Scoping AI Use Cases and Risks

This unit guides learners through identifying, prioritizing, and validating enterprise AI use cases while assessing associated technical, organizational, and ethical risks. It emphasizes partnership models, global R&D considerations, data privacy and access constraints, and criteria for selecting appropriate models and controls — building on foundational concepts and preparing students to design and implement governed AI solutions.

Learning Objectives

• Analyze and prioritize enterprise AI use cases by assessing business value, technical feasibility, required data assets, and potential operational impacts
• Evaluate internal and external partnership and governance models to support cross-functional and global AI R&D, including stakeholder roles and collaboration workflows
• Apply risk assessment techniques to identify black swan vulnerabilities, data privacy exposures, and inequities in data access, and propose mitigation and compliance strategies
• Choose and justify appropriate model types and deployment controls by comparing model capabilities, data dependencies, human-in-the-loop needs, and operational constraints