# AI for Managers and Leaders: Leading Teams, Choosing Use Cases, and Managing Risk

**Course FAST-09** · 9 hours · Instructor: Wadood Chaudhary · Presented by 7formations

## Session 1. Using AI as a manager (3 hours)

- Data rules for managers (employee and customer data)
- Three management tasks hands-on
- Supervising AI-assisted work: what to check
- **Lab 1: Own-use outputs with review notes.**

## Session 2. Choosing and justifying use cases (3 hours)

- Use-case matrix
- ROI and time-savings math
- Build, buy, or wait
- **Lab 2: Matrix and ROI worksheet.**

## Session 3. Leading the change (3 hours)

- Team AI use guideline
- Talking with staff about AI
- Measuring without surveillance
- 90-day plan
- **Lab 3: Guideline and 90-day plan.**

## Worksheets and deliverables

- W1 Own-use review notes
- W2 Use-case matrix
- W3 ROI worksheet
- W4 Team AI use guideline
- Final 90-day adoption plan

## Attendance and completion

- Attendance is recorded at the start and end of every session (live virtual: platform attendance log plus an instructor roll call or poll; in-person: signed sheet).
- A trainee must attend 100% of instructional hours. A missed session may be made up by attending the same session in another scheduled cohort within 30 days; the make-up is logged the same way.
- A trainee must submit every required lab deliverable and score 'Meets' on the final applied task.
- Each completion record is tied to the trainee, the employer FEIN, and the course number, and is kept for the contract retention period.
- Incomplete trainees are not reported as completions and are not billed to anyone. FAST AI pays for completions only; employers and trainees are never charged.
- Optional asynchronous pre-work (under 10% of course time) is supplemental, is not counted as instructional hours, and never substitutes for a live session.

## Assessment rubric

Each criterion is scored Not yet / Meets / Strong. Completion requires Meets on every criterion for the final deliverable (resubmission allowed within the course window).

| Criterion | Meets standard |
| --- | --- |
| Judgment | Use cases ranked with sound value and risk reasons |
| Business case | ROI math correct and assumptions stated |
| Policy fit | Guideline consistent with employer policy and data law |
| Plan quality | Milestones, training, measures, and communication present |