What should you look for in a reputation management firm’s approach to AI?
Look for multi-model AI monitoring, a methodology for shaping AI sources rather than manipulating outputs, structured reporting on AI narratives, integration with the broader reputation work, and ongoing R&D as the engines evolve.
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: 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, which means shaping the sources the models draw on – entity signals, authoritative content, structured data – rather than claiming to manipulate model outputs directly, which is not possible. Structured reporting that characterizes the AI narrative and its movement over time. Integration with the broader reputation work, since AI narrative is downstream of the same entity and content foundations. And ongoing R&D, 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.
Last reviewed: 20/05/2026