AI Governance Framework
A comprehensive, five-pillar approach to managing AI systems responsibly. Based on industry standards including NIST AI RMF, ISO 42001, and regulatory requirements.
How the Framework Works
Effective AI governance requires a systematic approach that addresses the entire lifecycle of AI systems. Our framework breaks down this complex challenge into five interconnected pillars, each building on the previous one to create a robust governance program.
Unlike purely theoretical frameworks, this approach is designed for practical implementation. Each pillar includes specific activities, tools, and templates that organizations can adapt to their context. Whether you're just starting your AI governance journey or looking to mature existing practices, this framework provides clear guidance for every stage.
The pillars work together: you can't effectively assess risk without knowing what AI you have, you can't implement controls without understanding the risks, and you can't monitor compliance without policies to measure against.
Discovery & Inventory
Establish visibility into AI usage across your organization
Key Activities
- •Create comprehensive AI inventory
- •Identify shadow AI and unapproved tools
- •Document AI use cases and stakeholders
- •Classify AI systems by risk level
Expected Outcomes
- ✓Complete catalog of AI systems
- ✓Clear ownership and accountability
- ✓Foundation for risk assessment
Policy & Standards
Define clear rules and guidelines for responsible AI use
Key Activities
- •Develop acceptable use policies
- •Establish ethical AI principles
- •Create technical standards
- •Define roles and responsibilities
Expected Outcomes
- ✓Clear AI governance policies
- ✓Stakeholder alignment
- ✓Enforceable standards
Risk Assessment
Systematically evaluate and prioritize AI-related risks
Key Activities
- •Conduct risk assessments
- •Evaluate bias and fairness
- •Assess security vulnerabilities
- •Review regulatory compliance
Expected Outcomes
- ✓Prioritized risk register
- ✓Mitigation strategies
- ✓Compliance roadmap
Controls & Guardrails
Implement protections to ensure safe AI deployment
Key Activities
- •Deploy technical controls
- •Implement approval workflows
- •Establish testing requirements
- •Create incident response plans
Expected Outcomes
- ✓Active protection mechanisms
- ✓Controlled AI deployment
- ✓Incident readiness
Monitoring & Compliance
Maintain ongoing oversight and continuous improvement
Key Activities
- •Monitor AI system performance
- •Conduct regular audits
- •Track compliance metrics
- •Drive continuous improvement
Expected Outcomes
- ✓Real-time visibility
- ✓Compliance assurance
- ✓Governance maturity growth
Getting Started
Assess Your Maturity
Use our maturity model to understand where you are today and identify priority areas.
Take Assessment →Download Templates
Access ready-to-use policy templates, checklists, and assessment tools.
Get Templates →Implement Incrementally
Focus on one pillar at a time. Start with Discovery to build visibility.
Start with Discovery →Need Help Implementing?
Aona AI provides enterprise AI governance solutions to help you implement this framework at scale.
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