Observation: Leverage comes from removing friction, not adding capability

When I look at where leaders try to apply AI, I notice a consistent pattern. Attention goes to novel or visible use cases, while the highest leverage sits in removing friction from work people already do every day.

The interventions that hold tend to share three characteristics.

1. First, they return time before adding capability, simplifying admin-heavy processes and removing repeated manual effort.

2. They tend to be practical rather than ambitious. The moves that succeed are not the most sophisticated, but those that deliver high impact with minimal additional effort.

3. The value shows up first for a specific group. Whether it’s people leaders, frontline managers, or teams buried in coordination work, the value shows up initially as relief rather than performance metrics.

Across all three, the constraint is rarely access to advanced AI. What I see most often is a lack of data readiness and decision clarity.

This shows up operationally in The grunt-work machine (NZ edition).