Risk review sheet
Client-data analysis
- Data
- Confidential
- Decision
- Advisory
- Tier
- Review
Move faster with clear boundaries
Practical AI Governance
Give people a clear way to decide what is allowed, what needs review, and what stays off limits.
Use-case register
Document summaryApprovedClient analysisReviewExternal commitmentsRestricted
Governance document set
Responsible AI Policy
Policy owner: Operations · Review cycle: Quarterly
01
Approved toolsUse company-approved AI environments only.
02
Data boundariesDo not enter restricted client or employee data.
03
Human reviewAn assigned owner reviews work before action.
Approved by AI Governance LeadEB
The business problem
What usually needs to change first.
Create usable policies, review points, and ownership that support adoption without turning governance into paperwork.
- Employees use AI without common rules
- Policies are too broad to guide daily work
- Nobody owns use-case approval or monitoring
- Sensitive information may enter unapproved tools
How the work operates
A controlled path from idea to use.
The exact technology depends on the workflow. The operating pattern remains understandable, testable, and owned.
Inventory
Identify active and proposed AI use cases, tools, data, and owners.
Classify
Apply practical risk tiers based on data, decisions, and external impact.
Control
Define required review, testing, documentation, and escalation.
Monitor
Track approved use, changes, incidents, and periodic reassessment.
Human and AI responsibilities
The handoff is designed, not assumed.
A useful implementation makes it obvious where AI prepares work and where a person reviews, decides, or acts.
People remain responsible for
- Set policy and risk appetite
- Approve high-impact use cases
- Monitor exceptions and incidents
AI can support
- Help maintain the inventory
- Draft documentation from approved facts
- Surface incomplete control information
Systems and inputs
- Use-case register
- Policy library
- Approved vendor list
- Issue and review log
Expected outputs
- Practical AI policy
- Use-case inventory
- Risk classification model
- Review and escalation workflow
Practical safeguards
- No autonomous approval
- Named accountable owner for every use case
- Controls scale with risk and impact
See whether this fits one of your real workflows.
We can begin with a focused working session and define the smallest responsible next step.