How do we track and evaluate our AI workflow implementations during our quarterly EOS session rhythm?

Question

Tyler Smith · Accepted Answer

When we incorporate artificial intelligence and workflow automation into your operating model, we do not treat AI as an experimental science fair project. It must submit to the exact same operational discipline, accountability, and measurable tracking as every other priority in your business.

AI implementations enter the quarterly session cycle in one of two ways: as a quarterly Rock or as a Scorecard Measurable. If your objective is deploying an automated customer triage pipeline or standardizing process documentation using generative tools, that project is assigned a single owner, broken into a clear ninety-day milestone, and tracked weekly in your Level 10 Meeting.

During our quarterly session, we review the Rock with the same rigor applied to revenue goals. Did the automation launch on time? Is the workflow documented in your Core Processes? Did the team actually adopt it, or are employees bypassing the tool to do manual work? If an AI project failed to deliver expected efficiency or faced employee resistance, we add it to the Issues List and run it through IDS.

Furthermore, through the lens of Step by Step Exit disciplines, we evaluate whether your AI automations are actively reducing value gaps and eliminating single-person dependencies. By capturing tribal knowledge and converting manual executive tasks into automated operational workflows, you systematically de-risk the company. If an AI tool does not lower overhead, accelerate delivery, or reduce founder reliance, it gets eliminated from your operational priorities.