Learning objective
Build a user-anchored dependency chain, distinguish visibility from evolution and turn contested positions into testable strategic options.
Why it matters
A strategy can fail even when its architecture is correct: the organisation may custom-build utilities, outsource the differentiator or ignore a dependency moving faster than its plan.
Core concept
Map the current landscape before adding preferred movements. The distance from the user is one dimension; market evolution is another.
Scenario
A bank assumes that owning every part of an AI adviser creates advantage. Yet identity and messaging are utilities, orchestration has multiple products, and understandable explanations remain immature.
Worked decision
Keep explanation design near the user and test it. Compare orchestration products against exit criteria. Use utilities with resilience controls. Do not infer a sourcing answer from x-position alone.
Decision rule
Make a move only when the dependency, position, constraint and disconfirming signal are explicit. A map without evidence is a useful question, not an answer.
Ethical boundary
Do not use a maturity placement to justify hidden workforce displacement, supplier exclusion or extraction of user data. Make affected groups, power and recourse visible.
AI lens
AI can maintain the evidence register and compare versions; humans own component definition, strategic commitments and consequences.
Quick check
A low-visible component is mature and utility-like. What follows?
A. It is unimportant.
B. It must be outsourced.
C. Standard options may exist, but resilience, power and exit still require a decision.
D. It belongs at the end of the project plan.
Answer: C.
Next step
Complete the AI platform strategy case and record one assumption that would move a component on the next map.