◆ By Need
AI can draft it, run it and log it. It still can't decide what learning needs.
Automation took the busywork. What's left is judgment — and most teams have no shared standard for making those calls. These checklists give you one, written for the three roles that carry live learning: instructional designers, facilitators and producers.
Automation didn't remove the judgment calls. It moved them to the front.
Here's the pattern we keep seeing. A team adds AI to design, delivery or production. Output speeds up. Completion looks healthy. Six months later, behavior hasn't changed. The tools did what they were asked. Nobody was left deciding whether the right thing was being asked for.
The split below is the same in every role. What changes is where the line falls — and which calls only a human can make.
What's automatable
- — First drafts, content generation, research synthesis
- — Scheduling, transcription, chat routing, tech monitoring
- — Attendance, timing, engagement flags, follow-up logistics
- — Performance data analysis and summary reporting
What's human
- — Sequencing for transfer, prerequisites and cognitive load
- — Reading the room — energy, silence, the retracted question
- — Deciding when to intervene and when to let a group struggle
- — Protecting psychological safety while sessions scale
AI flags that engagement dropped in minute 23. It can't tell you why. Only you can read the pause, notice the tone shift, sense when someone's confused but afraid to speak.
Three checklists. One for each role that carries the session.
Integrating AI into instructional design
Move from content creator to learning architect. Work through the questions AI can't answer: what job pressure undermines this skill, which prerequisite is missing, where transfer breaks down. Structured across analyze, architect and test.
Orchestrating AI in live learning
AI manages chat, flags drift and tracks time. You own the room. This checklist covers the calls you make before, during and after a session — pacing, intervention, safety and the coaching conversation that closes the loop.
From tech operator to learning advocate
When AI handles moderation and attendance, the risk is that nobody watches people. This checklist makes the shift explicit: what to monitor, when to step in, and how to keep quality from slipping as session volume grows.
Get yours
Which role are you in?
Pick one. We'll ask three quick questions and send the checklist straight to your inbox. No series, no drip, just the one you asked for.
Select an option below:
- For Instructional Designers
- For Facilitators
- For Producers
The AI design checklist
13 decisions for architecting learning that changes behavior, not just content that gets completed
The AI production checklist
17 decisions for moving from tech operator to learning advocate as automation takes the console
The AI facilitation checklist
14 decisions for owning the room while AI handles chat timing and engagement data14 decisions for owning the room while AI handles chat timing and engagement data
