Our leadership team gets distracted by shiny object syndrome whenever someone pitches a new AI experiment. How should we evaluate, frame, and approve these projects on our V/TO so they solve real operational friction instead of becoming tech theater?

Question

Tyler Smith · Accepted Answer

Establish a firm leadership rule: never sell AI inside your company. Stop calling initiatives AI projects or machine learning rollouts. Frame every proposal strictly as an operations improvement project that happens to use software.

If a team member brings an AI tool to the leadership team, ban discussions about features, neural networks, or prompts. Instead, force the proposal through the filter of your Vision/Traction Organizer. Require the sponsor to answer three concrete operational questions:

- What documented bottleneck or low-value administrative task in our Core Processes does this eliminate?
- Which measurable on our weekly Scorecard will this move within ninety days?
- Which seat on our Accountability Chart owns the ongoing maintenance and quality control of the output?

If the project cannot clearly improve gross margin, reduce cycle time, or free up human capacity for high-value client work, kill it immediately. AI without a direct link to an operational metric is theater. When you evaluate projects solely as operational improvements, you eliminate tech hype, protect your capital, and ensure that any automation you fund delivers measurable enterprise value.