ISO/IEC 23894 – AI Risk Management Training by Tonex
ISO/IEC 23894 – AI Risk Management Training by Tonex provides professionals with a structured understanding of risk management principles for artificial intelligence systems based on ISO/IEC 23894. Participants learn how to identify, analyze, evaluate, treat, monitor, and communicate AI-related risks throughout the system lifecycle. The course addresses governance, accountability, transparency, uncertainty, data considerations, and organizational integration of AI risk practices.
Effective AI risk management also strengthens cybersecurity by identifying threats, vulnerabilities, misuse scenarios, and security dependencies affecting AI systems. It supports stronger cybersecurity controls by connecting AI-specific risks with enterprise security, privacy, resilience, and governance practices.
The course uses a practical training approach that includes exercises, real-world case studies, and examples of processes and documentation used in AI risk management projects.
Learning Objectives
Upon completion of this course, participants will be able to:
- Explain the purpose, scope, terminology, and principles associated with ISO/IEC 23894 and AI risk management.
- Identify AI-specific risk sources, impacts, uncertainties, stakeholders, dependencies, and organizational considerations.
- Apply structured methods for AI risk identification, analysis, evaluation, treatment, monitoring, and communication.
- Integrate AI risk management activities with organizational governance, enterprise risk management, and management systems.
- Evaluate risks related to data quality, model behavior, transparency, explainability, accountability, reliability, and human oversight.
- Develop appropriate AI risk documentation, records, responsibilities, criteria, controls, and reporting mechanisms.
- Strengthen cybersecurity by incorporating security threats, vulnerabilities, resilience, privacy, and adversarial risks into AI risk management.
Audience
This course is suitable for:
- AI Risk Management Professionals
- AI Governance and Compliance Professionals
- Cybersecurity Professionals
- Risk Managers and Enterprise Risk Professionals
- AI Program and Project Managers
- Data Scientists and AI Engineers
- Information Security Professionals
- Privacy and Data Protection Professionals
- Internal Auditors and Assurance Professionals
- Compliance and Regulatory Professionals
- Technology Managers and Business Leaders
- Responsible AI and AI Ethics Professionals
Course Modules
Module 1: AI Risk Management Foundations
- Purpose and scope of ISO/IEC 23894
- Core concepts and AI risk terminology
- Characteristics of artificial intelligence risk
- Risk management principles and organizational context
- Stakeholder roles, expectations, and responsibilities
- Integrating AI risk into enterprise governance
Module 2: AI Risk Identification Methods
- Identifying AI risk sources and events
- Mapping affected stakeholders and business processes
- Recognizing uncertainty and system dependencies
- Evaluating data-related risk conditions
- Identifying misuse and unintended consequences
- Documenting risk scenarios and assumptions
Module 3: Risk Analysis and Evaluation
- Establishing AI risk assessment criteria
- Analyzing likelihood, consequence, and uncertainty
- Evaluating severity and potential organizational impact
- Assessing transparency and explainability concerns
- Prioritizing identified AI risks systematically
- Recording evaluation decisions and supporting evidence
Module 4: AI Risk Treatment Planning
- Selecting appropriate AI risk treatment options
- Designing controls for identified AI risks
- Defining risk ownership and accountability
- Establishing implementation priorities and responsibilities
- Managing residual and emerging AI risks
- Maintaining treatment plans and decision records
Module 5: Governance Monitoring and Communication
- Establishing AI risk governance structures
- Monitoring risk indicators and control performance
- Communicating AI risks to relevant stakeholders
- Developing reporting and escalation mechanisms
- Maintaining traceable AI risk documentation
- Reviewing risk management effectiveness periodically
Module 6: Secure Responsible AI Integration
- Connecting AI risk with cybersecurity practices
- Addressing privacy, security, and resilience risks
- Managing adversarial and malicious AI threats
- Integrating human oversight and accountability
- Aligning AI risk with organizational processes
- Supporting continual improvement and responsible AI
Build a structured approach to identifying, evaluating, treating, and governing artificial intelligence risks with ISO/IEC 23894 – AI Risk Management Training by Tonex. Develop practical knowledge for implementing effective AI risk management practices while strengthening governance, cybersecurity, resilience, accountability, and responsible AI across your organization.