AI governance for Devs: simple rules that work
Source: Dev.to
The 7 Rules for Minimum Viable Governance
1. Humans Own Outcomes
AI can draft, suggest, and summarise, but a human must approve anything that goes to:
- Customers
- Public platforms
- Pricing / terms
- Policies
- Decisions that affect people
Rule: No “AI said so.”
2. Clear “Do Not Share” List
Developers need a one‑page list of what never goes into AI tools:
- Customer identifiers
- Payment details
- Contracts and confidential documents
- Passwords / keys
- Private complaints with names
Rule: If it’s sensitive, it stays out.
3. One Workflow at a Time
Adopting AI across everything is a common failure.
Rule: One workflow → one KPI → 14 days → then expand. This keeps adoption stable and measurable.
4. Quality Checklist for Outputs
Without standards, AI output becomes random. Define what “good” means for:
- Support replies
- Sales messages
- Marketing content
- Internal SOPs
Rule: If it doesn’t meet the checklist, it doesn’t ship.
5. Escalation Rule for Risky Cases
AI should not handle high‑stakes situations alone:
- Angry customers
- Refunds / legal issues
- Medical / financial advice
- Harassment / safety concerns
Rule: When uncertain or sensitive, escalate to a human.
6. Simple Transparency Policy
You don’t need to announce AI everywhere, but if AI affects someone’s outcome (screening, approvals, decisions), clarity matters.
Rule: If it changes a person’s result, be transparent.
7. Learning Loop
Governance isn’t control; it’s improvement. Every week, developers should ask:
- What worked?
- What failed?
- What should be added to the checklist?
- Which outputs caused rework?
Rule: Update the system weekly, not yearly.
Leadership Insight
AI governance is not about restricting teams. It’s about making AI safe for normal people to use inside the business. That is democratisation in practice:
- Accessible
- Repeatable
- Accountable
- Trustworthy