From AI Potential to Performance

This unit introduces how to move AI from an experimental capability to measurable business performance using a demonstration-driven (“show, don’t tell”) approach. Students learn to identify high-impact opportunities, define success metrics, and compare demonstration vs. instruction strategies to prepare for hands-on prompt design and deployment in later units.

Learning Objectives

• Analyze a given business process and identify at least three high-impact opportunities where AI could measurably improve outcomes (e.g., efficiency, accuracy, customer experience).
• Apply the “show, don’t tell” demonstration-driven method to create and iterate at least two example demonstrations or prompts tailored to a specific business scenario to improve AI output relevance.
• Demonstrate how to define and map performance metrics and success criteria (KPIs) for an AI-enabled workflow by producing a one-page performance plan for a selected use case.
• Evaluate differences and trade-offs between demonstration-driven and instruction-driven AI approaches by comparing outcomes across defined metrics and recommending the optimal approach for a stated business objective.