Stefano Bennati

AI Governance

AI Governance: Secure, privacy-preserving, ethical systems presents a structured playbook for safely harnessing the potential of Generative AI, including security and privacy, bias, ethics, cost management, and regulation. You’ll begin with a look at common deployment scenarios and consider how those choices affect control, accountability, and risk. Then, you’ll walk through a six-level generative AI governance framework that provides a reusable approach to setting policy, assessing risk, reviewing designs, testing before launch, monitoring live systems, learning from incidents, and other core production concerns.

Using real-world case studies, you’ll explore how hallucinations, bias, and prompt injection manifest and how to mitigate them, including handling new attack vectors like prompt- and data-poisoning. The result is a stable set of guardrails that help you manage what AI can say and do.