As AI becomes more embedded in business operations, ensuring security at every level—from data and models to governance and oversight—is critical. Organizations must address vulnerabilities in AI systems, manage third-party risks, and implement strong governance to maintain trust and compliance.

During this in-depth webinar we explored:

• Data Security: Best practices for protecting AI training data, outputs, and sensitive information

• Model Security, Integrity & Authenticity: Safeguarding AI systems from adversarial attacks, manipulation, and unauthorized access

• Security of Third-Party Models & APIs: Assessing risks in open-source AI and third-party integrations

• Information Security Threats: Identifying and mitigating cybersecurity risks targeting AI-driven applications

• Access Control: Implementing user authentication, permission management, and least-privilege access strategies 

• Governance & Audit: Establishing policies to track AI decision-making, ensure compliance, and mitigate liability

• Human Oversight: Balancing automation with human intervention to prevent errors and biases

• Monitoring & Measuring AI Systems: Ongoing evaluation of AI performance, security, and compliance risks

• Incident Response & Recovery: Preparing for AI-related security breaches and ensuring rapid response

This session was designed for security professionals, legal teams, compliance officers, and AI practitioners looking to build resilient, secure, and compliant AI systems.