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October's four-part series on AI strategy addresses a paradox that dominates boardrooms: whilst 92% of companies are increasing AI investment, only 1% have achieved AI maturity. This disconnect reveals a fundamental misconception – that accumulating business cases and pilots somehow constitutes strategy. Through diagnosis, policy, and coherent actions, these articles provide the complete framework for systematic AI transformation.
The journey begins by exposing how business cases create fragmentation rather than transformation, then diagnoses six interconnected concerns that must be governed simultaneously rather than sequentially. The Complete AI Framework provides guiding policy that transforms multi-speed adoption from weakness into leverage, whilst the final piece delivers coherent actions that compound rather than conflict – from Day 1 amnesty through Quarter 4 scaling.
What makes this series essential reading is its progression from problem to solution. Rather than adding to the noise of AI hype or doom, it provides practical mechanisms for orchestrating transformation. The frameworks aren't theoretical – they're drawn from observing what separates the 1% who achieve AI maturity from the 99% accumulating expensive failures.
If your time is limited, I particularly recommend starting with the diagnosis article to understand why traditional governance fails, then moving to the coherent actions piece for immediately implementable steps. The combination provides both the 'why' and the 'how' of strategic AI transformation.
How is your organisation moving beyond project-level thinking to systematic AI strategy, and which governance approaches are proving most effective in orchestrating rather than constraining transformation?
-Mario
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