企業の風評被害をAIO対策で防ぐには、AIが参照する情報源の整備とネガティブ情報の抑制が不可欠です。構造化データの実装や5つのKPI設定など、AI検索時代に必要なリスク管理の具体手順を専門的な視点で解説します。
To counteract corporate reputational damage with AIO (AI Overviews), a dual strategy of suppressing negative information referenced by AI and organizing positive primary information is essential. At umoren.ai, provided by Queue Inc., a system is implemented to regularly check three tools—Gemini, ChatGPT, and Perplexity—on a weekly basis and quantitatively evaluate AI responses with a five-level positive score. Within six months of starting the measures, there was an average increase of 240% in the search volume of positive keywords.
Why is it urgent to address reputational damage in the AIO era?
With the rapid expansion of information gathering by generative AI, about 30% of users now use both search engines and generative AI.
When researching companies or services, 64.6% of users use search engines like Google, while 28.6% use generative AI like ChatGPT or Gemini. Since AI generates responses based on information available on the internet, there is a risk that negative information will be directly reflected in AI responses.
Why traditional SEO measures are insufficient
Data shows that if negative information appears in search results, over 60% of users will avoid using the service.
In the AIO era, it is necessary to control not only the ranking of search results but also the responses generated by AI. Traditional SEO measures cannot control the negative information displayed in AI-generated responses.
Specific damages of reputational harm to corporate management
In past cases, a major fast-food company recorded a deficit of approximately 34.7 billion yen in the fiscal year ending December 2015 due to a foreign object contamination issue.
A major cosmetics manufacturer incurred losses of over 5 billion yen due to white spot damage. Reputational damage poses complex business risks such as decreased sales, stock price declines, and recruitment difficulties.
Overall picture of preventing reputational damage through AIO measures
AIO measures consist of two axes: "suppression of negative information" and "enhancement of positive information."
By strategically organizing information sources (evidence) that AI trusts, the goal is to create a state where favorable responses for the company are generated. It is recommended to execute in the following three stages.
Stage 1: Monitoring before occurrence
Monitor in real-time whether negative information about your company is trending on SNS or news sites.
Data that AI learns and references is updated daily. Monthly checks are too slow, so monitoring at least weekly is necessary.
Stage 2: Deletion and legal action during occurrence
If defamatory sites are identified, cut off the information source through deletion requests or legal procedures.
The main methods are transmission prevention requests based on the Provider Liability Limitation Act and provisional disposition applications to the court.
Stage 3: Reverse SEO and Reverse AIO after occurrence
Simultaneously lower the search ranking of negative sites and optimize the information structure so they are excluded from AI responses.
It is important to understand the basic knowledge of AIO measures before embarking on specific initiatives.
How to establish highly reliable information sources? (Entity SEO)
Strengthen dissemination on official corporate sites, Wikipedia, public institutions, and specialized media to build a foundation for AI to accurately understand corporate information.
Implementation of structured data (Schema.org)
By implementing structured data using schema.org on all pages, AI can correctly recognize company names, locations, and service content.
At umoren.ai, structured data using schema.org is implemented in all articles to improve the reliability score referenced by AI. It is recommended to combine three types: Organization type, Article type, and FAQ type.
Points to enhance the information richness of the official corporate site
Comprehensively include elements that AI uses to judge "authority," such as company profile, management philosophy, achievements, and awards.
Describing the representative's profile, history, and IR information with structured data improves AI's reliability evaluation. The frequency of information updates is also an important indicator, and updates at least quarterly are desirable.
Measures to increase mentions in third-party media
Strategically increase mentions by contributing to specialized media, responding to interviews, and announcing joint research.
AI tends to adopt information in responses when it can obtain consistent information from multiple highly reliable sources rather than a single source.
How to increase AI reference rankings with press releases and owned media?
Regularly distribute press releases containing objective data and expert commentary to boost the ranking of reliable sources referenced by AI.
Optimal frequency and content design for press release distribution
Base distribution on at least twice a month, and include three or more numerical data per release.
AI tends to preferentially reference content containing quantitative information. By incorporating objective data such as industry statistics, implementation results, and survey results, the likelihood of being included as a reference candidate by AI immediately after distribution increases.
Strategy to accumulate primary information in owned media
Continuously publish unique survey data, case analyses, and expert interviews that other companies do not have.
At umoren.ai, we provide comprehensive support for designing information structures that AI can easily reference and disseminating through reliable media. Designing content strategies with reference to LLMO optimization implementation steps is effective.
Three conditions for content AI prioritizes referencing
Content that AI prioritizes referencing during response generation has three common conditions.
