This Lead AI Risk Manager training prepares professionals to design, operate, and defend an AI risk management program aligned with regulatory and governance expectations. The course focuses on practical risk identification, decision traceability, and defensible mitigation strategies across the AI lifecycle. Participants work with concrete scenarios reflecting the EU AI Act, NIST AI RMF, and enterprise governance realities. Delivered by practitioners actively advising organizations on AI governance, this training supports both PECB certification success and real-world AI risk accountability at operational and executive levels.
Upcoming dates you can join soon.
This course runs multiple times per year, onsite and online.
Understand AI risk management fundamentals and key techniques
Apply established frameworks to support governance and compliance
Identify and assess common AI risks (bias, security, transparency, ethics)
Develop mitigation strategies and incident response measures
Integrate AI risk management into business strategy and performance improvement
“Henri perfectly filled in the gaps in our knowledge and tailored the course contents to our difficult schedules, many thanks !”
Simon Baynes
BCMS manager
MSC MEDITERRANEAN SHIPPING COMPANY SA
“Henri and Alexis conducted a focused, intensive four-day ISO/IEC 27001 Lead Implementer Course of immediate relevance to The Global Fund. Participants representing both IT and Risk are now better prepared to design and operationise a corporate ISMS.”
Andreas Tamberg
Senior advisors enterprise risk management
The Global Fund
“Overall enjoyable training. To the point end trainer kept clear focused.”
Stephane Di Bari
Service operations manager
UNICC
Get instant answers to common questions about this course from our expert trainers.
AI risk management is the structured way to identify, assess, treat, and monitor AI risks—such as bias, security threats, transparency gaps, and compliance exposure—through governance, controls, and evidence.
“AI risk management makes AI governance operational.”
Expert Trainer
They provide recognized structures for governing AI risk, defining controls, and demonstrating compliance and ethical AI use in organizational settings.
“Frameworks turn principles into repeatable controls and evidence.”
Expert Trainer
Day 1 covers AI risk fundamentals; Day 2 covers context, governance, and risk identification; Day 3 covers analysis, evaluation, and treatment; Day 4 covers monitoring, reporting, awareness, and continual improvement.
“The course follows a full risk lifecycle: identify, treat, monitor, improve.”
Expert Trainer
The exam is domain-based, covering AI risk concepts and regulations, governance, identification and analysis, evaluation/treatment/monitoring, and organizational learning and performance improvement.
“The exam tests both governance design and practical risk handling.”
Expert Trainer
It's designed for risk owners, IT/security teams, data and AI engineers, consultants, legal/ethical advisors, leaders overseeing AI deployments, and executives needing strategic oversight of AI risk.
“Best results come when technical and governance stakeholders learn together.”
Expert Trainer
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