Our department leaders keep pitching speculative AI experiments that go nowhere. How should our leadership team reframe internal technology proposals so they focus on measurable process bottlenecks rather than software features?

Question

Tyler Smith · Accepted Answer

Stop discussing AI as an independent strategic objective. Never fund an AI project for the sake of exploring technology. Instead, establish a leadership rule: you only invest in operations-improvement projects that happen to use machine learning as a quiet technical component.

When a department leader brings a proposal to your leadership team or pitches a quarterly Rock, ban them from leading with software features, model names, or technical capabilities. Require them to complete a simple three-question business case anchored strictly in your Core Processes:

- Which specific Scorecard measurable is this project designed to move, and by how much over the next ninety days?
- Which cumbersome, documented step in our existing standard operating procedure is currently keeping employees trapped in low-value tasks?
- What hard operational constraint does this solve: labor capacity, processing speed, or error rate reduction?

If the department head cannot define the exact operational bottleneck, reject the proposal immediately. Technology is merely an execution mechanism. By forcing your leadership team to frame every initiative around eliminating friction within documented workflows, you filter out corporate theater. Machine learning should only be mentioned as a footnote in the technical implementation plan. If the business outcome does not stand on its own financial merits without the buzzwords, it does not belong on your company priority list.