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 foundational diagnostic discipline that the rest of AI reputation work depends on.
AI narrative monitoring is to AI reputation what media monitoring is to PR: the continuous diagnostic layer that the rest of the work depends on. It runs as a structured, repeating cycle, a fixed prompt set polled against the major AI engines on a regular cadence, with every response captured, stored, and analyzed so the brand’s trajectory across the engines is visible over time.
The monitoring cycle
- Define the prompt set. A fixed set of prompts covering the brand, key 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
Without that diagnostic layer 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. AIQ is built specifically for this discipline, and most of our advisory work runs on top of its data.
Last reviewed: 19/05/2026
