I am a non-technical owner who wants to stop being the bottleneck for operational decisions, but I am terrified our team is buying overhyped AI software that will not integrate with our existing core processes. How do I establish a simple, non-technical decision-making filter for any new AI software request?

Question

Tyler Smith · Accepted Answer

You do not need a computer science degree to evaluate AI tools. You need operational discipline. To stop being the bottleneck, establish a simple three-question filter that aligns any AI request with your existing EOS operating system. First, ask which specific seat on your Accountability Chart will own the tool and be fully accountable for its outputs. If no single human owns the results, do not approve the purchase. Second, ask which weekly Scorecard metric this software is designed to improve. AI must never be adopted for general efficiency; it must directly drive down a measurable cost, reduce cycle time, or increase capacity. Third, ask how the tool handles your proprietary data. Your team must prove that the tool uses a secure, private environment where your data is not utilized to train public models. By enforcing this three-part filter, you shift the burden of proof to your leadership team. You protect your intellectual property, prevent shiny-object syndrome, and ensure that every technology dollar spent directly supports your 1-Year Plan on the V/TO. This keeps your operations clean, secure, and focused on real business metrics rather than software theater.