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Important Notice: MyPECB Platform and New Website — With the launch of our new MyPECB Platform and Website, some users may experience temporary issues or disruptions while using the system. At the same time, our support teams are receiving an unusually high number of requests, which may affect response times. We want to assure you that we are actively working to resolve these issues and improve the platform. Your patience and understanding during this important transition are greatly appreciated.

Lead AI Risk Manager

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.

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 Lead 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 Lead 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
  • 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

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.

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

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.

After successfully completing the exam, you can apply for one of the credentials shown on the table below. You will receive a certificate once you fulfill all the requirements of the selected credential.

Credential Exam Professional experience Information Security Management experience Other requirements
PECB Certified AI Risk Provisional Manager PECB Certified Lead AI Risk Manager Exam, or equivalent None None Signing the PECB Code of Ethics
PECB Certified AI Risk Manager PECB Certified Lead AI Risk Manager Exam, or equivalent 2 years, of which at least 1 in AI risk management At least 200 hours of AI risk management activities Signing the PECB Code of Ethics
PECB Certified Lead AI Risk Manager PECB Certified Lead AI Risk Manager Exam, or equivalent 5 years, of which at least 2 in AI risk management At least 300 hours of AI risk management activities Signing the PECB Code of Ethics
PECB Certified Senior Lead AI Risk Manager PECB Certified Lead AI Risk Manager Exam, or equivalent 10 years, of which at least 7 in AI risk management At least 1000 hours of AI risk management activities Signing the PECB Code of Ethics

To be considered valid, AI risk management activities should follow best implementation and management practices and include the following:

  1. Determining the AI risk management objectives and scope
  2. Performing AI risk assessment
  3. Developing an AI risk management program
  4. Defining AI risk evaluation and risk acceptance criteria
  5. Evaluating risk treatment options for AI risks
  6. Monitoring and reviewing the AI risk management program

For more information about Lead AI Risk Manager certifications and the PECB Certification process, please refer to Certification Rules and Policies.

  • Certification fees are included in the exam price.
  • Participants will be provided with training course materials containing over 450 pages of information, practical examples, exercises, and quizzes.
  • An attestation of course completion worth 31 CPD (Continuing Professional Development) credits will be issued to the participants who have attended the training course.
  • Candidates who have completed the training course but failed the exam are eligible to retake it once for free within a 12-month period from the initial date of the exam.

For additional information, please contact us at marketing@pecb.com, or visit www.pecb.com.

Lead AI Risk Manager

Date:
03 Nov

Language:
English

Location:
Switzerland, LearnAnywhere ©️

Lead AI Risk Manager

Date:
01 Dec

Language:
English

Location:
Switzerland, LearnAnywhere ©️

Lead AI Risk Manager

Date:
02 Feb

Language:
English

Location:
Switzerland, LearnAnywhere ©️

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