Foundations of Decision Intelligence

This unit introduces core concepts that distinguish decision intelligence from data science and business intelligence, emphasizing how people, processes, and technologies interact in real-world decision-making. Students will explore decision theory, data literacy, AI capabilities and limits, uncertainty, and common pitfalls to prepare for building and evaluating decision workflows in subsequent units.

Learning Objectives

• Analyze and compare decision intelligence, business intelligence, and data science to identify the distinct goals, inputs, and outputs of each approach in organizational contexts
• Evaluate the reliability and relevance of data sources, model outputs, and AI recommendations by identifying common pitfalls, biases, and failure modes
• Demonstrate basic decision-theory concepts (including uncertainty, trade-offs, and what-if reasoning) by constructing and interpreting simple decision scenarios and decision trails
• Apply principles for integrating human roles and automation by proposing actionable workflows that assign responsibilities, checkpoints, and validation steps for AI-augmented decisions