The New PR Crisis: When AI Gets Your Company Wrong
For years, communications teams knew where a reputation problem was likely to surface. It could be a critical newspaper article, an angry customer on social media, a damaging Google search result or an unfavourable online review.
Now consider a different situation. A potential customer asks ChatGPT about your company and receives outdated information. An investor searches for your leadership team through an AI assistant and is given the name of a CEO who left two years ago. A prospective employee asks what your company is known for and receives an incomplete picture of its achievements.
Or someone asks an AI platform to recommend leading companies in your industry. Your competitors appear, but your brand is missing.
These scenarios highlight an emerging challenge in AI reputation management: how do organisations ensure that AI-powered platforms have access to accurate, credible and current information about their business?
The concern is not simply that artificial intelligence might generate incorrect answers. It is that those answers may influence how customers, investors, employees and other stakeholders perceive a company.
For public relations professionals, this introduces a new dimension to corporate reputation management.
The AI Reputation Problem Companies May Never See
Traditional reputation challenges usually leave a visible trail. A negative news article can be identified, social media conversations can be monitored and search rankings can be tracked.
AI-generated conversations are different because many interactions happen privately between users and AI platforms.
A procurement executive might ask, “Should I consider Company X for this project?” A potential employee may ask, “Is this a good company to work for?” An investor might request a summary of a company’s leadership, performance or recent developments.
The company may never know that these conversations took place, yet the information presented could influence a real decision.
This creates a challenge for communications teams. They cannot monitor every AI-generated conversation or control how each platform responds. However, they can regularly review how their organisation is represented and improve the quality of publicly available information.
That is where AI reputation management becomes relevant.
Why AI Gets Company Information Wrong
An incorrect AI-generated answer does not always involve a completely fabricated fact. Sometimes the information is simply outdated, incomplete or presented without sufficient context.
Imagine a business that has transformed over the past five years. It has expanded internationally, entered new product categories, invested in manufacturing and appointed new leadership. However, much of the information available online still describes the organisation as it existed several years earlier.
An AI platform may reproduce that older description, overlook recent developments or combine information from different periods.
AI systems can also generate inaccurate answers even when reliable information exists. Their responses depend on the model, available sources, retrieval methods and how the question is framed.
For communications teams, this raises an important question:
Have we made enough accurate, credible and current information publicly available for people to understand what our company has become?
Sometimes an AI reputation problem reflects a wider corporate information problem. Improving the information available online is therefore an important starting point, even though it cannot guarantee accurate AI responses.
AI Reputation Management vs Traditional Online Reputation Management
Traditional online reputation management and AI reputation management share a common objective: helping audiences access reliable information about a business. However, the way information is discovered and presented can differ.
| Comparison | Traditional online reputation | AI-generated brand reputation |
|---|---|---|
| Where information appears | Search results, news websites, review platforms and social media | AI assistants and AI-powered search experiences |
| How audiences discover it | Through links, search queries, articles and reviews | Through conversational questions, summaries and recommendations |
| Common risks | Negative reviews, outdated pages, inaccurate articles | Incorrect summaries, outdated leadership information, missing context and misleading recommendations |
| Monitoring approach | Media monitoring, search tracking and social listening | Regular AI reputation audits across selected platforms and prompts |
| Corrective approach | Update owned content, address inaccurate information and engage relevant sources | Improve authoritative source information, correct inaccuracies and use available platform feedback mechanisms |
| Main limitation | Organisations cannot control independent publishers | Organisations cannot control or guarantee AI-generated answers |
The two approaches should complement each other. A company with accurate corporate information, credible media coverage and consistent communication is better positioned to support both traditional online discovery and AI-assisted research.
How to Conduct an AI Reputation Audit for Your Company
One of the most practical steps communications teams can take is to conduct a structured AI reputation audit.
The objective is to understand how different AI platforms describe the organisation, identify recurring inaccuracies and examine whether important business developments are being represented accurately.
Start by asking ChatGPT and other major AI platforms a consistent set of questions.
Questions to Ask About Your Company
- What does [Company Name] do?
- What is [Company Name] known for?
- Who is the current CEO of [Company Name]?
