How to Use This Companion

This document makes Step 3 — Score Use Cases Across Five Dimensions and Step 4 — Assign Governance Tier of the ai-use-case-intake playbook executable.

Use it only after a use case has passed the pre-screen (i.e., it is not clearly out of scope, technically infeasible, or misframed as AI problems). For each qualifying idea:

1. 01Apply the weighted scoring model across the Five Dimensions using the rubrics below.
2. 02Calculate the total weighted score.
3. 03Assign a governance tier based on the risk factors and score.
4. 04Capture the result in the use case backlog so it can flow into governance review and resource allocation.

The Weighted Scoring Model

Overview

Each use case is scored from 1–5 on the Five Dimensions. Each dimension has a specific weight reflecting its importance in your portfolio.

The Five Dimensions and Weights

Total Weighted Score is computed as:

Total Score =
  (Strategic Alignment × 0.25) +
  (Business Value & Impact × 0.25) +
  (Data Readiness × 0.20) +
  (Technical Feasibility × 0.15) +
  (Risk & Governance Load × 0.15)

Scores range from 1.0 to 5.0.

Dimension Rubrics (1–5 Anchors)

Use these concrete anchors when scoring. When in doubt, choose the lower score and capture your rationale.

1. Strategic Alignment (Weight 0.25)

Question: How directly does this use case advance our AI strategy and key business priorities?

• 5 – Direct, primary driver
• Explicitly named in AI strategy or annual plan.
• Clearly accelerates 1–2 top business objectives (e.g., margin, growth, risk reduction).
• Strong executive sponsorship already in place.
• 4 – Strong, near-core alignment
• Not explicitly named, but clearly supports strategic initiatives or KPIs.
• Has a committed senior champion (e.g., VP level).
• Fits cleanly within AI guiding principles.
• 3 – Indirect but supportive
• Improves efficiency or quality in a supporting function.
• No explicit strategic mention but logically contributes to objectives.
• Sponsor at manager/director level with reasonable commitment.
• 2 – Peripheral or local benefit
• Benefits a single team or niche process with limited enterprise impact.
• Hard to connect to stated strategic outcomes.
• No senior sponsor; interest is exploratory.
• 1 – Misaligned or distracting
• Conflicts with AI strategy or guiding principles (e.g., shadow AI, data residency conflicts).
• Primarily "shiny object" with unclear business linkage.
• Leadership likely to question why this is being pursued.