Governance Framework
Compliance, Risk Management, and Responsible AI
Compliance Overview
92%
ComplianceCompliance Status
Your platform is currently compliant with all major regulatory requirements. There are 3 high-risk items that need attention in the next 30 days to maintain compliance.
Regulatory Framework Compliance
Risk Summary
Risk Items
Policy Compliance by Area
| Policy Area | Policies | Compliance | Status |
|---|---|---|---|
| Data Governance | 18 |
|
Compliant |
| Security Controls | 24 |
|
Compliant |
| AI Ethics | 12 |
|
Review Needed |
| Privacy | 20 |
|
Compliant |
| Operational | 15 |
|
Compliant |
Compliance Control Framework
Access Controls
- Role-based access control
- Principle of least privilege
- Separation of duties
- Access review procedures
Data Protection
- Data classification
- Encryption requirements
- Data retention policies
- Data anonymization
Change Management
- Risk assessment procedures
- Approval workflows
- Rollback procedures
- Documentation requirements
Monitoring & Audit
- Audit logging requirements
- Monitoring procedures
- Alert thresholds
- Review frequencies
Policy Compliance Actions
Policy Compliance Status
82 of 89 policies are currently in compliance (92%).
High Priority Actions
Data Retention Policy
Update data retention policy to comply with new GDPR requirements for vector embeddings and model outputs.
User Consent Framework
Implement enhanced user consent mechanisms for AI-generated content and recommendations.
Recently Updated Policies
Upcoming Reviews
-
Scheduled
Quarterly Security Assessment
Due in 14 days -
Scheduled
Annual Compliance Review
Due in 45 days
Audit Summary
Audit Results
Upcoming Audits
-
GDPR Compliance Audit
Scheduled: May 28, 2025External Data Privacy -
Model Bias Detection Review
Scheduled: June 12, 2025Internal AI Ethics -
Security Controls Assessment
Scheduled: June 20, 2025External Security
Recent Audit Reports
| Date | Audit Type | Status | Score | Findings | Actions |
|---|---|---|---|---|---|
| 2025-04-22 | Data Privacy | Passed |
94
|
No issues | |
| 2025-04-15 | Security Controls | Passed |
91
|
No issues | |
| 2025-04-08 | Model Fairness | Passed with Comments |
87
|
3 minor issues | |
| 2025-03-25 | Data Lineage | Passed |
92
|
No issues | |
| 2025-03-18 | Access Controls | Passed |
95
|
No issues |
Most Recent Audit: Data Privacy
Summary
The audit evaluated the platform's compliance with data privacy regulations and best practices. The platform demonstrates strong compliance with data minimization, purpose limitation, and user consent requirements.
Key Findings
- Strong data encryption and anonymization practices
- Clear data retention and deletion procedures
- Comprehensive privacy impact assessments
- Well-implemented user consent mechanisms
- Minor recommendations for enhancing data subject access request processes
Responsible AI Metrics
Fairness
Explainability
Transparency
Safety
Human Oversight
Overall Score
Areas for Improvement
| Area | Current Score | Target Score | Gap | Progress |
|---|---|---|---|---|
| Model Explainability | 82 | 90 | 8 |
|
| Bias Detection | 85 | 92 | 7 |
|
| Documentation Completeness | 83 | 95 | 12 |
|
Responsible AI Framework
AI Ethics Committee Update
The AI Ethics Committee has updated the Responsible AI Framework to incorporate the latest regulatory requirements and industry best practices. The platform's compliance with this framework is currently at 88%.
Governance Controls
- Automatic Bias Detection - Monitoring for demographic parity and equal opportunity
- Fairness Metrics - Regular evaluation against established fairness criteria
- Diverse Training Data - Requirements for training data diversity
- Bias Mitigation - Pre-processing, in-processing, and post-processing techniques
- Documentation Standards - Required documentation for model decisions
- Interpretability Methods - Feature importance, LIME, SHAP values
- Decision Traceability - Audit trails for agent decisions
- User Explanations - User-friendly explanations of AI outputs
- AI Interaction Disclosure - Clear indication when users interact with AI
- Model Cards - Standardized documentation of model capabilities and limitations
- Data Sheets - Documentation of training data sources and characteristics
- Confidence Scores - Transparent communication of confidence levels
- Human-in-the-Loop - Defined escalation pathways for high-risk decisions
- Manual Review Thresholds - Confidence thresholds for automatic escalation
- Override Mechanisms - Ability to override automated decisions
- Feedback Loops - Human feedback integration into system improvements
Certification Status
TÜV AI Certification
Certified for compliance with AI quality and safety standards.
