· the problem
Organisations move quickly. Rarely with a framework.
· what gets called "AI strategy"
list of use cases
budget allocated to AI
tools roadmap
initiative catalogue
· what a real strategy decides
where AI creates defensible value
which dependencies are acceptable
which capabilities to internalise
who answers for AI effects
The right AI strategy is not the one that deploys the most tools.
It is the one that correctly decides where AI must be used, controlled, limited or refused.
· our reading
An AI strategy starts with strategic position, not use cases.
AI does not have the same value depending on whether the company seeks to reduce costs, differentiate its offer, improve its decisions, create a new business model, defend a dominant position or catch up.
Only once the position is clear do the technology arbitrations become readable — and defensible before the board.
· the fundamental distinction
A list of AI initiatives is not a strategy. A decision system that says yes, no, not now, not under these conditions, only with these safeguards — that is a strategy.
· the decisions to arbitrate
What the executive committee must resolve.
where does AI create genuinely differentiating value for us?
which capabilities must we own or control?
which capabilities can we delegate without strategic risk?
which vendors are becoming structural?
which data must never be commoditised?
which uses do not justify the risk or cost?
what governance must frame the decisions?
who answers if an AI system produces an erroneous decision?
· what you get
A decision system, not a catalogue.
→ mapping of priority value creation domains
→ identification of capabilities to internalise vs delegate
→ vendor framework: conditions, dependency limits, exit costs
→ list of data to protect as strategic assets
→ build / buy / partner arbitrations with explicit criteria
→ indicators of captured value and preserved control
→ strategic brief defensible before board and shareholders
· d-c-a-r applied to ai strategy
The four dimensions of every strategic AI decision.
D
Dependency
Which capabilities are outsourced? Which decisions depend on a vendor? What is the real exit cost?
C
Control
Which decisions remain mastered? Can you explain, contest, stop? Who can take back control?
A
Advantage
What value stays with the organisation, hard to replicate? Does AI create a defensible advantage or only productivity?
R
Responsibility
Who assumes the effects of AI usage? Is accountability effective or merely declarative?