The AI Use Case Prioritization Matrix — Template and Guide
by the U2xAI Team | 4 min read | July 20, 2026
Most organizations don't have an AI ideas problem — they have a selection problem. Workshops produce fifty candidate use cases; budgets fund five. The prioritization matrix is the simplest tool that makes that cut defensible.
Plot every candidate on two axes: business value (revenue, cost, risk reduction) and feasibility (data readiness, technical maturity, change effort). The top-right quadrant — high value, high feasibility — is where your first wave lives. Quick wins in the bottom-right build momentum while the big bets in the top-left mature.
Two practical tips. First, score feasibility with the people who own the data, not the people who want the outcome; optimism is the biggest source of portfolio error. Second, re-score quarterly — feasibility moves fast as models improve and data work completes.
Our AI Use Case Discovery & Prioritization Toolkit includes the matrix as an editable slide plus a multi-criteria scoring model in Excel with calibration guidance and portfolio heatmaps.