AI and Data Science Use Case Prioritization

Produces a prioritized portfolio of AI/ML use cases scored on value potential (revenue uplift, cost reduction, risk mitigation) vs. feasibility (data availability, technical complexity, time-to-value). Use a 2x2 opportunity matrix and include build/buy/partner recommendation for each use case.