Foundations of Decision Intelligence

This unit introduces core concepts that distinguish decision intelligence from data science and business intelligence, examining how data, models, and human judgment interact in organizational decision-making. Students will explore decision theory, AI limitations, data quality, uncertainty, and role design to prepare for applying decision intelligence methods in later units.

Learning Objectives

• Analyze the differences between raw data, business intelligence, and decision intelligence using real-world examples and case scenarios.
• Apply decision-theory frameworks and the upside-down V workflow to map decision paths and trace outputs back to their critical inputs.
• Evaluate the capabilities, limitations, and ethical considerations of AI and automation in business decisions, including common data pitfalls and sources of uncertainty.
• Demonstrate strategies for redesigning roles, responsibilities, and actionable outcomes to integrate human judgment with AI assistance effectively.