Lead AI Risk Manager

The goal is to reduce potential negative consequences while maximizing AI’s benefits, ensuring that AI systems remain secure, ethical, and aligned with regulatory standards.

Unlike traditional risk management methods that often rely on historical data and manual analysis, AI-driven risk management can adapt dynamically in real time, using advanced tools such as machine learning and data analytics. This approach helps organizations identify, assess, and address risks efficiently and accurately.

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.

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Who Should Attend?

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This training course is intended for:

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Professionals responsible for identifying, assessing, and managing AI-related risks within their organizations

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IT and security professionals seeking expertise in AI risk management

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Data scientists, data engineers, and AI developers working on AI system design, deployment, and maintenance

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Consultants advising organizations on AI risk management and mitigation strategies

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Legal and ethical advisors specializing in AI regulations, compliance, and societal impacts

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Managers and leaders overseeing AI implementation projects and ensuring responsible AI adoption

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Executives and decision-makers aiming to understand and address AI-related risks at a strategic level

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Learning objectives

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Upon successfully completing the training course, participants will be able to:

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Understand AI risk management fundamentals, including key concepts, approaches, and techniques for identifying, assessing, and mitigating AI-related risks

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Identify, analyze, evaluate, and treat AI risks, such as bias, security vulnerabilities, transparency issues, and ethical concerns

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Develop and implement risk mitigation strategies and incident response measures to address AI-related threats and vulnerabilities

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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

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Educational approach

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The training course combines theoretical knowledge with practical applications, using real-world examples to illustrate the identification and mitigation of AI risks.

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The course includes various interactive activities, such as scenario-based exercises and multiple-choice quizzes, designed to deepen understanding of AI risk management principles.

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Participants are encouraged to engage in discussions and collaborate during exercises and quizzes.

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The quizzes are structured similarly to the certification exam, helping participants familiarize themselves with the exam format and key concepts.

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Course Contents

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Day 1: Introduction to AI risk management

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Day 2: Organizational context, AI risk governance, and AI risk identification

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Day 3: Analysis, evaluation, and treatment of AI risks

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Day 4: AI risk monitoring and reporting, training and awareness, and optimizing AI risk performance

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Day 5: Certification exam