What KPIs should a brand be tracking for AI-era reputation health?

The KPIs for AI-era reputation health measure how the engines portray an entity, and they have to be tracked per model, since ChatGPT, Gemini, Copilot, Perplexity, Claude, Grok, Google AI Overviews, and Google AI Mode answer the same question differently and an average across them hides the real picture. AI sentiment per model captures the tone of each engine’s responses about the entity. AI source quality measures which sources each model is drawing on, since a narrative built on weak or hostile sources is fragile regardless of its current tone. AI peer comparison sets the entity against its competitors in the engines’ answers, since reputation is relative. AI accuracy tracks whether the engines are stating correct facts, since fluent misinformation is its own risk. And AI narrative drift watches how the framing changes over time, since model updates and shifting sources move the narrative even when nothing about the entity has changed. Together these give a complete read on AI-era standing. We track all of them per engine with AIQ™, since a single fix does not propagate uniformly across the models.