Enterprise AI Security and Governance Summit 2026

AI governance has focused on making models explainable, fair, documented, and compliant. This approach implies the model is responsible for decision-making, rather than the organization.

Poor outcomes rarely result solely from the model. They typically arise from how people design, deploy and use these models. Decision thresholds, business rules, operational constraints and human judgment all influence results. While these challenges are not new, AI accelerates decision-making and broadens implementation, making them more visible.

This session explores why effective AI governance should begin with the decisions organizations aim to make, not just the technology involved. Using practical examples from regulated industries, we’ll discuss how governance can go beyond compliance to enhance accountability, reduce risk and support confident decision-making.

Join Gael Decoudu, Credit and AI Leader in Financial Services, to learn why trustworthy AI requires governance over both models and decision-making.

Key Takeaways
- Why good governance is about decisions, not just technology.
- Where governance really breaks down in day-to-day operations.
- How business rules, human judgment and AI work together.
- Practical ways to strengthen accountability without slowing innovation.
- A simple way to think about governance that delivers better business outcomes.