AI Reputation Management – when generative AI talks about you, we mind the tone.
ChatGPT, Perplexity and Gemini talk about you – whether you want them to or not. We measure the sentiment in which AI models describe your brand, correct false statements and build the trust signals that shift AI answers in a positive direction.
- Sentiment tracking
- Fact correction
- Crisis response
- Trust-signal building
AI Reputation Management is not online reputation management with a new name. AI models emerge from the consensus of many sources – to change that consensus, you have to work structurally and in several places at once, not contest a single review.
From old narrative to a positive AI answer
We measure the tone in which AI models talk about you, fix the defining sources and build current trust signals that shift the picture to the positive.
A four-phase approach
Issue identification
We test your brand systematically across every model with positive, neutral and critical prompts. The result: a list of the problematic statements.
Source research
Where did the models learn this? Which external sources shape the picture? Outdated studies, old reviews, forum threads?
Source correction
Where possible: correcting the source (e.g. an update on your website, a request to Wikipedia editors, targeted PR content).
Building counter-signals
Current, trustworthy content with clear authorship that overwrites the old narrative.
Three patterns we see often
Outdated information
AI cites a state of affairs from two years ago – product, price or ownership long since changed.
Confusion with another provider
Models mix up your brand with similar-sounding competitors.
An old negative source
A critical source from years ago carries disproportionate weight because current counter-signals are missing.
The key questions, answered briefly
What if ChatGPT says something false about my company?
AI models draw their knowledge from web sources. You correct false statements by setting the underlying signals straight: consistent, accurate information on your own site and on trustworthy third-party sources. We identify the sources and steer against them deliberately.
Can you actively influence how AI portrays you?
Yes – indirectly, but effectively. Through consistent entities, structured facts, author signals and mentions on relevant pages, you can influence how models classify and portray a brand – durably, because it carries over into subsequent training runs.
Which signals steer how AI portrays a brand?
AI models form their brand picture from web sources. These signals can be influenced deliberately:
How long does it take to change an AI portrayal?
With live-connected models like Perplexity, corrected signals often take effect within weeks, because they pull in current sources. Purely training-based answers (parts of ChatGPT) only change with model updates – but once established there, accurate signals are especially durable, because they're carried into subsequent training runs.
Frequently asked questions
Can you have a specific false AI statement deleted?
No – we can't have OpenAI's training data deleted. But we can make sure current sources and live web data show a different picture. Models like Perplexity and Google AI Overviews update from that quickly.
How long does it take to turn around an AI reputation crisis?
With live-web models (Perplexity, AI Overviews), often 4–12 weeks. With purely training-based models (older ChatGPT versions without browsing), only at the next training update – which can't be influenced, so the focus is on counter-signals.
When is AI Reputation Management worth it?
Whenever you operate in a sector where research-driven purchases are common (B2B, premium, advisory-heavy). Also acutely after crises, bad reviews or misinterpretations in the media.
Ready to put this lever to work?
In the free Visibility Check we look together at whether and how this service fits your situation – including a concrete proposal of next steps.
Request a reputation check →