When someone asks ChatGPT, Gemini, Perplexity or Google about a company, the response they receive can directly influence their perception of that brand.
They may discover it for the first time, compare it with competitors, associate it with certain attributes or dismiss it before visiting its website.
But where does that information come from?
The answer is more complex than simply “the Internet”. Artificial intelligence systems can combine knowledge acquired during training, results retrieved in real time, structured data and content from different digital sources.
That is why artificial intelligence does not create a company’s reputation from scratch: it interprets it based on the signals available to it.
The new question for brands
It is no longer enough to know what appears on Google when someone searches for the company’s name.
It is also necessary to ask:
Which sources are influencing what artificial intelligence says about our brand?
Understanding this ecosystem is one of the first steps towards improving AI visibility and building a recognisable presence across the new answer engines.
Where does artificial intelligence get its information from?
Not all models or search experiences work in the same way.
A model may respond using knowledge acquired during its training. However, when search, grounding or browsing features are available, it may also consult recent information from the web and use it to generate a response.
ChatGPT Search, for example, can search for current information and display links to the sources used. Perplexity builds responses by synthesising information from different pages and includes numbered citations. In Google’s case, experiences such as AI Overviews and AI Mode rely on its search, indexing and quality systems.
Sources that may help shape the perception of a brand include:
- The company’s official website.
- Product and service pages.
- Press articles and digital media outlets.
- Specialist publications and blogs.
- Technical documentation and help centres.
- Studies, reports and original data.
- Business directories and corporate profiles.
- Reviews and public opinions.
- Forums and specialist communities.
- Interviews, podcasts and audiovisual content.
- Knowledge bases and institutional sources.
- Properly maintained social profiles.
The key idea
A brand is more likely to be understood correctly when the information available about it is: clear + accessible + consistent + verifiable + up to dateThe official website remains at the heart of digital identity
Although AI systems can consult multiple references, the official website remains the space where a company has the greatest control over its identity.
It is where the company can explain clearly:
- What it does.
- Which products or services it offers.
- Who it is aimed at.
- Which markets or sectors it operates in.
- Which problems it solves.
- What sets it apart from other alternatives.
- Which experience and results it can demonstrate.
- How to contact the company or engage its services.
A simple example
Vague message: We help companies transform their future through innovative solutions. More useful message: We analyse how a brand appears in ChatGPT, Gemini, Perplexity and other generative engines to identify mentions, competitors, sources and opportunities for improvement. The second explanation makes it possible to identify quickly:- The company’s activity.
- The type of customer.
- The platforms analysed.
- The service offered.
- The outcome the user can achieve.
Do not confuse training with real-time search
One of the most common mistakes is assuming that every AI response is generated by searching the Internet at that exact moment.
This is not always the case.
It is important to distinguish between two scenarios:
1. Responses based on the model’s knowledge
The system responds using patterns and knowledge acquired during training. In this case, a recent change to a company’s website may not appear immediately in the response.2. Responses based on information retrieval
The system performs a search, consults documents or retrieves information from external sources before generating the response. In these experiences, freshness, indexation, page relevance and the ease with which information can be extracted become especially important. Important Publishing a page does not mean that every model will know about it, consult it or cite it. The brand needs to build a sufficiently robust information ecosystem so that different systems can find, interpret and verify it.Digital authority does not depend solely on what you say about yourself
A company may claim on its website that it is a leader, expert or benchmark in a market. However, these statements carry more weight when there is external evidence to support them.
Search and answer systems may find information about a brand in:
- Specialist media outlets.
- Industry publications.
- Professional associations.
- Interviews with company representatives.
- Studies in which the company has participated.
- Events and conferences.
- Customer case studies.
- Verifiable reviews.
- Third-party comparisons.
- Independent reports.
Specialist content adds more value than a collection of generic articles
For years, many SEO strategies have relied on publishing a large volume of content around keywords.
In generative environments, producing more pages does not necessarily guarantee greater visibility.
Google continues to recommend creating useful, original, people-first content and states that fundamental SEO best practices remain relevant to its generative search experiences. It also emphasises the importance of providing information with genuine value, a clear technical structure and content that is not interchangeable with that of any other website.
Formats that can help demonstrate expertise include:
- Detailed guides.
- Transparent comparisons.
- Case studies.
- Original research.
- Original data.
- Step-by-step methodologies.
- Specific frequently asked questions.
- Product documentation.
- Specialist glossaries.
- Trend analysis.
- Articles written by identifiable professionals.
- Well-supported expert opinions.
Good content should not simply repeat definitions that already appear on hundreds of pages. It should offer something worth retrieving, summarising or citing.
Before publishing, it is worth asking:
- Does it genuinely answer a specific question?
- Does it provide first-hand experience, data or examples?
- Does it explain who created or reviewed the content?
- Does it include a publication or update date?
- Can it be understood without prior knowledge of the company?
- Does it contain claims that can be substantiated?
- Is it better organised than the content already available?
Consistency across channels helps define the brand entity
A company does not exist digitally only within its own domain.
