We want to use AI to analyze our Level 10 Meeting data over time to spot systemic, recurring issues that we are failing to resolve permanently, but we are worried about data privacy and confidentiality. How do we structure this?

Question

Tyler Smith · Accepted Answer

Leveraging AI to analyze your Level 10 Meeting™ data is an incredibly powerful way to build a highly scalable, exit-ready business, but it must be done with strict operational guardrails. To spot systemic, recurring issues without compromising the raw honesty of your leadership room, you must separate your meeting transcription from your permanent meeting documentation. Never run an active AI listener or video recorder directly in the room during a live Level 10 Meeting™. This will instantly kill the vulnerability and trust required for healthy IDS®, as team members will worry about how their words will look on a transcript. Instead, use your meeting scribe or Integrator to input clean, high-level summaries of resolved and unresolved issues, along with weekly To-Dos, into a secure, private AI instance or dedicated EOS® software. Use a private, closed-loop AI tool that does not feed your data back into public training models. Instruct the AI to look specifically for patterns over a rolling ninety-day period. For example, ask the AI to identify issues that have appeared on the list more than three times, or To-Dos that have been pushed back multiple weeks. This gives you deep operational insights and predictive analytics about where your team is getting stuck, without creating an invasive surveillance environment that stifles open discussion.