Building trust into the AI operating model
Operators need clear ownership for data, models and automated actions. They also need practical controls for privacy, bias, security, third-party models, incident response and continuing performance monitoring.
- Responsible AI governance
- Model and data risk
- AI security and adversarial threats
- Fraud and financial-crime detection
- Explainability and regulatory readiness
Balancing innovation and control
The summit will examine how leaders can create guardrails that enable deployment rather than slow it down. The emphasis is on governance that is proportionate to risk, connected to business ownership and measurable in day-to-day operations.