Certified Valid until: March 2026ISO/IEC 42001
AI management system certification.
Certified Valid until: November 2025EU AI Act Compliance
Conformity with EU AI regulations.
In Progress Expected: August 2025High Risk Items
Model Explainability for Regulated Industries
High RiskCurrent explainability methods may be insufficient for financial and healthcare decisions, potentially violating regulatory requirements.
Demographic Bias in Customer Support Agents
High RiskAnalysis found potential bias in customer support agent responses based on inferred demographic characteristics of users.
Data Retention Policy Compliance
High RiskCurrent data retention practices for model training logs and user interactions do not fully align with updated GDPR requirements.
Risk Response Framework
Risk Treatment Approach
Mitigate
Implement controls to reduce risk to acceptable levels through technical or procedural safeguards.
Share
Transfer or share risk through insurance, partnerships, or third-party verification.
Avoid
Eliminate risk by removing the feature or capability that creates the risk exposure.
Accept
Acknowledge and accept the risk after documenting the decision and getting approval.
Risk Assessment Triggers
-
New Agent Deployment
Full risk assessment required for all new agent deployments
-
Use Case Expansion
Assessment when existing agents are deployed to new domains
-
Model or System Changes
Incremental assessment for significant updates or changes
-
Regulatory Changes
Re-assessment when relevant regulations are updated
Medium & Low Risk Items
Third-Party Model Dependencies
Medium RiskDependency on external AI models creates potential for service disruptions if provider changes terms or deprecates models.
Risk Category: OperationalModel Drift in Production
Medium RiskPerformance degradation over time as real-world data diverges from training data distributions.
Risk Category: Data QualityIncomplete Agent Documentation
Medium RiskSome agents lack complete documentation on capabilities, limitations, and appropriate use cases.
Risk Category: ExplainabilityUI/UX Inconsistencies in Agent Interfaces
Low RiskMinor inconsistencies in how agents present information to users across different interfaces.
Risk Category: OperationalPerformance Variability with High Load
Low RiskResponse time degradation during peak usage periods.
Risk Category: OperationalAgent Knowledge Boundaries
Low RiskSome agents may provide outdated information in rapidly evolving domains.
Risk Category: Data QualityRisk Mitigation Example
Model Explainability for Regulated Industries
Risk Description
Current explainability methods may be insufficient for financial and healthcare decisions, potentially violating regulatory requirements in those sectors.
Risk Category
ExplainabilitySeverity
HighTreatment
MitigateMitigation Plan
| Action | Owner | Status | Due Date |
|---|---|---|---|
| Implement domain-specific explanation templates | Product Team | Complete | April 10, 2025 |
| Enhance factor attribution for decision models | Data Science | In Progress | May 15, 2025 |
| External review by regulatory compliance experts | Legal | Planned | June 5, 2025 |
| Documentation updates for regulated industries | Documentation | Planned | June 20, 2025 |
Risk Management Lifecycle
Identify
- Regular risk assessment sessions
- Automated testing and scanning
- Incident reporting system
- Stakeholder consultations
Assess
- Risk scoring methodology
- Impact and likelihood evaluation
- Regulatory impact analysis
- Business continuity assessment
Mitigate
- Risk treatment planning
- Control implementation
- Process modifications
- Governance enhancements
Monitor
- Periodic risk reviews
- Control effectiveness testing
- Key risk indicators
- Continuous improvement process
Governance Documentation
Key Governance Policies
Compliance Templates & Tools
Risk Assessment Matrix
Template for evaluating AI risks and determining appropriate controls.
Download