The GenAI Risk Landscape: Identification and Management of Evolving Risks
Session 1/3 of the AI webinar series.
Tom Callaghan and Christophe Forêt explore GenAI landscape risk and security teams, and business leaders with a better understanding of how to identify, assess, and mitigate AI-related cyber risks. They explore real-world incidents, emerging AI threat vectors, evolving regulatory landscapes, and best practices for AI risk management.
AI adoption is accelerating across enterprises, driving innovation, efficiency, and new business opportunities.
However, it also introduces a complex and evolving risk landscape that security leaders must navigate.
From identifying evolving external threats to the challenges of deploying AI tools, businesses need a clear understanding of the risks involved and the best practices for managing them effectively.
This webinar hosted by C-Risk co-founders Tom Callaghan and Christophe Forêt explore GenAI landscape risk and security teams, and business leaders with a better understanding of how to identify, assess, and mitigate AI-related cyber risks. They explore real-world incidents, emerging AI threat vectors, evolving regulatory landscapes, and best practices for AI risk management.
- How AI changes the external and internal risk landscape
- Case studies on AI-driven cyber threats, including deepfakes and fraudulent activity
- The role of governance in securing AI models and data
- Emerging AI regulations and their impact on risk assessments
- Practical steps for organizations to start their AI risk management journey
Now is the time to build your organization's AI risk management capabilities.
Register now and watch the replay.
Check out our AI Risk Assessments use case to learn more about how we assess AI risks with data-driven FAIR™ frameworks to identify threats, quantify impacts, and develop mitigation strategies that safeguard your business and users.