- What are the company’s most important recent developments?
- What products or services does the company offer?
- What makes the company different from its competitors?
- What publicly available evidence supports the company’s credibility?
- Which companies are recognised in [Industry or Category]?
Repeat relevant questions for the CEO, senior leadership team, products and major business divisions.
Do not expect identical answers across platforms. AI-generated responses can vary depending on the platform, prompt wording, available information and timing.
Instead, look for recurring patterns. Is the company described accurately? Are recent developments missing? Is the leadership information current? Are competitors represented more comprehensively? Does the platform associate the business with the industries and areas of expertise it wants to be known for?
Where available, examine the sources cited by the AI platform and record the date, platform and exact prompt used. This creates a useful baseline for future reviews.
Most importantly, ask yourself: If someone knew nothing about our organisation, would these answers give them an accurate understanding of who we are today?
Follow the Sources Before Trying to Correct AI
When an AI platform presents incorrect company information, the first response should be to investigate the underlying sources.
An outdated corporate biography may still be available online. A former executive may remain listed as CEO on an old website. The company’s own About Us page may not reflect recent developments, or different online profiles may contain conflicting information.
Start by reviewing the information your organisation controls, including its website, leadership profiles, corporate announcements and official social media accounts.
Where inaccuracies appear on third-party websites, contact the relevant publisher or platform to request a factual correction where appropriate.
If an AI service provides a mechanism to report inaccurate responses, use that process as well. However, correcting a webpage or submitting feedback does not guarantee that an AI platform will immediately change its answers.
The objective should be to improve the reliability and consistency of information at its source.
How Press Release Distribution Supports AI Reputation Management
Press releases have traditionally helped organisations communicate important business developments to journalists, publications and other stakeholders.
In an AI-driven information environment, they can also contribute to a more complete and current public record of the company.
A well-written press release provides structured information about an announcement, including what happened, when it happened, who was involved and why it matters. It can identify executives, establish dates and include approved quotations and supporting facts.
When distributed to relevant media and online information platforms, a meaningful announcement can become part of the publicly discoverable information surrounding the organisation.
Consider a company that makes several important announcements during a year, including a new CEO appointment, an overseas expansion, a manufacturing investment, a strategic partnership and a sustainability initiative.
Communicating these developments consistently can help create a clearer digital chronology of how the company is evolving.
This information may be useful to customers, investors, journalists, prospective employees and other stakeholders researching the business. It may also be encountered by search engines and AI systems, depending on how those systems access and use information.
However, press release distribution cannot guarantee that a company will be mentioned, cited or recommended in an AI-generated answer.
The priority should remain the quality and relevance of the announcement. A few meaningful, well-supported corporate updates are more valuable than publishing large volumes of repetitive or insignificant content.
Why Credible Media Coverage Still Matters in the AI Era
The growing use of AI should not encourage organisations to replace independent journalism with large quantities of promotional content.
Credible media reporting remains important because it can provide independent context, scrutiny and perspectives that corporate communication alone cannot offer.
There is a difference between a company describing itself as an industry leader and an independent journalist examining its achievements, interviewing its executives and evaluating its claims.
For PR teams, this reinforces the importance of developing newsworthy stories, sharing original information and making knowledgeable spokespersons available to the media.
Research findings, meaningful business developments, expert commentary and relevant industry insights can give journalists stronger reasons to engage with a company.
These activities help build a more credible public information footprint. They may also contribute to how a company is discovered and understood online, although no individual media placement guarantees inclusion in AI-generated responses.
In an environment where AI can produce large volumes of content, credible information and independent reporting remain valuable.
Executive Profiling and Thought Leadership in AI Search
Corporate reputation is often connected to the visibility and credibility of company leadership.
When people research a business, they may also ask AI platforms about its founders, CEO, senior executives or recognised industry experts.
If leadership information is outdated or difficult to find, AI-generated responses may provide an incomplete picture.
Communications teams can address this by maintaining accurate executive biographies, communicating leadership appointments and highlighting meaningful professional achievements.
Executive interviews, authored articles, conference participation and expert commentary can also help establish the subjects on which company leaders have relevant experience.
