The State of AI Transformation
88% of organisations use AI in at least one function. Less than a third are scaling it. The gap isn’t the model, it’s everything around it.
—McKinsey Global Institute, 2025
AI AssessmentThe Pattern
What Separates Programmes That Scale
A named executive owns each workflow, with authority to redesign it.
Workflows rebuilt around AI capability, not layered on top of unchanged processes.
A hub-and-spoke model separates central governance from domain delivery.
KPI baselines documented and owned before deployment begins.
Architecture matched to operating maturity, not imported from case studies.
An AI inventory exists, with risk tiers and validation rules assigned.
Adoption treated as a product launch, with champions and 90-day measurement.
Value realization thresholds agreed before deployment, not after.
Where You Actually Stand
Where Most
Actually Are
Where Most Leaders
Think They Are
Isolated pilots. No real foundation.
A few things working. Nothing consistent between them.
First genuinely enterprise-ready state.
It is embedded in core workflows. Domain teams delivering.
Continuously redesigning work around AI.
Isolated pilots. No real foundation.
Where Most
Actually Are
A few things working. Nothing consistent between them.
Where Most Leaders
Think They Are
First genuinely enterprise-ready state.
It is embedded in core workflows. Domain teams delivering.
Continuously redesigning work around AI.
The gap between where you think you are and where you are, that’s the work.
Find Your LevelHowever Feels Right
Built from NIST, ISO/IEC 42001, McKinsey, AWS, Microsoft, and Google Cloud. Refined around the conditions that actually determine AI scale.
At Your Own Pace
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