Develop the expertise to identify, assess, and manage AI risks across the AI lifecycle.
AI introduces risks that extend beyond traditional technology and enterprise risk management, including bias, security vulnerabilities, transparency issues, regulatory exposure, and ethical concerns.
This programme provides a structured approach to AI risk governance, helping professionals assess AI-related threats, implement appropriate controls, and support responsible AI adoption.
- Why get trained: Learn to identify, assess, treat, and monitor AI risks using established frameworks, regulations, and practical risk scenarios
- Why it matters: Effective AI risk management strengthens governance, compliance, security, accountability, and responsible AI decision-making
- Who should attend: Risk, security, AI, compliance, governance, legal, and management professionals responsible for AI initiatives
Build the practical expertise to manage AI risks, strengthen governance, and support responsible AI adoption across your organization. HRD Corp Claimable

Overview
The Lead AI Risk Manager training course equips participants with the essential knowledge and skills to identify, assess, mitigate, and manage AI-related risks. Based on leading frameworks such as the NIST AI Risk Management Framework, the EU AI Act, and insights from the MIT AI Risk Repository, this course provides a structured approach to AI risk governance, regulatory compliance, and ethical risk management.
Participants will also analyze real-world AI risk scenarios from the MIT AI Risk Repository, gaining practical insights into AI risk challenges and effective mitigation strategies.
Educational Approach
- The training course combines theoretical knowledge with practical applications, using real-world examples to illustrate the identification and mitigation of AI risks.
- The course includes various interactive activities, such as scenario-based exercises and multiple-choice quizzes, designed to deepen understanding of AI risk management principles.
- Participants are encouraged to engage in discussions and collaborate during exercises and quizzes.
- The quizzes are structured similarly to the certification exam, helping participants familiarize themselves with the exam format and key concepts.
Skills Covered
Upon successfully completing the training course, participants will be able to:
- Understand AI risk management fundamentals, including key concepts, approaches, and techniques for identifying, assessing, and mitigating AI-related risks
- Identify, analyze, evaluate, and treat AI risks, such as bias, security vulnerabilities, transparency issues, and ethical concerns
- Develop and implement risk mitigation strategies and incident response measures to address AI-related threats and vulnerabilities
- Apply established AI risk management frameworks, such as the NIST AI Risk Management Framework and the EU AI Act, to ensure governance, compliance, and ethical AI use
Prerequisites
The main requirements for participating in this training course are having a fundamental understanding of AI 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 beneficial but not mandatory.
Target Audience
This training course is intended for:
- Professionals responsible for identifying, assessing, and managing AI-related risks within their organizations
- IT and security professionals seeking expertise in AI risk management
- Data scientists, data engineers, and AI developers working on AI system design, deployment, and maintenance
- Consultants advising organizations on AI risk management and mitigation strategies
- Legal and ethical advisors specializing in AI regulations, compliance, and societal impacts
- Managers and leaders overseeing AI implementation projects and ensuring responsible AI adoption
- Executives and decision-makers aiming to understand and address AI-related risks at a strategic level

- Day 1: Introduction to AI risk management
- Day 2: Organizational context, AI risk governance, and AI risk identification
- Day 3: Analysis, evaluation, and treatment of AI risks
- Day 4: AI risk monitoring and reporting, training and awareness, and optimizing AI risk performance
- Day 5: Certification exam

Exam & Certification
The “PECB Certified Lead AI Risk Manager” exam meets all the requirements of the PECB Examination and Certification Program (ECP). It covers the following competency domains:
- Domain 1: AI risk principles, concepts, and regulations
- Domain 2: AI risk management program and governance
- Domain 3: AI risk identification and analysis
- Domain 4: AI risk evaluation, treatment, and monitoring
- Domain 5: Organizational learning and performance improvement
For specific information about the exam type, languages available, and other details, please visit the List of PECB Exams and Exam Rules and Policies.
Training & Certification Guide
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