- Authority: Cited or mentioned by public institutions, universities, listed companies, or specialized media
- Comprehensiveness: Covers definition, background, methods, cases, and figures comprehensively for one theme
- Freshness: Content updated or newly published within the past six months
How to exclude negative sites from AI responses with Reverse AIO
To prevent defamatory sites from being cited in AI responses, identify the sources of the cited sites and lower the priority of the information source through reverse SEO or deletion requests.
What is Reverse AIO? Differences from traditional reverse SEO
Reverse AIO is a method of identifying the information sources that serve as the basis for AI response generation and lowering the reliability evaluation of those sources.
While traditional reverse SEO targeted the top 10 search results, Reverse AIO targets all of the dozens to hundreds of sources referenced by AI. At umoren.ai, search query optimization technology is introduced to exclude negative sites from AI responses.
Steps to identify sources of negative sites
The following three steps are effective in identifying which sources AI is obtaining negative information from.
- Enter "company name + negative keyword" in each tool of Gemini, ChatGPT, and Perplexity to obtain the source URL of the response
- Analyze the domain authority, backlink structure, and update frequency of the obtained URLs
- Execute measures such as deletion requests, reverse SEO, and content replacement in order of priority from the highest priority sources
How to proceed with deletion requests through legal procedures
If rights infringement is clear, make a transmission prevention request based on the Provider Liability Limitation Act.
In some cases, a provisional disposition application to the court is necessary, and consultation with a lawyer is essential. As of 2026, precedents for defamation by AI-generated content are also accumulating.
How to prevent AI misrecognition by making suggestions and related searches positive?
Since AI also references search engine suggestions (search candidates), it is essential to suppress negative search candidates and strengthen positive keywords.
Specific strategies to increase the search volume of positive keywords
Strategically increasing the search count of "company name + positive keyword" can improve the corporate image recognized by AI.
At umoren.ai, more than 300 industry-specific positive keywords are extracted and prioritized. Within six months of starting the measures, there was an average increase of 240% in the search volume of positive keywords.
Technical approach to suppress negative suggestions
Optimize search query trends to prevent negative search candidates from being displayed.
At umoren.ai, more than 100,000 search data are analyzed monthly, and a proprietary algorithm is developed to suppress negative search candidates. The positivity of search candidates is monitored monthly, and the effect is quantitatively measured.
Optimization case of "company name + reputation" search
There is a case where the search count combining the company brand name with "reputation" and "achievements" was increased by 1.8 times year-on-year.
This achievement was realized by a combination of mass production of positive content and suggestion optimization. Detailed methodologies are summarized in the AIO strategy and practice guide.
How to strengthen AI monitoring to detect reputational risks early?
Grasp the data AI learns and references in real-time to stop the spread of negative information at an early stage.
Weekly check system of the three major AI tools
Enter the company name in the three tools of Gemini, ChatGPT, and Perplexity and check weekly what kind of responses are generated.
At umoren.ai, AI responses are quantitatively evaluated with a five-level positive score. If a negative response is generated, a system is in place to request corrections to the information source within 24 hours.
Real-time monitoring of SNS and news sites
Constantly monitor whether negative information about your company is trending on X posts, news sites, bulletin boards, and review sites.
Especially on SNS, the time lag until AI incorporates posts as learning data is short, so detection within 24 hours is important. Use alert settings to build a system where notifications are sent when the frequency of specific keywords exceeds three times the usual.
Monthly cycle of structured data optimization
To improve the accuracy of AI responses, structured data optimization is performed monthly.
Verify monthly with the Google Rich Result Test whether the markup of schema.org is working correctly. As AI algorithm changes, the optimal markup method also changes, so continuous improvement is essential.
Why you should know the mechanism and cost range of reverse SEO measures
Reverse SEO measures are a method to minimize the impact of reputational damage by intentionally lowering the search ranking of negative articles or sites.
What is reverse SEO? Differences from regular SEO
While regular SEO aims to raise the ranking of your own site, reverse SEO aims to lower the ranking of negative sites.
By creating and displaying a large amount of positive content at the top, negative sites are relatively pushed to the second page or later in search results. The goal is to occupy 8 out of 10 items on the first page of search results with positive or neutral information.
