AI Use Case Prioritisation Framework
Which AI use case should your organisation fund first?
Rank up to 12 AI use cases across 5 weighted dimensions and produce a defensible Wave 1 shortlist — with a data-feasibility hard gate that disqualifies use cases before they fail in delivery.
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■ Instant download · ■ No macros · ■ Excel 2016+
“Which AI use case do we start with?” is the most expensive unanswered question in a transformation programme.
Most teams pick use cases on executive enthusiasm or technical novelty — not on a structured view of business value, feasibility, and data readiness. The result: Wave 1 is over-ambitious, under-resourced, and fails visibly.
The scoring framework.
Five weighted dimensions. Up to 12 use cases scored simultaneously. A data-feasibility hard gate that disqualifies before it is too late.
- Prioritization Framework
- A structured, weighted method for ranking candidate initiatives by business value, feasibility, and risk — producing a defensible shortlist rather than a workshop debate.
Every tab, explained.
Open the workbook and know exactly where to go and what to enter.
Built for the people who have to defend the number.
Replace workshop-based use case debates with a scored, repeatable instrument that produces a defensible shortlist in one session.
Ensure Wave 1 initiatives have a viable data foundation before delivery teams are committed — using the hard gate to protect programme credibility.
Run a structured use case prioritisation exercise with any client using a weighted, auditable framework that holds up under scrutiny.
Feeds from: a readiness assessment establishes whether you're positioned to invest at all.
View Readiness Assessment →Feeds into: once you have a Wave 1 shortlist, the next decision is what it will realistically cost.
View Estimation Model →Questions buyers ask before ranking their use cases.
What is an AI use case prioritization framework?
A structured, weighted method for ranking candidate AI initiatives by business value, implementation feasibility, data readiness, time to value, and risk — producing a defensible shortlist instead of a workshop debate.
How is this different from a generic prioritization matrix?
Most prioritization matrices score value against effort only. This framework adds a data-feasibility hard gate specific to AI initiatives, so use cases without a viable data foundation are disqualified before delivery teams are committed, not after.
Should this run before or after a readiness assessment?
After. A readiness assessment establishes whether the organization is positioned to invest at all. This framework then ranks which specific use cases to fund first, once that baseline is established.
AI Use Case Prioritisation Framework
Rank up to 12 AI use cases across 5 weighted dimensions and produce a defensible Wave 1 shortlist — with a data-feasibility hard gate that disqualifies use cases before they fail in delivery.