Our departmental managers keep proposing AI tools as technology experiments, but our leadership team struggles to evaluate their business value. How do we reframe these proposals on our V/TO so they are treated as genuine operational improvements?

Question

Tyler Smith · Accepted Answer

When department leaders pitch AI as a technology initiative, leadership teams get trapped in endless debates about software platforms, algorithms, and technical architecture. This is classic shiny object syndrome. As an owner, you must establish a clear rule: your company does not fund AI projects. You fund operations-improvement projects that happen to use machine learning as a tactical tool.

Strip all technical jargon out of the conversation. When an initiative is brought to your quarterly planning session or evaluated for your V/TO, require the leader to define the problem using operational metrics. They must answer four questions:
- Which seat on the Accountability Chart owns the broken process?
- How many hours or gross margin dollars are currently lost?
- What specific operational bottleneck exists in the documented Core Process?
- What measurable business outcome defines success on the Scorecard?

If someone proposes a Rock titled Implement Generative AI in Customer Support, reject it immediately. Rename the Rock to Reduce Tier 1 Ticket Resolution Time from 24 Hours to 2 Hours. Mention machine learning only as a footnote in the execution plan.

Framing projects this way ensures your Integrator and leadership team focus exclusively on return on investment, process efficiency, and enterprise value rather than technical theater that fails to move your Scorecard numbers.