AI Risk Manager

The 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.

Why Should You Attend?

Artificial intelligence (AI) is transforming industries at an accelerated pace, driving innovation while simultaneously introducing new risks and challenges. As AI technologies advance, organizations must address critical concerns such as bias, security threats, transparency, and regulatory compliance. Managing these risks effectively requires a specialized approach that goes beyond traditional risk management frameworks. 

The PECB Certified AI Risk Manager certification validates your expertise in identifying, assessing, and mitigating AI-related risks while ensuring compliance with industry frameworks and regulations.

Upon passing the certification exam, participants can apply for the “PECB Certified AI Risk Manager” credential.

Who Should Attend?

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

Learning Objectives

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
• 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
• Identify and assess 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
• Integrate AI risk management into business strategy, ensuring AI initiatives align with organizational objectives while maintaining compliance with industry regulations
• Continually monitor, evaluate, and improve AI risk management processes to adapt to emerging risks and evolving AI technologies
• Advise key stakeholders on responsible AI adoption, providing guidance on ethical AI deployment, regulatory compliance, and best practices in AI risk governance

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.

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.