How to Fix Negative AI Mentions About Your Brand

AI does not invent most of its opinions about your brand — it reads them. When an answer says your support is slow or your product is overpriced, that line almost always traces back to a specific source. Fix the source, and the answer changes.

Step 1: find the source

For grounded answers (Perplexity, ChatGPT search, AI Overviews), the citations are returned with the answer — the negative is in that list. For answers with no citation, search the exact phrasing of the claim; it usually lives in a Reddit thread, a review, a competitor comparison page, or your own outdated content.

Step 2: classify the source type

The fix depends on where it comes from. A competitor's "alternatives to you" page, a Trustpilot trend, a forum thread, a stale page on your own site, and a pure model hallucination each need a different response. Misdiagnosing the source wastes weeks.

Step 3: apply the right fix

Competitor comparison page? Publish your own, better comparison and earn the keyword. Negative reviews? Run review generation to shift the aggregate the model reads. Your own outdated page? Update it and add FAQ + schema so AI quotes the right facts. A hallucination with no source? Flood authoritative content (your FAQ, Wikipedia, structured data) to override the model's memory.

Step 4: re-check across engines

After a fix, re-run the prompt on every engine over the following weeks. Sources propagate at different speeds; you want to confirm the change actually landed, not assume it did.

The fast path

Kairosy does Steps 1–2 automatically — it traces each negative to its source and labels the type — then hands you a prioritized fix list so you spend your time fixing, not hunting.