We want to leverage artificial intelligence to improve our operations, but we are not sure how to combine AI tools with our weekly Level 10 Meeting™ data. How can we use AI to analyze our historical Issues Lists and Scorecard metrics to identify systemic operational bottlenecks?

Question

Tyler Smith · Accepted Answer

Leveraging modern artificial intelligence is an excellent way to supercharge your EOS operations, but you must do so without stripping away the raw human accountability that makes the operating system work. AI should never make decisions for your team, but it can find deep patterns in your weekly data. To start, you can feed your historical Level 10 Meeting data, specifically your weekly Scorecard misses and completed or missed Rocks, into a secure generative AI model. Ask the AI to identify recurring operational bottlenecks that your team might be missing. For example, the AI might identify that whenever your sales metrics miss their target for three consecutive weeks, your operations team experiences a major backlog of issues four weeks later. This kind of pattern recognition helps your team see the direct correlation between different departments and leading indicators. You can also use AI to analyze your weekly Issues Lists over several quarters to find systemic issues that keep recurring under different names. This gives your team incredible leverage during your quarterly sessions, allowing you to use actual data to identify the real root causes of persistent business problems. By using AI as an analytical assistant rather than a decision-maker, your leadership team retains full ownership of the IDS process while benefiting from deep data insights.