What is AI narrative monitoring?
AI narrative monitoring means regularly polling AI engines with a defined prompt set about a brand, capturing and storing the full responses, and analyzing themes, sources, and sentiment over time. It is the diagnostic layer the rest of AI reputation work depends on.
AI narrative monitoring is to AI reputation what media monitoring is to PR. It runs as a repeating cycle: a fixed prompt set polled against the major AI engines on a regular cadence, with every response captured, stored, and analyzed so you can see how the brand moves across the engines over time.
The monitoring cycle
- Define the prompt set. A fixed set of prompts covering the brand, its executives, products, themes, and named peers.
- Poll the engines. Run the prompt set against the eight major AI engines: ChatGPT, Gemini, Copilot, Perplexity, Claude, Grok, Google AI Overviews, and Google AI Mode, on a daily cadence.
- Capture and store. Record the full response from each engine verbatim, so the data can be compared and diffed across runs.
- Extract and classify. Pull out recurring themes, classify sentiment, and identify which sources each engine is citing.
- Track the trajectory. Watch how themes, sentiment, and sources move over time to catch drift early and see which interventions are landing in which engines.
Why it has to run continuously
If this layer is not running continuously, source-level work is guesswork. The team has no way to know which interventions are landing in which engines, or to catch drift early enough to act on it. AIQ is built for this, and most of our advisory work runs on its data.
Last reviewed: 19/05/2026
