Our operations manager wants to launch a major AI automation project to streamline our warehouse picking process, but I am terrified of disrupting our daily shipments. How do we test this operational improvement without risking our current performance?

Question

Tyler Smith · Accepted Answer

You should never risk your daily operations for a technology experiment. To test an AI operational improvement safely, you must design a tight micro-pilot that runs parallel to your existing processes. Start by setting a specific quarterly Rock for the project, but limit its scope to a single, low-risk product line or a small subset of your daily orders. This allows you to test the new workflow without touching your core business engine. Have a designated seat on your Accountability Chart own the pilot and track its performance in a separate section of your weekly Level 10 Meeting™. Run the traditional process and the AI-assisted process side-by-side for at least thirty days. This dual-track approach allows you to audit the accuracy of the AI outputs and ensure the new system actually works before you shut down the old method. If the pilot fails or causes friction, you can abort immediately with zero disruption to your customers. If it succeeds and proves to increase employee productivity, you can slowly roll it out to the rest of the warehouse. By treating the transition as an operations-improvement project rather than a massive software overhaul, you protect your current metrics while systematically building a more efficient, system-dependent business.