What reporting should stakeholders receive about AI reputation?

Stakeholder reporting on AI reputation has to be built around decisions, not just observations. The components that produce decision-grade reports: a dashboard summary covering the headline metrics (sentiment, share of voice, accuracy concerns) at a level a CEO or board can absorb; peer comparison against the named competitor set; theme trends showing what is gaining or losing weight in the AI narrative; source-quality assessment of what the engines are citing; accuracy concerns highlighting where the engines are stating something incorrect; and the prioritized list of interventions that the data is recommending, with timing and ownership. The reporting that fails this test is purely descriptive – it tells the audience what is happening without telling them what to do. The reporting that works puts the recommendations at the front and supports them with the data.