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Artificial Intelligence

Lead AI Risk Manager

AI brings new categories of risk — bias, security exposure, opacity, and shifting regulation — that traditional risk programs weren't built for. This course gives risk and AI leaders a structured way to handle them: identifying, analyzing, evaluating, and treating AI risk, then monitoring and improving over time. It draws on recognized frameworks such as NIST and the EU AI Act so risk decisions stand up to governance and compliance scrutiny.

Lead5 daysVirtual & On-site31 CPD credits

Learning path options

Self Study

Self-paced online study, at your own pace

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In-Person Training

On-site delivery across Qatar and the GCC

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Live Online Training

Instructor-led and delivered live online

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Why attend

  • Get ahead of AI-specific risks — bias, security, opacity, and regulation
  • Prove you can identify, assess, and treat AI risk credibly
  • Align AI risk decisions with recognized frameworks and regulations
  • Bring structure and governance to ethical AI risk management

Who should attend

  • Professionals responsible for managing AI-related risk
  • IT and security professionals, data scientists, and AI developers
  • Consultants and legal or ethical advisors on AI risk and regulation
  • Managers and executives overseeing AI implementation

What you'll learn

  • Grasp the fundamentals, concepts, and techniques of AI risk management
  • Identify, analyze, evaluate, and treat AI risks — bias, security, transparency, and ethics
  • Build risk-mitigation strategies and incident-response measures
  • Apply AI risk frameworks such as NIST and the EU AI Act for governance and compliance

Our approach

  • Pairs the theory with real-world examples and scenario exercises
  • Includes interactive activities and multiple-choice quizzes
  • Encourages discussion and collaboration throughout
  • Mirrors the certification exam format

Prerequisites

A fundamental understanding of AI concepts and general risk-management principles; familiarity with frameworks such as NIST or the EU AI Act is helpful but not required.

Course agenda

Day 1Introduction to AI risk management
Day 2Organizational context, AI risk governance, and risk identification
Day 3Analyzing, evaluating, and treating AI risks
Day 4Monitoring, reporting, awareness, and improving risk performance
Day 5Certification exam

Examination

The exam spans five competency domains, from AI risk principles and governance through to evaluation, treatment, and performance improvement.

Certification

  • Leads to the PECB Certified Lead AI Risk Manager credential
  • Earned by passing the exam, signing the PECB Code of Ethics, and meeting the experience requirement for your tier
  • Includes one free exam retake within 12 months

Credential tiers

Provisional ManagerPass the exam — no experience required
AI Risk Manager2 years' experience (1 in AI risk) · 200 hours
Lead AI Risk Manager5 years' experience (2 in AI risk) · 300 hours
Senior Lead AI Risk Manager10 years' experience (7 in AI risk) · 1,000 hours

Build this capability across your teams.

DAI Consultancy delivers Lead AI Risk Manager as a corporate cohort — in-person, virtual, or hybrid — structured around your organization's objectives.