Listening as a Product – Signals, Open-text and Agentic AI
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Run in-house listening with micro-pulses, UX experiments and safe agentic Q&A.
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What do you want to learn about?
This session explores
- In-house operating model: cross-functional team, intake and backlog, success measures tied to decisions and time-to-signal.
- Weekly micro-pulse design: cadence, embedded delivery, UX/nudge experiments, coverage and fatigue monitoring.
- Open-text with AI: when to favour comments over scales; minimal evaluation to avoid hallucinations; red-team for sensitive themes.
- Agentic listening architecture: centralised quality data, access controls, policy-as-code, logs; retaining anchor surfaces during transition.
- Behaviour-of-response telemetry: interpreting who replies, when and to what; adapting cadence, channels and value exchange.
Why this matters
Survey fatigue, fragmented tools and rising expectations for privacy and explainability are colliding with rapid AI adoption. Leaders need faster, safer decisions from employee input while employees behave more self-preservingly, altering participation patterns. Operating listening as a product – with experiments and governed AI – has become a commercial necessity.