How to approach AI Risk, when your chosen framework or set of standards fall short

Join us to discuss how to approach AI Risk, when your chosen framework or set of standards fall short.

• Why Traditional Frameworks Don't Fully Address AI Risk.
  
  • Understanding where existing cyber security, privacy, and risk management frameworks provide coverage and where significant gaps remain.
• Identifying and Assessing AI-Specific Risks.
  
  • Exploring risks such as model misuse, prompt injection, data leakage, hallucinations, bias, autonomy, and third-party AI dependencies.
• Building Practical AI Governance Beyond Compliance.
  
  • Establishing policies, ownership, risk assessment processes, and decision-making structures that support the safe adoption of AI.
• Managing AI Risk Across the Organisation.
  
  • Addressing both sanctioned and unsanctioned AI use, shadow AI, supplier-provided AI capabilities, and AI embedded within existing business applications.
• Developing an AI Risk Framework That Evolves with the Technology.
  
  • Creating a pragmatic approach that can adapt to rapidly changing AI capabilities, regulatory expectations, and emerging threats.

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