Our leadership team wants to start an AI project this quarter, but I worry we are chasing technology for its own sake. How should we evaluate and frame these initiatives so they produce actual operational ROI?

Question

Tyler Smith · Accepted Answer

Never run an AI project. The moment you label an internal initiative as a machine learning or AI project, you invite technology theater, scope creep, and vendor bloat. Frame every single initiative strictly as an operations-improvement project that happens to use software to solve a quantified bottleneck.

Start by looking at your EOS Scorecard and your Accountability Chart, not software directories. Identify where your gross margins are slipping, where administrative cycle times are choking capacity, or where high-cost employees are trapped executing low-value mechanical tasks.

When leadership members propose a quarterly Rock around technology, force them to answer three operational questions:

- What specific manual step in our Core Process are we eliminating or accelerating?
- How many human hours will this recapture each week, and exactly what high-value work will those hours be redirected toward?
- How will we measure the financial return in our P&L within ninety days of completion?

If the sponsor answers by discussing algorithms, generative features, or digital transformation, kill the project. If they answer by demonstrating that an automated intake parser will save twenty project coordinator hours weekly and cut billing cycle time by five days, approve the Rock.

Treat AI as invisible infrastructure, exactly like cloud storage or database indexing. The technology is just a footnote. The only thing that belongs on your V/TO is measurable operational performance.