🛡️AI Guardrails
How to set AI rules that protect your company without slowing innovation.
What you'll learn
- Build a data sensitivity matrix for AI
- Set up an AI tool approval process
- Write AI usage policies people actually follow
- Prepare an incident response plan for AI failures
Who this is for
Managers, CTOs, CISOs, legal teams, and anyone responsible for AI policy in their organization.
Syllabus
Why You Need Guardrails — Not Bans or Free-for-All
Between 'AI is banned' and 'do whatever you want' lies a huge gap. Guardrails fill it — protecting your company while making room for innovation.
Data Classification: What Can Go Into AI and What Cannot
A practical data sensitivity matrix. Which information you can safely process in AI tools and where to draw the line.
Tool Approval: How to Select and Authorize AI Solutions
How to evaluate AI tools against security, privacy, and cost criteria. A practical approval process that does not slow down innovation.
AI Usage Policies: Rules People Actually Follow
How to write an AI policy people will read and adhere to. Templates, examples, and the psychology of rule compliance.
Incident Response: When AI Goes Wrong
Data leaks, incorrect outputs, costly mistakes. What to do when AI fails — and how to prepare in advance.
Your Policy Document: From Course to Practice
Assemble your AI policy document step by step. Leave with a draft ready to present to leadership.