10% is the model.
90% is execution.

It starts ambitiously at the top

It almost always starts ambitiously at the top: clearly defined opportunities, an approved budget, transformation goals and the language of competitive advantage that gets everyone in the boardroom nodding. Then it has to bridge the gap between ambition and reality and land in the real work.

Fragmented, poor-quality data. Legacy systems that won't release what you need. Compliance and risk. Resistance to change. And the silent killer: nobody truly feels ownership. The strategy doesn't fail with a bang. It simply stops being anyone's responsibility.

The gap nobody budgets for

This is the gap nobody reserves budget for: the distance between ambition and execution. The model was never the limiting factor. The operating model was.

What does survive the drop has a backbone that is often skipped in the boardroom: first the strategy, then the operating model, then redesigning work processes, then integration and data, then adoption and enablement, and only after that does real business value emerge.

Every step is a handover moment where the strategy can run aground. And the two parts that fail most often are workflow redesign and clear ownership. That is exactly why pilots keep growing bigger while, six weeks later, hardly anything has changed.

Not a technology challenge, but an execution challenge

As far as I can see, success with AI is not a technology challenge. It is an execution challenge. And the quality of execution does not improve by itself.

In the video I share the honest story behind my own AI assistant, including the moment it crossed a line, and what that teaches us about why AI succeeds or fails inside organizations.

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