Framework
The Deployment Ladder
Most organisations do not have an AI problem. They have a deployment problem. This is the ladder I use with leadership teams to locate where they actually are — and what the next rung costs.
Curiosity
Teams are experimenting individually. Nothing is measured, nothing is owned.
Exit criteriaA named owner and a written definition of what 'working' means.
Pilot
One workflow, one team, a demo that impresses the board and changes nothing.
Exit criteriaA baseline: current cost, current cycle time, current error rate.
Production
The system runs daily with real data, real users and a real fallback path.
Exit criteriaUptime, cost per task and quality tracked like any other operating line.
Operating Line
AI output is in the P&L. Someone's targets depend on it. It gets reviewed monthly.
Exit criteriaBudget moves from innovation to operations.
Compounding
Each deployment shortens the next one. Data, evals and governance become shared assets.
Exit criteriaDeployment time drops with every cycle instead of resetting.
Assessment
Where are you on the ladder?
Who owns the most active AI initiative in your organisation?
This is a diagnostic preview. The full assessment is included with Signal Pro and the Deployment Sprint.
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Subscribers get the full assessment, templates and new rung notes. If you'd rather work through it directly, advisory engagements start with exactly this exercise.
Advisory engagements