What it means
The governance model should address data use, model behavior, access, retention, third parties, human oversight, monitoring, cost, and provider changes.
Why it matters
Easy access to managed AI can accelerate experimentation while spreading sensitive data and consequential decisions into services that teams do not fully understand.
Practical focus
- Classify use cases by impact and data sensitivity
- Approve providers, models, regions, and data-handling settings
- Monitor outputs, access, cost, and material provider changes
Common mistakes
- Treating a managed API as low risk because no model is hosted locally
- Sending sensitive data without retention review
- Using model output without validation or accountable human decisions
Certification relevance
This subject appears in or supports the following certification bodies of knowledge: