Certified Lead AI Risk Manager

This course equips professionals with the knowledge and tools to identify, assess, and mitigate AI-related risks within modern organisations. It explores the principles of AI governance, compliance, and ethics through globally recognised frameworks such as the NIST AI Risk Management Framework and the EU AI Act. Learners will gain hands-on experience applying these frameworks to real-world scenarios involving bias, security vulnerabilities, and transparency challenges. By the end of the course, participants will understand how to embed AI risk management within organisational strategy to ensure responsible, compliant, and ethical AI adoption.

By the end of this course, learners will be able to:

• Explain the key concepts and principles of AI risk management and governance
• Apply frameworks such as the NIST AI Risk Management Framework and the EU AI Act to evaluate compliance and ethical considerations
• Identify and assess AI risks, including bias, data security, transparency, and accountability concerns
• Develop and implement AI risk mitigation and incident response strategies
• Integrate AI risk management into wider business and compliance frameworks
• Analyse real-world case studies to identify lessons learned and best practices for AI risk control
• Promote responsible AI use across the organisation through governance and continual improvement

Participants should have:

• A foundational understanding of artificial intelligence concepts and data governance principles
• Basic knowledge of organisational risk management or information security practices
• Familiarity with compliance and governance structures within a business environment

Target audience

This course is designed for:

• Risk, compliance, and governance professionals managing AI-related initiatives
• IT and security specialists responsible for evaluating AI systems and controls
• Data scientists, AI developers, and engineers integrating responsible AI practices
• Consultants advising on AI risk management and mitigation strategies
• Legal, ethical, and compliance advisors specialising in AI regulations
• Business leaders and decision-makers responsible for strategic AI adoption

Introduction to AI risk management

• Understanding AI’s opportunities and challenges in modern organisations
• Key terms, definitions, and risk management concepts
• Overview of global AI risk management standards and regulations

AI risk identification, assessment, and measurement

• Techniques for identifying and classifying AI-related risks
• Quantitative and qualitative methods for risk assessment
• Assessing AI model reliability, data integrity, and ethical exposure

AI risk mitigation, governance, and incident response

• Designing mitigation strategies aligned with compliance frameworks
• Developing governance structures for ethical AI deployment
• Planning incident response and escalation procedures for AI failures or bias events

AI risk monitoring and continual improvement

• Establishing metrics and KPIs for AI risk performance
• Continuous evaluation of AI systems through audits and impact assessments
• Integrating lessons learned into organisational governance frameworks

AI risk management in business strategy

• Linking AI risk management with strategic planning and enterprise risk frameworks
• Ensuring accountability and ethical oversight in AI operations
• Building a culture of responsible and transparent AI innovation

Exams and assessments

Participants will complete a formal certification exam administered by PECB. Certification fees and the exam voucher are included in the course price. Candidates who do not pass on the first attempt may retake the exam once for free within 12 months of the initial attempt. Knowledge checks, exercises, and quizzes are provided throughout the course to reinforce learning and readiness for the certification exam.

Hands-on learning

This course includes:

• Practical exercises based on real-world AI risk scenarios
• Interactive group discussions and case-based simulations
• Workshops on developing and applying AI risk management frameworks
• Guidance from experienced instructors and access to over 450 pages of supporting materials