Total Risks: 6
High Risk: 2
Medium Risk: 3
Low Risk: 1
AI model may perpetuate historical biases in candidate selection, leading to discrimination.
Mitigation: Implement bias testing, diverse training data, regular audits, and human oversight.
Current data handling practices may not fully comply with GDPR requirements.
Mitigation: Conduct privacy impact assessment, implement data minimization, obtain explicit consent.
AI model accuracy may degrade over time due to changing data patterns.
Mitigation: Implement continuous monitoring, automated alerting, and regular retraining schedules.
Black-box models cannot provide explanations for decisions, violating regulatory requirements.
Mitigation: Implement SHAP/LIME explanations, model documentation, and decision audit trails.
External AI services may not meet internal governance standards.
Mitigation: Vendor assessment framework, contractual requirements, regular audits.
Some AI systems lack complete documentation of development process.
Mitigation: Implement documentation templates and mandatory review checkpoints.
Last audit: 2025-11-15
Last audit: 2025-12-01
Last audit: 2025-10-20
Last audit: 2025-11-30
Last audit: 2025-12-10
Last audit: 2025-11-25
| Requirement | Standard | Status | Due Date | Owner |
|---|---|---|---|---|
| Data Processing Impact Assessment | GDPR Art. 35 | Complete | 2025-12-31 | Privacy Team |
| AI System Risk Classification | EU AI Act | In Progress | 2026-01-15 | AI Governance |
| Model Bias Testing | NIST AI RMF | Complete | Quarterly | ML Engineering |
| Security Controls Audit | SOC 2 | Complete | 2025-12-20 | Security Team |
| Transparency Documentation | EU AI Act | In Progress | 2026-02-01 | Product Team |
| Human Oversight Procedures | EU AI Act | Pending | 2026-01-30 | Operations |
Use the power/interest matrix to prioritize stakeholder engagement.
High Power, High Interest: Manage Closely
High Power, Low Interest: Keep Satisfied
Low Power, High Interest: Keep Informed
Low Power, Low Interest: Monitor
High Power, High Interest
Strategic direction, budget approval, governance oversight
Policy approval, risk review, ethical guidance
High Power, Low Interest
High-level oversight, major decisions, risk awareness
Contract review, compliance verification, liability
Low Power, High Interest
Model development, testing, documentation
User experience, feedback, concerns
Low Power, Low Interest
Service delivery, SLA compliance
Market trends, best practices
Initial
Ad-hoc processes
Developing
Some policies defined
Defined
Documented processes
Managed
Measured & controlled
Optimizing
Continuous improvement
Level 3: Defined
Your organization has documented AI governance processes and is working towards systematic measurement and optimization.