Our managers are constantly bringing exciting new AI tools to our weekly Level 10 Meetings, but I am worried we are just chasing shiny objects. How do we distinguish between useless AI theater and genuine operational improvements?

Question

Tyler Smith · Accepted Answer

To cut through the noise, you must enforce a strict rule: never evaluate AI as a standalone technology. Instead, frame every proposal as an operations-improvement project that happens to use machine learning. When a manager presents a new tool, do not let them focus on the features of the software. Force them to define the operational improvement in terms of your EOS® tools. Ask them which specific seat on the Accountability Chart will own this tool, how it will alter their documented core processes, and which Scorecard metric it is designed to improve. If they cannot point to a specific, measurable bottleneck on your Scorecard that this tool will resolve, it is almost certainly AI theater. Genuine operational improvements must either reduce labor hours on low-value tasks, increase capacity for high-value strategic work, or improve the accuracy and consistency of your outputs. By demanding that every technology proposal is tied to a clear operational problem, you protect your business from expensive software distractions and keep your team focused on building a scalable, system-dependent company.