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AI Use Case Prioritization Tool

Run the AI Use Case Prioritization Tool Fullscreen

About This MicroSim

This interactive tool enables students to practice prioritizing AI use cases using the classic value-complexity matrix framework. Use cases are visualized as bubbles in a 2x2 matrix, with bubble size representing estimated investment. Students can explore different industry scenarios and manipulate use case positions to understand how changes affect prioritization.

Iframe Embedding

You can include this MicroSim on your website using the following iframe:

<iframe src="https://dmccreary.github.io/Digital-Transformation-with-AI-Spring-2026/sims/ai-use-case-prioritization/main.html"
        height="652px"
        width="100%"
        scrolling="no">
</iframe>

How to Use

  1. Select a Scenario: Choose from Healthcare, Financial Services, Retail, or Manufacturing
  2. Observe the Matrix: Each bubble represents an AI use case positioned by value and complexity
  3. Click Bubbles: Select a use case to view detailed information
  4. Drag Bubbles: Reposition use cases to explore "what-if" scenarios
  5. Review Rankings: The priority list automatically updates based on positions

The 2x2 Matrix Framework

Quadrant Characteristics Strategy
Quick Wins (High value, Low complexity) Fast ROI, build momentum Implement immediately
Strategic (High value, High complexity) Transformational but risky Plan carefully, phase approach
Low Priority (Low value, Low complexity) Easy but limited impact Consider if resources available
Avoid (Low value, High complexity) Poor investment Deprioritize or eliminate

Visual Elements

  • Bubble Position: X-axis = Business Value, Y-axis = Implementation Complexity
  • Bubble Size: Estimated investment amount (larger = higher investment)
  • Bubble Color: Distinguishes different use cases within a scenario
  • Quadrant Colors: Green (Quick Win), Blue (Strategic), Yellow (Low Priority), Pink (Avoid)

Priority Score Calculation

The tool calculates a priority score for each use case:

Priority Score = (Value × 1.5) - (Complexity × 0.5) + 5

This formula emphasizes high-value, low-complexity initiatives while still giving credit to strategic high-complexity projects.

Learning Objectives

After using this tool, students should be able to:

  • Evaluate (Bloom's L5): Evaluate and prioritize AI opportunities using structured criteria
  • Analyze (Bloom's L4): Analyze the trade-offs between value and complexity
  • Apply (Bloom's L3): Apply prioritization frameworks to real business scenarios

Lesson Plan

Activity 1: Scenario Exploration (10 minutes)

Cycle through all four industry scenarios. For each: - Identify which use cases fall into each quadrant - Note patterns: Which types of AI initiatives tend to be "Quick Wins"? - Compare priority rankings across industries

Activity 2: What-If Analysis (15 minutes)

Select the Healthcare scenario. Then: 1. Drag "Diagnostic Imaging" from Strategic to Quick Wins (reduce complexity) 2. Observe how this changes the priority ranking 3. Discuss: What would need to change for this use case to become easier to implement?

Activity 3: Portfolio Balance (10 minutes)

Analyze the overall portfolio distribution: - How many use cases in each quadrant? - Is the portfolio balanced or concentrated? - What risks exist if all use cases are "Strategic"?

Discussion Questions

  1. Why should organizations pursue "Quick Wins" before "Strategic" initiatives?
  2. What factors might cause a use case to move between quadrants over time?
  3. How would you handle pressure to implement an "Avoid" quadrant initiative?

References

  1. McFarland, K. R. (2017). The Breakthrough Imperative. Crown Business.
  2. Brynjolfsson, E., & McAfee, A. (2017). Machine, Platform, Crowd. W.W. Norton.
  3. Fountaine, T., McCarthy, B., & Saleh, T. (2019). Building the AI-Powered Organization. Harvard Business Review, 97(4).

Self-Assessment Quiz

Test your understanding of AI use case prioritization.

Question 1: What are the two axes used in the AI Use Case Prioritization matrix?

  1. Cost and Time
  2. Business Value and Implementation Complexity
  3. Risk and Reward
  4. Technology and People
Answer

B) Business Value and Implementation Complexity - The matrix plots use cases based on their potential business value (X-axis) and the complexity of implementing them (Y-axis).

Question 2: Which quadrant represents "Quick Wins" in the prioritization matrix?

  1. Low value, Low complexity
  2. Low value, High complexity
  3. High value, Low complexity
  4. High value, High complexity
Answer

C) High value, Low complexity - Quick Wins are initiatives that deliver high business value with relatively low implementation complexity, making them ideal for immediate implementation.

Question 3: What strategy is recommended for use cases in the "Avoid" quadrant?

  1. Implement immediately
  2. Plan carefully with a phased approach
  3. Deprioritize or eliminate from consideration
  4. Consider if resources are available
Answer

C) Deprioritize or eliminate from consideration - The "Avoid" quadrant (low value, high complexity) represents poor investments that should be deprioritized or removed from the portfolio.

Question 4: What does bubble size represent in this visualization?

  1. Number of employees needed
  2. Estimated investment amount
  3. Project duration
  4. Risk level
Answer

B) Estimated investment amount - Larger bubbles indicate use cases requiring higher investment, adding a third dimension to the value-complexity analysis.

Question 5: Why should organizations pursue "Quick Wins" before "Strategic" initiatives?

  1. Quick Wins are more profitable in the long term
  2. Quick Wins build momentum, credibility, and organizational learning
  3. Strategic initiatives are always failures
  4. Quick Wins require no investment
Answer

B) Quick Wins build momentum, credibility, and organizational learning - Starting with Quick Wins demonstrates AI value early, builds organizational capabilities, and creates support for tackling more complex Strategic initiatives later.