PECB Certified Lead AI Risk Manager

During this PECB Lead AI Risk Manager course, you’ll gain the necessary skills to establish, manage, and oversee artificial intelligence (AI) risk management frameworks based on industry best practices and emerging standards. It provides you with the knowledge and expertise required to identify, assess, and mitigate risks associated with AI systems, ensuring they are implemented responsibly, ethically, and aligned with organisational objectives.

Led by expert PECB-certified instructors, this course delivers a comprehensive, hands-on approach to AI risk management. You’ll cover the knowledge and skills needed to design, implement, and manage AI risk processes in alignment with frameworks such as ISO/IEC 23894 and related governance and risk management guidelines. Through engaging discussions, practical exercises, and interactive learning, you will develop a deep understanding of AI risk concepts while strengthening your ability to manage risks across the AI lifecycle.

Earning the PECB Lead AI Risk Manager certification validates your ability to lead and manage AI risk initiatives, helping organisations ensure trustworthy AI adoption, maintain compliance, and support strategic decision-making in an increasingly AI-driven environment.

Throughout this course, you'll learn 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

With Firebrand’s Lecture | Lab | Review method, you’ll certify while gaining access to official courseware, expert instruction, and an immersive, distraction-free learning environment.

As part of the course, you’ll take the PECB Lead AI Risk Manager exam, backed by our Certification Guarantee for added confidence. Additionally, upon certification, you’ll earn a digital badge, enhancing your professional credibility in AI Risk Management.

• Training course objectives and structure
• International AI standards and frameworks
• Overview of AI laws and regulations worldwide
• Understanding risks, impacts, and harms
• AI life cycle
• AI risk management program
• Organisational context and AI risk governance
• AI risk mapping and identification
• AI risk analysis
• AI risk evaluation and prioritisation
• AI risk treatment
• AI risk monitoring and reporting
• Training and awareness
• Optimising and evaluating AI risk performance
• Closing of the training course

To participate in this accelerated course, you should have 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.

At the end of this course, you’ll sit the PECB Certified Lead AI Risk Manager examination, covered by the Firebrand Certification Guarantee.

• Duration: 180 minutes (3 hours)
• Format: Multiple-choice questions, open book
• Number of questions: 80
• Pass score: 70%
• CPD points available: 31 CPD points available upon completion
• Digital Badge: PECB have partnered with Credly to offer you the chance to earn a digital badge upon completing your certification.

After successfully completing the exam, you can apply for your credential. You will receive a designation once you meet the requirements related to the specified credential.

Competency domains covered during the examination include:

• 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