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Business Strategy
Anchors every AI decision in business objectives, value pools, and executive ownership.
The executive perspective
Which business outcomes would we accept as evidence that AI is working?
Where is value actually created or lost in our operations today?
Who on the executive team owns each AI initiative and its results?
Scope
- Business objectives and strategic priorities
- Value pools and measurable outcomes
- AI opportunity alignment
- Investment priorities and executive sponsorship
From assessment to action
Assessment criteria
- Each initiative is linked to a named objective and owner
- Value hypotheses are written down before investment
- A single prioritized portfolio exists and is reviewed regularly
Practical interventions
- Value-pool mapping workshop with business leaders
- Portfolio prioritization using value, feasibility, and risk
- Executive sponsorship model with clear decision rights
Risks & measurement
Common failure patterns
- Starting from tools or vendor demos rather than business problems
- A long list of disconnected pilots with no portfolio view
- Sponsorship delegated entirely to IT or innovation teams
Example KPIs
- Share of AI initiatives with a documented value hypothesis
- Time from idea to funded decision
- Realized vs. expected outcome per initiative
Illustrative metric types — targets depend on your baseline.
Connection to other dimensions
Sets the targets that Measurement tracks and decides which Processes are worth redesigning first.