Trust But Verify Your AI

Enterprises increasingly rely on AI systems built internally, sourced from open-source communities, and delivered through third-party vendors. This webinar examines the security risks across the AI supply chain and explains why organizations need independent verification of the AI and machine learning components running in their environments.

The session explores how to secure AI across three areas: purchased services, internally built models, and production deployments. Topics include gaining visibility into external AI services using SaaSBOM, generating a Machine Learning Bill of Materials to inventory open-source models, and protecting GenAI applications and RAG pipelines from prompt injection and data poisoning. The discussion focuses on improving transparency, strengthening controls, and supporting compliance with emerging regulations such as the EU AI Act.