Value evidence
Assess contribution to a named business outcome and whether baseline, volume and pain are measured.
Free AI use case assessment
AI Use Case Prioritization Matrix
An AI use case prioritization matrix compares candidate workflows through business value, evidence, technical feasibility, data, operating readiness and risk control. This free tool ranks two to five cases while keeping unresolved critical gates visible.
Three decisions, not one opaque score
Separate value, feasibility and permission to proceed
A high-value idea can still be unready or blocked. The matrix preserves these differences so the numerical score cannot hide a critical issue.
Execution feasibility
Review technical capability, representative data, system access and an owner for exceptions and change.
Critical gate
Check compliance, affected people, sensitive data, human control and reversibility before a pilot recommendation.
Interactive prioritization matrix
Compare AI use cases with the same evidence
Score two to five candidate workflows. Value and feasibility stay separate, while an unresolved critical gate prevents a pilot recommendation.
Transparent scoring
The matrix shows where each point comes from
Each criterion uses a 0 to 4 evidence scale. The result supports a portfolio discussion and does not replace stakeholder judgment.
Value
50% of combined score
Business value contributes 60% of the value axis. Evidence strength contributes 40%.
Feasibility
50% of combined score
Technical, data, operating and risk controllability contribute equally to the feasibility axis.
Critical gate
Overrides the score
Unknown requires review. A blocker produces hold, regardless of numerical value or feasibility.
Use the result
Turn ranking into the next smallest responsible action
Pilot candidate
Value and feasibility are both at least 70, and the critical gate is clear. Define a bounded pilot with an acceptance metric.
Discovery or foundation
Close evidence, process, data, integration or ownership gaps before committing to a build.
Gate review or hold
Review unresolved impact and control questions. A critical blocker stops progression until mitigated or redesigned.
Method sources
Built from current public guidance on prioritization and risk
The criteria synthesize primary government and risk guidance into a comparable business review. The final decision remains contextual.
Frequently asked questions
Using the AI use case prioritization matrix
How do you prioritize AI use cases?
Define candidate workflows, score each with the same value and feasibility evidence, review critical risk and compliance gates, then compare the portfolio. A high score should lead to a bounded pilot, not automatic full deployment.
What makes a good first AI use case?
A good first case has a named outcome, measurable baseline, frequent enough work, representative data, controlled system access, an operating owner and failures that can be detected, reviewed and reversed.
Why are value and feasibility separate?
Combining them too early can hide a valuable case that needs foundations or an easy case with little business value. Separate axes make the next action clearer.
Can a critical blocker be offset by a high score?
No. An unresolved compliance, rights, safety, ownership, human control or reversibility blocker must be mitigated or designed out before the case proceeds.
Does this matrix calculate ROI?
No. It ranks relative evidence for candidate use cases. Cost, benefits and accepted output should be modeled separately for the shortlisted pilot.
From shortlist to pilot
Choose one workflow and replace assumptions with evidence
AI consulting maps the current process, validates the shortlist and defines a controlled experiment with ownership, metrics and stop conditions.
See AI consulting services