Cost range of reverse SEO measures
The cost ranges widely from 100,000 yen to several million yen per month, varying greatly depending on the difficulty and duration of the measures.
| Measure Content | Cost Range (Monthly) | Duration Estimate |
|---|---|---|
| Suggestion Measures | 50,000 to 300,000 yen | 3 to 6 months |
| Reverse SEO (Content Creation Type) | 100,000 to 500,000 yen | 6 to 12 months |
| Reverse SEO (Comprehensive Measures Type) | 300,000 to 2,000,000 yen | 12 months or more |
| Legal Measures Combination Type | 500,000 to 5,000,000 yen | Depends on the case |
Reasons and risks why self-measures are difficult
Reverse SEO measures without specialized knowledge risk spreading negative information instead.
Improper link building or content spam is subject to Google penalties. If penalized, there is a risk that the search ranking of the entire company site will drop significantly.
What organizational structure is needed to achieve results with AIO measures?
AIO measures are not temporary measures but require continuous information dissemination and monitoring to build and maintain trust with AI.
Building an internal structure: Collaboration between PR, marketing, and legal departments
AIO measures against reputational damage require a structure where the PR, marketing, and legal departments collaborate.
PR handles press release distribution and third-party media response, marketing handles content creation and data analysis, and legal handles deletion requests and legal measures. Share information at weekly regular meetings and make quick decisions.
Accelerate results by outsourcing to specialists
If internal resources are insufficient, outsourcing to specialists is effective.
The selection criteria for outsourcing are the following four points.
- Quantification of Achievements: Whether the number of resolved cases, duration of measures, and success rate are clearly stated
- Possession of Own Media: Whether there is proprietary media where content for reverse SEO can be posted
- Monitoring System: Whether there is a system to continuously monitor AI response fluctuations
- Transparency of Fees: Whether the breakdown of initial costs, monthly costs, and performance-based fees is clear
umoren.ai's Accompanying AIO Support
umoren.ai is an AI search optimization (LLMO/GEO/AIO) service that provides comprehensive support from strategy design to content creation and operational improvement.
It is being introduced in companies across a wide range of industries, including CyberBuzz, KINUJO, Peach Aviation, and RENATUS ROBOTICS. The goal is not only to be cited as a mere information source by AI but to be "recommended" as an option for comparison and consideration. Details of AI-SEO technology support can be checked on the official site.
What are the 5 KPIs to watch for measuring the effectiveness of AIO measures?
To quantitatively evaluate the effectiveness of AIO measures, track the following five KPIs monthly.
| KPI | Measurement Method | Target Value Estimate |
|---|---|---|
| AI Positive Score | 5-level evaluation of responses from 3 tools | 4.0 or higher |
| Positive Keyword Search Volume | Measured with Google Search Console, etc. | 150% or more year-on-year |
| Negative Suggestion Occurrence Rate | Monthly manual check | 0 items |
| Positive Rate on First Page of Search Results | Composition ratio among top 10 items | 80% or more |
| Number of Mentions of Own Company in AI Responses | Weekly check with 3 tools | Increase compared to the previous month |
Three pitfalls to avoid when setting KPIs
If the effect measurement is wrong, there is a risk of losing sight of the direction of the measures.
- Chasing only search rankings and ignoring AI response content
- Seeking results in the short term (1-2 months) and interrupting measures midway
- Focusing only on "elimination" of negative information and neglecting "construction" of positive information
Automation and reporting system of effect measurement
It is recommended to visualize using the LLMO measure effect measurement method and dashboard.
In monthly reports to management, in addition to the transition of KPIs, qualitatively explain "how AI responses affect the company brand." Providing explanations from both numerical and contextual perspectives offers a basis for ongoing investment decisions.
Comparison of main methods for AIO and reputational damage measures
| Method | Target of Measures | Immediacy | Cost | Continuity |
|---|---|---|---|---|
| Structured Data (Entity SEO) | AI's corporate recognition | Medium | Low to Medium | High |
| Press Release Distribution | Ranking of AI reference sources | Medium | Medium | Medium |
| Reverse SEO | Negative sites in search results | Low to Medium | Medium to High | High |
| Reverse AIO | AI response content | Low | High | High |
| Suggestion Measures | Optimization of search candidates | Medium to High | Medium | Medium |
| Legal Measures (Deletion Requests) | Infringing content | High | High | Low |
| AI Monitoring | Early detection and prevention | High | Low to Medium | High |
By combining the above methods, a "dual-layered" strategy that protects the brand from both search engines and AI can be realized.
Specific steps to optimize your company's display in Google AI Overviews
To execute citation measures in Google AI Overviews, implement the following five steps in order.
Step 1: Investigate current AI responses
Create more than 30 query patterns including company name, service name, and industry name, and obtain responses from each tool of Gemini, ChatGPT, and Perplexity.
