I am a non-technical business owner, and my leadership team is pitching me on three different AI projects that sound like expensive science experiments. How do I evaluate these initiatives and make sure we are funding real operational improvements rather than software theater?

Question

Tyler Smith · Accepted Answer

Stop looking at these as technology projects. Refrain from calling them AI or machine learning projects. Instead, frame them strictly as operations-improvement projects that happen to use machine learning as a footnote. Your job is not to understand the underlying code. Your job is to enforce business logic and protect the P&L.

Start by looking at your EOS Accountability Chart. Ask your team which specific seats are currently buried in low-value, repetitive tasks. Every proposal must tie back to liberating a human to focus on higher-value strategic work or directly improving a Scorecard metric.

Demand a simple cost-to-benefit analysis that ignores the hype. If a proposal claims it will save hours, make them define the exact documented SOP that will be automated. If they cannot point to a clean, step-by-step process that already exists in your company, deny the project. AI cannot optimize chaos.

Finally, never approve a project that requires a massive, upfront development budget. Run a small test first. Use off-the-shelf tools to prove the concept within thirty days. If the team cannot show a measurable reduction in administrative friction during that window, kill the project and reallocate your resources to other Rocks.