In 30 seconds
- Clear, short rules beat long policies nobody reads.
- Cover data, security, accountability and disclosure.
- Build checks into the workflow, not after it.
Key areas
| Area | Question |
|---|---|
| Data | What can be shared with which tools? |
| Security | How is AI-generated code checked for vulnerabilities? |
| Accountability | Who approves and owns AI output? |
| Licensing | How do we handle generated code's provenance? |
| Transparency | When do we disclose AI use to users or customers? |
A lightweight starter
- A list of approved tools and what data each may see
- Human review for all AI-generated changes
- Security scanning in the pipeline
- A named contact for questions
Embedding it
Put the key rules into the Definition of Done and working agreements, automate checks with security testing, and review the rules quarterly. See agile governance.
Myth vs reality
Myth · Governance means banning AI.
Reality · Good governance enables safe use.
Myth · A policy document is enough.
Reality · Rules work only when built into the workflow.
Myth · Governance is IT's job.
Reality · Teams apply it daily.
FAQ
Who writes the rules?
Security, legal and engineering together, with team input.
How often should rules change?
Review them regularly; tools change quickly.
What about regulated industries?
Add domain rules; see agile compliance.