industry and search intent classifications are also automated by LLM and have certain accuracy limitations.
Some cells in the industry-specific and cross-analysis (e.g., Travel & Tourism x Navigational) have small sample sizes (n<30) and should be viewed as indicative. This analysis aggregates brand appearances within AIO blocks.
FAQ
How often does Google's AI Overview display brand names in non-branded searches?
According to a study by the Japanese company EXIDEA, even in search queries that do not include a brand name, 57.7% of AI Overview responses contained specific brand names.
In the Japanese search market, what types of searches are more likely for AI to recommend brands?
The tendency for AI to mention brand names is strongest in 'comparison-type' searches that include keywords like 'comparison' or 'difference'. In such cases, an average of 6.6 brands are presented in a single response.
What does this AI search trend mean for digital marketing of companies in Japan?
It means that in addition to traditional SEO measures, getting AI to 'recall' and present one's brand as a candidate will become a new competitive arena. Exposure during the comparison and consideration phase is particularly important.
Is there a difference in how often AI mentions brands depending on the industry?
Yes, there is. According to the survey, in the Japanese market, the 'Travel & Tourism' industry was most likely to be mentioned (71.2%), while the 'Education & Learning' industry was the least likely (37.7%).
In the AI era, what should brand managers in Japan check immediately?
The top priority is to check whether their brand is included as a candidate in AI responses for non-branded searches like '[category name] + recommendation' or '[service] + comparison', and how competing brands are being treated.