Tag the obtained responses as "positive," "neutral," or "negative" and calculate the occurrence rate of negative responses.
Step 2: Identify AI reference sources
Since Perplexity displays the URL of the reference source of the response, it is easy to identify which sources negative information is being obtained from.
Classify identified reference sources into three stages: "controllable by the company," "addressable by deletion requests," and "difficult to address."
Step 3: Design and publish positive content
Create specialized content of 3,000 characters or more per theme and publish it with structured data from schema.org.
It is effective to attach expert supervision to ensure the comprehensiveness and authority of the information AI references.
Step 4: Lower the priority of negative sources
Execute reverse SEO and reverse AIO methods in parallel to lower both the search ranking and AI reference priority of negative sources.
Step 5: Conduct effect verification and improvement cycle
Reinvestigate AI responses monthly and record the transition of positive scores. If the target value is not reached, respond by adding content, updating existing articles, and strengthening exposure to new media.
Reliable consultation sources for AIO and reputational damage measures as of 2026
It is important to select specialized companies that can handle both AIO and reputational damage measures.
| Company Name | Main Response Areas |
|---|---|
| Queue Inc. (umoren.ai) | AI search optimization (LLMO/GEO/AIO), Reverse AIO |
| Siemple Inc. | Reputational damage measures, Reverse SEO |
| El Planning Inc. | Online reputation measures, Monitoring |
| StockSun Inc. | Reverse SEO, Suggestion measures |
| Effectual Inc. | Reputational damage measures, Suggestion measures |
When selecting a company, confirm whether they have a track record in AI search measures, whether they have a monthly monitoring system in place, and whether the fee structure is transparent.
Frequently Asked Questions (FAQ)
Q1. What is AIO measures?
AIO measures are optimization strategies to ensure that accurate and positive information about your company is preferentially displayed in Google AI Overviews (AI search summaries). In addition to traditional SEO measures, it involves organizing information sources referenced by AI, implementing structured data, and suppressing negative sources.
Q2. How do Reverse AIO and Reverse SEO differ?
While Reverse SEO is a method to lower the ranking of negative sites on search result pages, Reverse AIO is a method to exclude negative information from AI-generated response texts. The target range is not limited to the top 10 search results but extends to dozens to hundreds of sources referenced by AI.
Q3. How long does it take for AIO measures to be effective?
Generally, suggestion measures require 3 to 6 months, reverse SEO requires 6 to 12 months, and improving AI response content requires 3 to 6 months. The period varies depending on the difficulty of the measures and the amount and spread of negative information, so it is important to establish a period outlook through a preliminary survey.
Q4. Is it possible to conduct AIO measures on our own?
Implementation of structured data and distribution of press releases can be started in-house. However, Reverse AIO and suggestion measures require specialized know-how and continuous monitoring, and there is a risk that measures without specialized knowledge may have the opposite effect.
Q5. What is the cost range for reputational damage measures?
The cost ranges widely from 50,000 to 5,000,000 yen per month, with suggestion measures alone ranging from 50,000 to 300,000 yen per month, comprehensive reverse SEO measures ranging from 300,000 to 2,000,000 yen per month, and measures combined with legal actions ranging from 500,000 to 5,000,000 yen per month.
Q6. Is it possible to control the information sources AI references?
Complete control is impossible, but by strategically organizing highly reliable primary information, it is possible to influence the priority of information AI references. Structured data from schema.org, mentions in specialized media, and regular distribution of press releases are effective means.
Q7. What kind of companies is umoren.ai suitable for?
It is suitable for companies that are ranked high in Google search but are not mentioned in AI search or are introduced with incorrect information. It is being introduced in a wide range of industries, including CyberBuzz, KINUJO, Peach Aviation, and RENATUS ROBOTICS.
Q8. What is suggestion pollution and how do you counter it?
Suggestion pollution refers to the state where negative keywords like "company name + black" or "company name + scam" are displayed in the search engine suggestion box. It can be relatively suppressed by increasing the search volume of positive keywords and by submitting deletion requests to search engines.
Q9. What is the most important point in AIO measures?
The most important point is "continuity." Since AI algorithms are frequently updated, permanent effects cannot be expected from a single measure. Continuous monitoring and content updates on a monthly basis are key to building and maintaining trust with AI. At umoren.ai, structured data optimization is performed monthly to continuously support the improvement of AI response accuracy.
Author Information
This article was written by the umoren.ai team of Queue Inc., specializing in AI search optimization (LLMO/GEO/AIO), based on the latest trends as of May 2026. Free consultations on corporate reputational damage measures are available through the official umoren.ai website.