Foundations of Decision Intelligence

This unit introduces core concepts of Decision Intelligence (DI), distinguishing DI from data science and business intelligence while emphasizing a decision-first approach. Students will learn to map decision trails, assess AI’s role and limitations, surface uncertainty and pitfalls, and prepare actionable, human-centered decision plans that set up later technical units.

Learning Objectives

• Analyze real-world decision trails to map stakeholders, decision points, information flows, and intended outcomes using the who/what/where/why framework
• Apply foundational decision-theory concepts and what-if reasoning to evaluate trade-offs and quantify uncertainty in simple decision scenarios
• Evaluate the differences between Decision Intelligence, Business Intelligence, and data-first approaches by identifying common pitfalls, failure modes, and sources of machine and human error
• Demonstrate the ability to assess data sources and design a decision-first action plan that specifies organizational roles, AI/automation boundaries, checks for bias and math issues, and measurable actionable outcomes