What should you look for in a reputation management firm’s approach to AI?

What to look for in a firm’s approach to AI has become a central diligence question, because the AI engines are now where much perception forms, and many firms have adopted the vocabulary without the capability. The genuine markers start with multi-model monitoring, since ChatGPT, Gemini, Copilot, Perplexity, Claude, Grok, Google AI Overviews, and Google AI Mode answer the same question differently and a firm needs to see all of them rather than spot-checking one. A sound methodology for influence means shaping the sources the models draw on, including entity signals, authoritative content, and structured data (machine-readable tags that tell search engines what a page is about), rather than claiming to manipulate model outputs directly, which is not possible. Structured reporting characterizes the AI narrative and its movement over time. Integration with the broader reputation work matters too, since AI narrative is downstream of the same entity and content foundations. And ongoing R&D matters because the engines change quickly and a static approach falls behind. We built AIQ to do the monitoring and tie source-influence work to the rest of the program, and we invest continuously as the engines evolve.