Intermediate
Manager Path
For leaders and managers who need to make real decisions about AI — where to invest, what to buy, how to govern, and how to explain it to the business. No coding required.
Steps 11
Est. time ~2.5 hours
Prerequisites None — non-technical
The Path
1
The AI Model Landscape
A non-technical overview of the major AI providers and what they offer. Know the names and positions before evaluating vendors.
12 min
2
Hallucinations and Limitations
Every AI decision at the org level must account for what AI can't do. Understand failure modes before you approve adoption.
10 min
3
Why Model Selection Matters
AI costs scale with usage. Learn the cost structures behind AI before approving budgets or vendor contracts.
10 min
4
Use Case Discovery
How to find the AI use cases worth pursuing in your organization — a structured approach to prioritization.
12 min
5
Build vs Buy vs Partner
Should you build an internal AI system, buy a vendor solution, or partner with an AI company? A decision framework.
12 min
6
Measuring ROI of AI Projects
How to define success metrics for AI initiatives and report value to the business. Avoid vanity metrics.
12 min
7
Workforce Impact of AI
Understand how AI changes roles, what skills become more valuable, and how to manage the transition.
12 min
8
The AI Operating Model
How leading organizations structure AI teams, governance, and delivery — the org design layer of AI adoption.
15 min
9
AI Governance Overview
What governance means in practice: policies, oversight, accountability. Necessary before any production deployment.
12 min
10
The EU AI Act
The world's first comprehensive AI law affects most organizations, not just EU ones. Know what it requires.
12 min
11
Compliance Checklist
Practical checklist for enterprise AI compliance — data privacy, audit trails, human oversight, bias testing.
10 min
After This Path
You now have the strategic and governance context to lead AI adoption confidently. Good follow-on sections:
- Enterprise AI section — reliability, FinOps, responsible deployment at scale
- Full Governance section — security, ethics, privacy, explainability, red teaming
- AI in Industry — sector-specific playbooks (healthcare, legal, finance, education)
- Strategy subsection — more depth on change management and open-source economics
Checklist: Do You Understand This?
- Can you name the major AI providers and what they offer at a high level?
- Do you have a framework for evaluating which AI use cases to pursue first?
- Can you articulate how to measure ROI on an AI project to your executive team?
- Do you understand what the EU AI Act requires and whether it applies to your organization?
- Can you describe the key components of an AI operating model?
- Do you know what governance controls are needed before deploying AI in a production context?