The Lead AI Risk Manager is delivered as an intensive two-day training programme, structured around five integrated competency domains. Throughout the training, participants work with practical examples, real-world scenarios and recognised AI risk management frameworks to prepare for both operational implementation and the official PECB certification exam.
Module 1 – AI Risk Principles, Concepts & Regulations
- Fundamentals of AI risk management
- AI lifecycle and emerging AI risks
- AI harms, impacts and trustworthiness
- International AI standards and frameworks
- EU AI Act and global AI regulations
- ISO/IEC 23894, ISO/IEC 42001 and NIST AI RMF
- Ethical and responsible AI principles
Outcome: Participants gain a solid understanding of the AI risk landscape, international standards and regulatory obligations that form the foundation of effective AI risk management.
Module 2 – AI Risk Governance & Risk Management Programme
- Establishing AI risk governance
- Roles and responsibilities
- AI risk management processes
- Governance structures and accountability
- AI policies and organisational controls
- Risk culture and management commitment
- Integration with enterprise risk management
Outcome: Participants learn how to build and govern an AI risk management programme that aligns with organisational objectives, governance frameworks and regulatory expectations.
Module 3 – AI Risk Identification & Analysis
- AI risk identification techniques
- Risk sources across the AI lifecycle
- Bias and fairness risks
- Security and adversarial threats
- Privacy and data governance risks
- Transparency and explainability challenges
- Risk analysis methodologies
Outcome: Participants develop the ability to systematically identify, categorise and analyse AI-related risks before they impact business operations or regulatory compliance.
Module 4 – AI Risk Evaluation, Treatment & Monitoring
- AI risk evaluation methodologies
- Risk prioritisation
- Selecting appropriate controls
- Designing AI risk treatment plans
- Continuous monitoring and reporting
- Measuring control effectiveness
- Continuous improvement and post-deployment monitoring
Outcome: Participants learn how to evaluate AI risks, implement effective mitigation strategies and continuously monitor AI systems throughout their operational lifecycle.
Module 5 – Organisational Learning & Performance Improvement
- Incident response for AI-related events
- Lessons learned and continuous improvement
- AI risk reporting
- Performance metrics and KPIs
- Organisational learning
- Maintaining long-term AI resilience
Outcome: Participants understand how organisations can continuously improve AI governance through structured monitoring, performance measurement and organisational learning.
Certification Exam
Following the training, participants can take the official PECB Lead AI Risk Manager examination, covering:
- AI risk principles, concepts and regulations
- AI risk governance and management programmes
- AI risk identification and analysis
- AI risk evaluation, treatment and monitoring
- Organisational learning and continual improvement
Outcome: Successful participants demonstrate the competence required to lead AI risk management initiatives and earn the internationally recognised PECB Lead AI Risk Manager credential.
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