AI Risk Assessment and Model Governance Session

This session is designed for teams working on AI systems, machine learning models, GenAI tools, or internal AI deployments that need a sharper risk and control approach.

I advise on how to identify and assess AI risks across data, models, vendors, workflows, and operations. We can review model governance, AI impact assessments, quantitative risk methods, control frameworks, bias and fairness issues, adversarial threats, monitoring design, and residual risk decisions.

This is especially useful if you need help with:

• AI risk assessments
• Model governance
• AI security and adversarial risk
• Third-party AI vendor review
• Drift, monitoring, and validation plans
• Audit-ready documentation

Best for:

• Risk managers
• Data scientists
• AI product owners
• Security teams
• Internal audit and assurance teams