As AI models become integral to business operations, ensuring their reliability, fairness, and compliance is essential. This session explores best practices for managing model risks, minimizing failures, and embedding governance to drive responsible AI innovation.

-           Establishing a comprehensive model governance framework to monitor performance, bias, and ethical compliance effectively.

-           Conducting rigorous risk assessments, stress-testing models under diverse scenarios to identify vulnerabilities.

-           Implementing continuous validation protocols to ensure alignment with evolving regulations and organizational goals.