Case study 02 of 15
Governance Without Red Tape Through Risk Zones
Builders needed clear paths for different kinds of AI work, not one review model for all of it.
Business challenge
A single review process was too slow for low-risk experimentation and too weak for higher-risk, customer-facing work.
Architecture approach
Personal productivity, department-level solutions, and enterprise-grade solutions were split into distinct risk tiers, each with its own path to production.
How the work moved from request to production
- Business need
- Intake & risk classification
- Select reusable pattern
- Build / configure
- Review & validate
- Deploy / enable
- Monitor usage, risk, cost, value
Governance considerations
Controls scaled with risk — training and safe defaults for the lightest tier, environment separation and publishing review for the middle, stronger controls reserved for sensitive or broad-impact use cases.
Results
Builders gained clarity, reviewers focused their attention where it actually mattered, and unnecessary friction dropped out of the process.
Lesson learned
The best governance models route work correctly instead of treating every request as an exception.
Discussion questions
- What belongs in the lowest-risk zone?
- When should a solution graduate to a higher zone?
- Who has the authority to approve exceptions?