Artificial intelligence may find information about it on LinkedIn, in the media, directories, author profiles, business databases, event pages, review platforms and third-party publications.
When each channel presents different information, it creates noise.
For example:
These contradictions make it harder for a system to determine which information is accurate and up to date.
To reduce this ambiguity, it is advisable to standardise:
- Trading name and legal company name.
- Description of the business activity.
- Products and services.
- Locations.
- Contact details.
- Key personnel and spokespeople.
- Sectors served.
- Logos and visual identity.
- Core messages.
- Links between official profiles.
Freshness matters, but updating content is not simply about changing a date
When a query depends on the current context, systems with web access may look for recent information.
This makes it necessary to review pages such as the following regularly:
- Services.
- Pricing and plans.
- Leadership teams.
- Statistics.
- Comparisons.
- Industry studies.
- Product documentation.
- Legislation and regulations.
- Lists of tools.
- Frequently asked questions.
- Replacing outdated data.
- Removing tools that no longer exist.
- Adding new features.
- Reviewing screenshots.
- Fixing broken links.
- Including recent examples.
- Updating the conclusions.
- Adding the review date.
- Explaining which sections have changed.
Primary sources can become a key differentiating asset
Pages that provide original information are more likely to become a reference for other publications.
A primary source may be:
- An original study.
- A survey.
- A dataset.
- A recurring index.
- A methodology.
- An experiment.
- A benchmark.
- An original interview.
- A documented customer case study.
- An analysis based on anonymised internal information.
- The most frequently mentioned brands in a sector.
- The sources most often cited by each platform.
- Monthly changes in competitors’ visibility.
- The most common positive and negative attributes.
- The differences between ChatGPT, Gemini and Perplexity.
Reviews, forums and communities also form part of the narrative
Brands do not have complete control over the information that exists about them.
Customer experiences, professional conversations and public opinions can influence the attributes associated with a company.
These spaces may contain signals related to:
- Product quality.
- Customer service.
- Ease of use.
- Value for money.
- Reliability.
- Common problems.
- Use cases.
- Recommended alternatives.
- Advantages and limitations.
How to identify which sources are influencing your brand
This is one of the main challenges in the new generative environment.
Traditional analytics tools make it possible to see which pages receive visits, which keywords generate impressions and which domains link to a website. However, they do not always reveal which sources an AI system uses to build a specific response.
To analyse a brand’s situation, it is useful to examine four dimensions:
1. Presence
- Does the brand appear in the responses?
- How frequently?
- On which platforms?
- For which types of queries?
2. Competitive position
- Which competitors appear?
- Which ones are recommended first?
- Which companies dominate the comparisons?
- How is AI Share of Voice evolving?
3. Perception
- Which attributes are associated with the brand?
- Is the description accurate?
- Are services that are no longer offered still mentioned?
- Do errors or outdated information appear?
- Is the sentiment positive, neutral or negative?
4. Sources
- Which domains are cited?
- Which media outlets influence the responses?
- Is the official website used?
- Which third-party pages appear repeatedly?
- Which sources benefit competitors?
What a brand can do to improve its sources
There is no button that allows brands to control what models say, but it is possible to improve the signals available to them.
Priority actions
- Clarify the value proposition
- Create specific pages
- Strengthen the semantic structure
- Demonstrate expertise
- Correct inconsistencies
- Gain external validation
- Update strategic content
- Measure regularly
Mistakes that reduce a brand’s visibility and understanding
Some common problems include:
- Overly abstract corporate descriptions.
- Different services grouped together on a single page.
- A lack of information about who is behind the content.
- Publications without a date or author.
- Outdated data presented as current.
- Duplicate or contradictory pages.
- Name changes without a clear transition.
- Abandoned social media profiles.
- Case studies without specific results.
- Content created solely to include keywords.
- Important information hidden in images or documents that are difficult to crawl.
- Exclusive reliance on the corporate website.
- A lack of relevant external mentions.
Discover how AI sees your brand with AIBrandPulse360
Knowing that a brand appears on Google no longer provides a complete picture of its digital presence.
Marketing, communications and reputation teams need to understand how the company is presented when a user asks questions directly to artificial intelligence engines.
AIBrandpulse360 makes it possible to analyse a brand’s presence in AI-generated responses and study the factors that influence that visibility.
The platform helps identify:
- Whether the brand appears or not.
- Which competitors are mentioned.
- What position it occupies in the responses.
- Which attributes are associated with it.
- Which sources are used.
- How its presence changes over time.
- Which queries offer growth opportunities.
The future of SEO also involves managing AI sources
SEO has not disappeared. Indexing, website architecture, links, content quality and authority all remain relevant.
What is changing is the way users receive information.
Instead of reviewing ten results, a person may receive directly:
- An explanation.
- A list of recommended companies.
- A comparison.
- A market overview.
- A personalised response.
- A conclusion built from different sources.
- Is identified correctly.
- Appears in the right queries.
- Is associated with relevant attributes.
- Is supported by reliable sources.
- Has up-to-date information available.
- Is included in comparisons and recommendations.
- Maintains a consistent narrative across its entire digital ecosystem.
Jul 16, 2026 
