Why AI risk management is a critical competence
AI systems introduce a new category of risks that traditional risk frameworks were not designed to handle. A hallucinating chatbot can give dangerous medical advice. A biased model can discriminate in hiring. A poorly secured AI pipeline can leak training data.
I train your teams on the full AI risk lifecycle: identification (what can go wrong), assessment (how likely and how severe), mitigation (technical and organisational controls) and monitoring (ongoing vigilance in production). We use the NIST AI Risk Management Framework as the baseline, adapted to Swiss regulations and your sector.
For FINMA-supervised institutions, I specifically address the regulator's emerging expectations around AI model risk management.
AI risk is not hypothetical — it is happening now: the question is whether you are managing it proactively.