AI Use Case Prioritisation Framework
Every organisation starts an AI programme with more ideas than capacity. This framework gives you a structured, defensible way to prioritise which AI use cases to build first - based on business impact, data readiness, technical complexity, and time-to-value. We've used this with clients from Series A startups to Fortune 500 companies to identify the right first AI investment.
What's inside
Section 1: The four scoring dimensions - business impact, data readiness, technical complexity, time-to-value
Section 2: The scoring matrix - how to rate each use case on each dimension
Section 3: Weighting by context - how to adjust weights for your organisation's constraints
Section 4: The prioritisation conversation - how to use the framework in a leadership team discussion
Appendix: Completed examples from three different organisational contexts
What you'll get
Scoring matrix template (available as Excel/Sheets): rate any AI use case across four dimensions
Dimension definitions and scoring rubrics: objective criteria for each score level
Weighting guide: how to adjust dimension weights for different organisational contexts (startup vs enterprise, cost-focused vs growth-focused)
Three completed worked examples from real AI programme scoping sessions
Facilitation guide: how to run a 2-hour use case prioritisation workshop with a leadership team
Who this is for
CTOs and Heads of Product scoping their first enterprise AI programme
Digital transformation leads evaluating AI investment options
Consultants facilitating AI strategy workshops with executive teams
Engineering managers building internal AI roadmaps
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AI Use Case Prioritisation Framework
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