However, thought leadership should contribute useful perspectives rather than simply repeat promotional messages.
For example, a logistics executive discussing practical challenges in sustainable transportation may provide more value than a generic statement about the company being committed to innovation.
The goal is to build identifiable expertise supported by credible information.
Don’t Try to Manipulate AI Recommendations
As interest in AI search visibility grows, businesses may encounter services promising guaranteed rankings or complete control over what ChatGPT and other AI platforms say about their brand.
Such claims should be treated cautiously.
AI-generated answers are influenced by multiple factors, and organisations cannot reliably guarantee how a particular platform will describe or recommend them.
A more sustainable approach involves maintaining accurate corporate information, publishing original research, communicating meaningful developments, building credible media visibility and developing recognised expertise.
It is also important to avoid publishing repetitive content solely to influence AI-generated answers. Large quantities of low-value material can make it harder for audiences to identify genuinely useful information.
The objective of AI reputation management should not be to manipulate a response. It should be to make reliable information about the organisation easier to find, verify and understand.
How Often Should Companies Review Their AI Reputation?
AI reputation monitoring should become part of a company’s broader communications review process.
A quarterly audit can provide a practical starting point for many organisations. Additional reviews may be useful after significant developments, including leadership changes, acquisitions, major investments, rebranding, product launches or reputational crises.
Communications teams should maintain a record of recurring inaccuracies, missing information, relevant sources and corrective actions.
Over time, this can help identify whether public information has improved and whether selected AI platforms are representing the company more accurately.
The results should be treated as observations rather than definitive rankings. AI responses can change, and improvements in one platform or prompt may not appear consistently across others.
The Future of Corporate Reputation Management
For decades, PR professionals have helped organisations manage how they are represented in the media and understood by important audiences.
AI-powered discovery adds another layer to that responsibility.
Communications teams must now consider not only what journalists, customers and stakeholders are saying about the company, but also what information AI platforms may present when people ask questions about it.
This does not require abandoning traditional PR practices. It makes accurate corporate communication, credible media relations, meaningful announcements and consistent information management even more important.
The emerging PR challenge is not simply that AI might get your company wrong.
The bigger challenge is discovering that the public information surrounding your company is too outdated, incomplete or inconsistent to represent it accurately.
A strong AI reputation management strategy begins with making sure the world has reliable information about who your organisation is, what it does and how it is evolving.
Frequently Asked Questions
What is an AI reputation audit?
An AI reputation audit is a structured review of how AI platforms describe a company, its leadership, products, reputation and areas of expertise. It helps identify outdated information, inaccuracies, missing developments and differences between platforms.
How can companies improve their AI reputation?
Companies can improve the quality of their public information by keeping corporate websites current, maintaining accurate leadership profiles, communicating meaningful business developments, building credible media visibility and correcting inaccurate source information. These steps can support AI discoverability but do not guarantee specific responses.
Can press release distribution help with AI reputation management?
Professional press release distribution can help make accurate corporate announcements available across relevant media and online information platforms. This may strengthen a company’s public information footprint, but it does not guarantee that an AI system will retrieve, cite or recommend the company.
Does media coverage matter for AI search visibility?
Credible media coverage contributes to the publicly available information about a company and can provide independent context. Depending on the platform and how information is accessed, such coverage may be relevant to AI-assisted discovery. However, no individual article guarantees visibility in AI-generated answers.
Can businesses control what ChatGPT says about them?
Businesses cannot directly control or guarantee ChatGPT’s responses. They can maintain accurate information on their own platforms, address inaccuracies in third-party sources and use available feedback mechanisms to report incorrect answers.
How often should companies conduct an AI reputation audit?
Quarterly reviews are a practical starting point. Additional audits may be useful after major leadership changes, acquisitions, rebranding, corporate announcements or reputation-related developments.
What is the difference between AI reputation management and Generative Engine Optimization (GEO)?
AI reputation management focuses on how accurately and credibly an organisation is represented in AI-generated information. Generative Engine Optimization, or GEO, generally focuses on improving the discoverability and usefulness of content in AI-powered search and answer experiences. The two areas overlap, particularly in their emphasis on clear, accurate and credible information.
