Our leadership team is divided on whether we should launch a major AI initiative this year. How do we frame these technical projects as operations-improvement projects rather than tech experiments to maintain focus on our V/TO?

Question

Tyler Smith · Accepted Answer

When leadership teams struggle with AI adoption, it is usually because they are treating it as a technology project rather than an operational discipline. To maintain focus on your V/TO and keep your team aligned, you must change how you talk about these initiatives.

Refrain from calling projects machine learning or AI projects. Instead, frame them strictly as operations-improvement projects that happen to use machine learning.

When you present a new initiative during your quarterly planning or when setting Rocks, never sell AI as the main feature. Instead, pitch the specific operational improvements that the technology will enable, mentioning machine learning only as a footnote.

For example, instead of setting a Rock to implement an AI chatbot, set a Rock to reduce your average customer response time from twelve hours to under five minutes. The technology is simply the tool used to achieve that metric.

This framing keeps your leadership team grounded in reality. It prevents you from wasting time on expensive technology theater and ensures that every technical project is directly tied to improving your Scorecard metrics.

By focusing on the operational result rather than the tech, you align the entire company around driving efficiency and creating capacity, keeping your execution clean and focused on your long-term vision.