Intermediate course · Free
AI at Work
Evaluate workplace use cases, run safe pilots, measure value, and communicate changes responsibly.
For: Professionals, managers, job seekers, and small organizations
- Use-case selection2 guides
- Pilots and experiments2 guides
- People and jobs2 guides
- Operational governance3 guides
- 4Modules
- 9Guides
- ~6hTo complete
- 11Competencies
Outcomes
What you will be able to do
- Select use cases using value, feasibility, and risk.
- Run a bounded pilot with measurable success criteria.
- Plan adoption without hiding workforce or governance impacts.
Recommended first: Responsible AI User
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Curriculum
Course modules
- Module 1
Use-case selection
Outcome: Prioritize tasks where AI can create measurable value.
Practice: Score three candidate use cases on value, feasibility, reversibility, and risk.
Tool selection and comparisonAI-assisted workflow design - Module 2
Pilots and experiments
Outcome: Design a comparison that can reveal whether AI actually helps.
Practice: Write a pilot plan with baseline, treatment, metrics, stop conditions, and review owner.
Experiment and pilot designSuccess metrics and monitoringModel cost and operational tradeoffs - Module 3
People and jobs
Outcome: Assess task changes without reducing workers to job titles.
Practice: Create a task-level impact map and reskilling plan.
Workforce and job impactsAI career readinessStakeholder communication - Module 4
Operational governance
Outcome: Assign ownership for approvals, monitoring, and incidents.
Practice: Build a lightweight responsibility matrix for one deployed workflow.
Governance and accountabilityAI incident responsePrivacy and data handling
Applied capstone
AI pilot proposal
Produce a decision-ready pilot proposal for a real organization.
Evidence checklist
- Use-case scorecard
- Baseline and success metrics
- Risk controls
- Adoption and review plan