AI Risk Management & Governance (NIST AI RMF, ISO/IEC 42001) Essentials Training by Tonex
Artificial intelligence adoption brings innovation but also introduces risks that demand structured governance. This course provides a practical framework for aligning AI initiatives with organizational goals using NIST AI Risk Management Framework (AI RMF) and ISO/IEC 42001. Participants will gain the knowledge to identify, assess, and mitigate risks while ensuring responsible AI deployment. A strong emphasis is placed on cybersecurity, as poorly governed AI systems can expose vulnerabilities, amplify attack surfaces, and cause compliance failures. By mastering governance standards, learners will strengthen both trust and resilience in AI-powered enterprises.
Learning Objectives:
- Understand the foundations of NIST AI RMF and ISO/IEC 42001
- Apply AI governance principles across organizational workflows
- Identify and manage AI system risks with structured frameworks
- Strengthen compliance and accountability in AI lifecycle management
- Integrate risk-based controls to prevent exploitation of AI vulnerabilities
Audience:
- Cybersecurity Professionals
- AI Governance Officers
- Risk and Compliance Managers
- Data Scientists and Engineers
- IT Managers and Architects
- Business Leaders and Policy Advisors
Course Modules:
Module 1: Foundations of AI Governance
- Overview of AI governance landscape
- Core principles of responsible AI
- NIST AI RMF structure and purpose
- ISO/IEC 42001 standard introduction
- Risk vs. opportunity in AI adoption
- Regulatory and policy alignment
Module 2: NIST AI RMF in Practice
- Risk identification methodologies
- Trustworthiness and reliability dimensions
- Mapping AI lifecycle stages
- Integrating RMF into decision-making
- Monitoring AI system performance
- Documentation and transparency practices
Module 3: ISO/IEC 42001 Essentials
- Scope and objectives of ISO/IEC 42001
- Key requirements for AI management systems
- Alignment with existing ISO frameworks
- Governance of AI supply chains
- Certification pathways and benefits
- Building organizational accountability
Module 4: AI Risk Management Strategies
- Frameworks for AI risk categorization
- Threat modeling in AI environments
- Bias, fairness, and ethical challenges
- Incident response for AI failures
- Business continuity considerations
- Metrics for evaluating risk effectiveness
Module 5: Cybersecurity and AI Governance
- AI attack surfaces and vulnerabilities
- Securing AI training data and models
- Defensive controls for adversarial AI
- Integrating cybersecurity with governance
- Compliance with global security standards
- Case examples of AI-related breaches
Module 6: Governance Implementation Roadmap
- Establishing governance structures
- Roles and responsibilities in AI oversight
- Embedding governance in project pipelines
- Communication and stakeholder alignment
- Continuous monitoring and auditing
- Maturity models for AI governance evolution
Strengthen your organization’s ability to manage AI responsibly with Tonex’s AI Risk Management & Governance Training. Gain expertise in NIST AI RMF and ISO/IEC 42001 to build trustworthy, secure, and resilient AI systems. Enroll today and lead the way in responsible AI adoption.