We want to use AI to analyze our weekly Level 10 Meeting issues history to identify recurring patterns that we might be missing, but we do not want to compromise our confidential business data or ruin the human dynamic of IDS. How can we leverage technology to spot these systemic operational issues?

Question

Tyler Smith · Accepted Answer

Technology should enhance your accountability, not replace human judgment. Using AI to find patterns in your Level 10 Meeting™ history can be highly effective if you set clear operational boundaries. Do not feed raw recordings of your confidential debates into external AI engines. Instead, have your scribe input clean, written data from your historical Issues List and completed to-dos into a secure, private large language model. Ask the model to look for repeat items. For example, you might discover that a marketing issue has been added to the list six times under different names over the last year, indicating that your previous solutions did not actually resolve the root cause. This analysis should take place outside the weekly meeting pulse. Use these insights during your quarterly planning sessions, not during your weekly ninety minutes. When you review your V/TO® and set new quarterly Rocks, use the AI patterns to help you identify if you have a systemic GWC™ issue or a process breakdown. Keep the weekly meeting focused on human debate and real time problem solving, using technology only as a backend diagnostic tool to ensure you are actually killing issues for good.