Lead AI Risk Manager
The Lead AI Risk Manager training course enables you to structure and manage an artificial intelligence risk management program, from risk identification (bias, security, ethics, robustness) through to monitoring, reporting, and continuous improvement. It draws on recognized frameworks such as the NIST AI Risk Management Framework (AI RMF) and the requirements of the European AI Regulation (AI Act) to align your practices with concrete governance and compliance standards.
1. Why should you participate ?
AI introduces specific risks (model drift, bias, lack of transparency, vulnerabilities, non-compliance, and impacts on fundamental rights). At the same time, the AI Act is being rolled out gradually, with phased implementation and obligations that are becoming increasingly stringent.
The training helps you to :
- Establish AI risk governance (roles, responsibilities, policies, controls)
- Structure the risk analysis according to a clear framework (mapping, measurement, treatment, monitoring) based on the NIST AI RMF
- Reduce the risk of bias, lack of transparency, and misuse, while establishing clear requirements for documentation and traceability
- Supporting compliance (AI Act: categorization, obligations, evidence, oversight, monitoring)
- Boost the credibility of your expertise with PECB certification
2. Who is this training intended for ?
The training helps you to :
- Managers in charge of AI projects
- Legal professionals and AI regulatory advisors
- AI Compliance and Ethics Consultants
- Engineers, data scientists, and AI developers
- Professionals responsible for AI risk management
3. Learning objectives
Upon completion of the training, you will be able to :
- Identify, analyze, and assess AI risks (bias, security, ethics)
- Develop strategies for mitigating and responding to AI incidents
- Establish processes for monitoring and reporting AI risks
- Understanding the fundamentals of AI risk management
- Apply frameworks such as the NIST AI RMF and the AI Act to structure AI governance
4. Educational approach
The training combines :
- Structured theoretical content
- Real-world case studies from the MIT AI Risk Repository
- Interactive exercises and practical applications
- Discussions among participants and the application of principles to real-world scenarios
5. Are there any prerequisites ?
The main requirements for participating in this training are a basic understanding of AI-related concepts and a general knowledge of risk management principles. Familiarity with AI governance frameworks, such as the NIST AI Risk Management Framework or the EU AI Act, is a plus but not required.
6. Training program
The training takes place over 4 days :
1° First day
Introduction to AI Risk Management and Theoretical Frameworks
2° Second day
AI Governance, Risk Identification, and Organizational Context
3° Third day
AI Risk Analysis, Assessment, and Management
4° Fourth day
Monitoring, awareness-raising, training, and continuous improvement regarding AI risks
7. PECB Certification exam
The exam lasts 3 hours and covers the following areas :
- Principles and Concepts of AI Risk Management
- Governance, Frameworks, and AI Compliance
- Identification, Assessment, and Measurement of AI Risks
- Risk Management, AI Incident Response
- Monitoring, reporting, and continuous improvement of AI risks
8. Additional training
To strengthen your expertise :
9. FAQ
1) Does this training cover the NIST AI RMF ?
Yes, the training program is based on the NIST AI RMF and its four-function framework (Govern, Map, Measure, Manage) to structure an AI risk management program.
2) Is this helpful in preparing for compliance with the AI Act ?
Yes : The training helps organize governance, documentation, monitoring, and reporting in line with the requirements that are being phased in over time.
3) Which PECB courses should you take to build a career path as an “AI Manager” ?
A suitable career path (depending on your level and role) might include :
- ISO/IEC 42001 Lead Implementer : to establish and manage an AI management system (AIMS)
- ISO/IEC 42001 Lead Auditor : to audit AI governance and verify system compliance
- Lead AI Risk Manager : to structure the identification, assessment, treatment, and monitoring of AI risks, in line with regulatory requirements (e.g., AI Act) and reference frameworks (e.g., NIST AI RMF)
4) What career paths are available after earning a Lead AI Risk Manager certification ? (roles & opportunities)
This certification can support a career transition into roles such as: AI Risk Manager, AI Governance Manager, Responsible AI / AI Compliance Manager, Risk & Compliance (AI), or GRC with an AI focus. In terms of market trends, the World Economic Forum reports that 86% of employers expect AI and information processing technologies to transform their businesses by 2030, which automatically boosts demand for professionals capable of managing risk, governance, and compliance.
5) Is this training course suitable if I need to lead AI projects involving multiple stakeholders (IT, business, legal, compliance) ?
Yes. It emphasizes governance and coordination including roles and responsibilities, committees, validation rules, documentation, reporting, and decision-making to ensure alignment among technical, business, and compliance teams.
10. Conclusion
The Lead AI Risk Manager training course provides you with a clear methodology for anticipating, defining, and managing AI-related risks by aligning governance, control, and compliance. It is a key step toward deploying responsible, robust, and traceable AI, with recognition through PECB certification.