AI in Human Work – Abilities, Applications, and Value Creation
Lesson 1: The AI Capability Map – From Conversation to Work Product
Lesson Objectives
By the end of this lesson, students should be able to:
- Describe AI as a work-product engine, not just a chatbot.
- Distinguish generation, transformation, analysis, extraction, planning, simulation, and tool use.
- Match each capability to a real deliverable.
Lesson Content
Modern AI is valuable when it changes the work a person can complete. That is why this path focuses on outputs, decisions, and repeatable workflows rather than trivia about the tool.
Core capability categories:
- Generate: create drafts, options, examples, scripts, lesson plans, emails, outlines, images, or code.
- Transform: rewrite, summarize, translate, format, simplify, restructure, or adapt material for a new audience.
- Extract: pull requirements, risks, names, action items, claims, contradictions, or data points from messy material.
- Analyze: compare options, find patterns, critique arguments, inspect datasets, evaluate decisions, or review evidence.
- Plan: turn a goal into phases, tasks, owners, dependencies, milestones, checklists, or review gates.
- Simulate: role-play customers, interviewers, reviewers, students, stakeholders, edge cases, objections, or failure scenarios.
- Operate with tools: use files, search, code, apps, connectors, or supervised agent features when available.
The professional difference is not whether AI can produce text. It is whether you can scope the work, give useful context, judge the output, verify claims, and turn the result into something another person can use.
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