AI adoption is accelerating, but AI systems introduce risks that traditional IT and cybersecurity programs do not fully address: bias, drift, adversarial manipulation, model theft, limited transparency, and exposure from deployment choices.
Course 2079, AI Risk Management: Implementing the NIST AI RMF in Practice, gives security, risk, and governance professionals a practical approach to applying the NIST AI Risk Management Framework in enterprise environments. The course connects AI RMF with ISO/IEC 42001 and NIST SP 800-37 to support inventories, risk classification, controls, approvals, and audit-ready governance.
In this 60-minute webinar, we will overview the AI risk landscape, explain how AI RMF can be operationalized, and discuss risks such as bias, explainability, model drift, poisoning, evasion, model extraction, inference risk, and AI supply chain exposure.
We will also preview how Course 2079, AI Risk Management: Implementing the NIST AI RMF helps teams implement controls, produce evidence, monitor AI systems in production, and build a sustainable AI risk management program.
[Webinar 5391]
Submit the form below to register for the webinar.
Christian Owens
Christian Owens is a cybersecurity engineer and governance, risk, and compliance (GRC) professional with extensive experience securing enterprise environments and advising organizations on risk mitigation strategies. He specializes in bridging technical security controls with governance frameworks and emerging technologies, including AI-enabled systems.
Christian brings a practical, real-world perspective to AI security and is passionate about helping professionals build the skills needed to secure next-generation technologies.
Managing AI Risk with NIST AI RMF Webinar FAQs
- Cybersecurity professionals responsible for AI-enabled systems
- GRC, risk management, compliance, and audit professionals
- Security analysts, engineers, and architects supporting enterprise AI adoption
- IT leaders overseeing AI governance and approval workflows
- AI/ML practitioners who need risk and control context
- Organizations building audit-ready AI risk management programs
• Understand how AI risk differs from traditional software and cybersecurity risk
• Learn how the NIST AI RMF applies to real-world AI systems
• See how AI RMF aligns with ISO/IEC 42001 and NIST SP 800-37
• Identify risks such as bias, drift, adversarial manipulation, model theft, and limited transparency
• Explore controls for validation, monitoring, audit evidence, and lifecycle management
Check out the following:
- CompTIA SecAI+ Certification (Course 2078)
- AI and Cyber Security: Attack and Defend (Course 1216)