Module 1/5 25 min
Mapping AI in Talent Development
Step 1 / 3·The 5 application areas
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Learning objectives — after this module you will:
- Grasp the 5 application areas of AI in TD
- Distinguish AI that supports decisions from AI that makes decisions
- Learn from IBM's AI-in-HR journey
Learn ~8 min
The 5 application areas
Get the big-picture map before diving deep.
What is AI doing in TD?
| Area | What AI helps with | Example application |
|---|---|---|
| TNA & gap analysis | Reads performance data, job descriptions and feedback to suggest needs | Analyze recurring error tickets to find skill gaps; infer skills from work data (skills inference) |
| Content design | Speeds up authoring of curricula, cases, questions, scripts | Use Claude to design a course (exactly TTD's AI-Powered Training Design course) |
| Assessment & adaptive learning | Generates questions, drafts preliminary essay grading, adjusts difficulty to the learner | Personalized learning path: skip what you're strong at |
| Coaching & performance support | Conversation practice assistant, instant feedback, support in the flow of work | Roleplay handling a difficult customer with AI before facing a real one |
| Learning analytics | Detects learning patterns, predicts risk, measures impact | Early warning for learners at risk of dropping out of a pathway |
The most important boundary
AI that SUPPORTS decisions (suggests, summarizes, warns — a human decides) is fundamentally different from AI that MAKES decisions (auto-grading pass/fail, auto-ranking potential). For decisions that affect people — promotions, ratings, HiPo selection — the unbreakable principle is: human-in-the-loop, AI proposes, a human is accountable for the decision.
Key takeaway: 5 areas: TNA, design, assessment, coaching, analytics — and the boundary: AI proposes, a human decides.