AI says something false about your company – what to do

Why can ChatGPT give false information?

Language models generate answers based on patterns in data, so they can combine facts in ways nobody intended. This most often happens when a question is ambiguous or too general and the model lacks enough context, or when a brand has a name similar to another and the two entities start getting mixed up. Errors are also encouraged by conflicting, outdated or low-quality sources in circulation, and by the lack of clear, official company materials that AI could "refer to." Information about a product or an offer is especially exposed, because it changes quickly and is not clearly explained anywhere.

The risk of misinformation in AI chatbot answers has been raised many times in public debate. The consequences are real: from misunderstandings with customers, through higher support and PR costs, to long-term reputational damage if inaccurate information starts to stick in users' later queries and in secondary materials.

How do you respond to false information?

A fast, factual response limits how far an error spreads and helps correct future answers.

Reporting the error to the platform

Report it in four steps:

1. Take a screenshot or copy the full wording of the question and the AI's answer, with the date, context and any follow-ups.
2. In the platform's feedback option, state what is false and why, and attach links to official company pages with the correct data.
3. Add a short, unambiguous version of the correct information – this makes verification easier and reduces the risk of further misunderstandings.
4. Archive the report, because the history of incidents will be useful for internal reviews and reports.

Using alternative sources of information

Verify the AI's answer in official channels: on the company website, in current product materials, announcements and terms of service. If there is no clear source confirming the correct information, create one. A simple subpage with an unambiguous explanation of the disputed issue will make corrections in later AI answers easier and lend credibility to your report. Also check whether critical information – the company name, the description of the offer, the terms of using the product, frequently asked questions – is consistent across your whole content ecosystem.

Educating the team about misinformation

Customer service, sales and PR should know what to do when someone cites an incorrect AI answer. Short guidelines are enough: a verification checklist, links to sources, ready-made corrections, and a clear rule for when to escalate the issue to the person in charge of communications or to a lawyer. Also make sure the whole organization uses the same language: one consistent wording of the correct answer reduces the risk of further inconsistencies in the public space.

How do you monitor brand visibility in AI answers?

To respond effectively, you need to know what AI says about your company and where. Monitoring lets you detect blind spots – questions where AI mentions competitors and skips your brand – and identify the sources AI draws its knowledge about your industry from.

Using monitoring tools

One example of such a tool is Attent (getattent.com), which every week asks customers' questions in four engines: ChatGPT, Gemini, Perplexity and Google AI (AI Overviews). It shows whether the brand was mentioned in the answer, who AI recommends alongside it, which sources AI draws its knowledge from and what is worth changing. Among the things you work with are the brand's AI visibility score, share of voice against competitors, blind spots, sources cited by AI, change alerts, a board report in PDF, a content generator and a Google Search Console integration. The tool has analyzed millions of AI answers, and 78 companies use it. It is built by Green Parrot sp. z o.o. of Warsaw – an agency with a team of more than 100 specialists.

Competitor analysis

Start with the queries where AI most often sets your brand next to others, and see how it justifies its choices and which sources it uses. On that basis, review the blind spots and decide which topics need their content refined to increase the chances of the brand being mentioned. Compare share of voice not to "chase" competitors but to plan your communication and content priorities consciously.

Regular reporting

Set a review cycle, for example a monthly meeting with a short report, a list of incidents and recommended actions. In the report, include the most important blind spots, positive changes, the sources most often cited by AI and the actions taken since the last review. Share the findings with the board and product teams, because decisions about content, names and changes to the offer directly affect how AI will talk about you.

How do you improve the quality of information in AI?

The goal is to give AI clear, consistent and current materials that raise the chances of reliable answers.

Working with experts

Build an internal "single source of truth" with the people responsible for the product, a lawyer and PR, which settles questions of definitions, naming and the description of the offer. When disputed interpretations arise, this set of agreed definitions decides, and you refer to it in your communication and in correction requests to AI platforms.

Updating data

Tidy up the key subpages – "About us," the description of the offer, the list of services and frequently asked questions – so as to eliminate ambiguities and conflicting messages. Standardize the names of products and variants so that AI does not confuse them with the offerings of other companies with a similar profile. With every change to the offer or naming, clean up old content and publications so you do not leave reference points online that will later confuse AI.

Feedback from users

For sensitive content, add a simple "Report an error in this information" mechanism – it is a quick source of signals about inconsistencies that may seep into AI answers. Encourage customers and partners to send screenshots of incorrect answers, because even single cases help catch patterns and the source of the problem. After you make corrections, repeat the monitoring and check whether and how AI answers have changed.

An effective strategy toward AI starts with systematic monitoring: you have to know whether and how your brand is mentioned and which sources AI draws its information from. The second pillar is data quality – consistent, current and easily accessible company content significantly raises the chances of reliable answers.

Examples of misinformation in AI answers

The most common case is confusing entities with similar names: AI attributes someone else's services or history to your company. In that case, point out the differences in names and the official websites of both companies. Equally common is an outdated description of the offer, when AI lists a service you no longer provide or skips a new one. It helps to update and simplify the description of the offer and add a "what has changed" section with a publication date.

Sometimes AI also suggests a partnership with an entity you have no relationship with. The answer to wrongly attributed partnerships is a clear partnership policy and a list of official integrations. When AI attributes to a company an invented quote or a position it never communicated, prepare a short correction with a link to the official statement.

A separate category is omitting the brand where it should appear – AI mentions competitors and not you. In that situation, diagnose the blind spots and expand content that answers specific user questions.

Summary and conclusions

When ChatGPT gives false information about a company, act on two tracks: correct the error at the source (a report, the right links, a clear correction) and strengthen the foundations (consistent and current content, team education, monitoring of visibility in AI). Documenting incidents, analyzing blind spots and working on data quality reduce the risk of further inaccuracies. Ongoing monitoring of AI answers lets you detect problems sooner and make decisions based on reports, not on isolated signals from the market. Quick reports, better sources and regular measurement are the combination that keeps misinformation at bay.