Introduction
Welcome to Module 2. Now that you understand how AI actually works — as a pattern engine, not a thinker — the next question is practical: where should you actually use it? Not all tasks carry the same risk. This module gives you a simple framework for telling the difference.
What you'll learn in this module
- 1Not All Decisions Are Created Equal
- 2AI Shines in Exploration, Not Final Calls
- 3Human Accountability Cannot Be Delegated
- 4Small Errors Compound in Workflows
Imagine the following scenario
A team lead uses AI to draft a performance review. The draft is articulate, balanced, and professional — maybe too balanced. It smooths over a serious performance issue that needed direct, unambiguous language. The review goes out as written. The employee reads it and thinks everything is fine. Six months later, the real conversation finally happens — but now the written record contradicts reality. The employee feels blindsided. HR has a documentation problem. The team lead has a trust problem.
Have you ever let AI soften something that needed to stay sharp?