How do you measure brand safety in AI search results?

AI brand-safety measurement addresses a risk specific to the AI era: that the engines, synthesizing from imperfect sources, may state things about a brand that are false, inappropriate, or genuinely harmful, and do so with the fluent confidence that makes errors persuasive. The measurement assesses, across the major engines, whether responses about the brand contain misinformation – wrong facts presented as true – inappropriate associations, or dangerous claims, and it tracks each model separately, since ChatGPT, Gemini, Copilot, Perplexity, Claude, Grok, Google AI Overviews, and Google AI Mode behave differently and a problem in one may not appear in another. Tracking over time matters because the engines change, so a brand that is safely represented today may not be after a model update or a shift in sourcing. The value is early detection: catching a harmful AI claim while it is contained, before it spreads or gets repeated, and tracing it to the source so it can be addressed. We measure this across the engines with AIQ™ and tie remediation to the underlying sources the models are drawing on.