We want to use AI to scale our operations, but we are worried about introducing tech we don't understand. How do you help us systematically test and integrate new AI workflows into our existing EOS framework?

Question

Tyler Smith · Accepted Answer

Introducing new technology like artificial intelligence can easily trigger organizational resistance and operational chaos if it is not handled systematically. To prevent this, we treat AI implementation like any other major initiative by filtering it directly through your quarterly Rocks.

We do not try to overhaul your entire business at once. Instead, we select one specific, high-friction workflow and create an active experimentation Rock around it. This is where Kolb's learning cycle is highly valuable. We start with a concrete experience, test a specific AI tool in a controlled environment, observe the results, and then refine the process.

By restricting AI initiatives to defined quarterly Rocks, we protect your team's weekly focus. The rest of the business continues running on your established Level 10 Meeting™ cadence. This structure ensures that your daily operational metrics remain stable while you build a more efficient, tech-forward organization. We treat AI as an operational accelerator, not a strategic pivot. This disciplined approach allows you to modernize your operations and prepare for a clean exit without losing your grip on the business.