Part II — AI Strategy and Value Creation
This part asks a harder set of questions than Part I. Once leaders understand what AI is, how the external environment is shifting, and where exposure begins, the next issue is practical judgment: where is AI actually worth using, under what conditions, and in what order?
This section answers four practical leadership questions:
- where does AI create real value for the organisation?
- which capabilities should be built, bought, or developed through partners?
- what data conditions make those bets reliable and defensible?
- how should investment be sequenced so that pilots become durable capability?
The argument of this section is deliberate. Value comes first because weak use cases do not become strong through better tooling. Sourcing and data then determine whether promising use cases can be delivered with acceptable cost, control, and trust. The roadmap chapter brings those choices together into one sequence for investment, adoption, and scale.
Leaders should read these chapters as one strategic arc rather than as separate topics. A weak value thesis makes sourcing irrelevant. Poor data quality weakens even a promising use case. A good pilot without a roadmap remains local activity instead of becoming an organisational capability.
The practical shift in Part II is from AI enthusiasm to AI selectivity. The task is no longer to find uses everywhere. It is to decide where AI deserves redesign, ownership, and continued operating effort.
Chapters
- Where AI Creates Organizational Value
- Build, Buy, or Partner
- Data as a Strategic Asset
- Designing an AI Roadmap
Next: Where AI Creates Organizational Value →