Strategy

Overview

What an AI strategy is, in the framework's sense

• The framework's stance on AI strategy is that it is short, falsifiable and committal. Most documents that call themselves AI strategies are positioning documents: statements of intent, value-of-AI summaries, governance disclaimers. A working strategy is something tighter. It is a small set of commitments the organisation has made about how it will deploy AI across its work, stateable in a page or two, with the conditions under which it would be revised made explicit.
• The framework names four decisions an AI strategy must commit to. Scope decides which workflows are addressed. Pattern allocation assigns one of the four cognitive patterns to each in-scope workflow. Operational changes name the consequences the chosen pattern demands: workflow redesign, team capability, governance maturation, information plumbing, technical infrastructure. Sequence decides the order and dependencies. Each names a different kind of strategic choice; together they exhaust what an AI strategy can commit to inside the framework's scope.
• Other strategic concerns (business case, budget, accountability owner, success measures) sit outside the framework. What the framework supplies is the minimum the strategist must have decided before pattern allocation can be acted on, and the relationship between each decision and the readiness diagnostic that constrains it. A strategy that names a pattern allocation without committing to the operational changes the pattern demands is one of the framework's recognised antipatterns and the most common shape of AI-strategy theatre.