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AI Risk Manager: manage artificial intelligence risks
Your AI projects carry risks that a technical assessment alone cannot cover. Structure risk identification, assessment and monitoring to inform decisions. Strengthen your ability to connect expected performance, impacts and control measures.
- Duration
- 4.5 days 31 hours
- Code
- GSI002FR Code
- Certification
- PECB Certified AI Risk Manager Certification
Accredited training for the PECB Certified AI Risk Manager certification.
Presentation
Artificial intelligence accelerates innovation but introduces new risks: discriminatory bias, adversarial attacks and changing regulatory requirements. This 4.5-day PECB Certified AI Risk Manager course develops you into a specialist able to identify, quantify and reduce these threats while preserving the business value of your AI projects.
Based on proven AI risk management frameworks such as the NIST AI Risk Management Framework and European AI regulation, this course combines theory, case studies and practical exercises. You will assess model robustness, develop mitigation plans, test incident scenarios and write compliance reports required by regulators. These tasks use industry-standard tools (MLSecOps, explainability dashboards, model registries, etc.).
After completing this PECB programme, you will be able to manage the AI risk lifecycle, ensure regulatory compliance and make informed decisions to continually improve security measures. This programme also prepares you for and enables you to take the certification exam for PECB Certified AI Risk Manager (find out more in the Certification tab).
Objectives
By the end of this PECB AI Risk Manager course, you will be able to:
- understand AI risk management fundamentals, including identification and mitigation concepts and techniques;
- apply established AI risk management frameworks such as the NIST AI Risk Management Framework and the EU AI Act;
- identify and assess AI risks such as bias, security vulnerabilities and transparency issues;
- develop and implement risk mitigation strategies and incident response measures;
- integrate AI risk management into your business strategy;
- prepare effectively for the PECB Certified AI Risk Manager certification exam.
Program
Day 1: understand AI risk management fundamentals and challenges
- Fundamental principles and key concepts of risk management.
- AI risks (bias, vulnerabilities, ethical and transparency issues).
Case study
- Analyse examples of AI-related incidents.
Day 2: identify, assess and mitigate AI risks
- Risk identification and assessment methods.
- Applying established risk management frameworks (NIST, EU AI Act).
- Implementing mitigation and AI governance strategies.
Practical exercise
- Create a risk matrix for an AI use case.
Day 3: implement incident response
- Establishing incident response measures.
- Developing an AI security incident response plan.
Case study
- Develop an incident response plan.
Day 4: monitor AI risks and continually improve risk management
- Strategies for monitoring AI risks and continually improving risk management.
Practical exercise
- Implement a risk monitoring plan.
Final half-day: prepare for PECB AI Risk Manager certification
- Introduction to the exam structure and format.
- Tips and guidance for passing the PECB AI Risk Manager exam.
Audience
This course is intended for anyone wishing to master AI risk management, including:
- Professionals responsible for identifying, assessing and managing AI risks within their organisation.
- IT and security professionals seeking to specialise in AI risk management.
- Data scientists and engineers, and AI developers working on AI system design and deployment.
- Consultants advising organisations on AI risk management strategies.
- Managers and leaders overseeing AI implementation projects and ensuring responsible adoption.
- Executives and decision-makers seeking to understand and manage AI risks at a strategic level.
Prerequisites
This PECB course requires the following prerequisites:
- Fundamental cybersecurity knowledge: a good understanding of basic cybersecurity principles (threat, vulnerability, risk) and main attack types (malware, phishing, denial of service).
- Proficiency in incident response basics: familiarity with the incident lifecycle (preparation, detection, containment, eradication, recovery, lessons learned) and at least some practical experience managing an alert ticket or participating in an exercise.
- Professional experience: to obtain PECB AI Risk Manager certification, you need 2 years of experience, including at least 1 year in AI risk management and 200 hours of activities.
- Good command of English: course materials and the certification exam are currently available in English only.
Teaching and assessment methods
- Initial skills assessment
- Training materials provided to participants
- Continuous assessment throughout the course
- End-of-course feedback questionnaire
- Combination of theory and practical application
- Attendance records
- Post-course follow-up evaluation
- Practical exercises
- Case study
Course highlights
- PECB certification included: this course specifically prepares you for the PECB Certified AI Risk Manager exam. Your course fee includes examination and certification fees.
- Certified instructor expertise: your instructor is an AI risk management expert, combining theory, anecdotes and tips from projects they have personally led to make each concept immediately applicable.
- Professional development credits: participation entitles you to 31 continuing professional development credits (CPD/CPE), helping you keep your skills and certifications up to date.
- A second exam opportunity: if needed, you can retake the exam once free of charge within 12 months of the initial exam date.
Dates and sessions
Choose the date and delivery format that suit you.
No upcoming sessions are currently available.
Training content provided in partnership with PECB