AI systems move fast, often faster than the governance processes meant to keep them in check. Before a model touches customer data, shapes a recommendation, or automates a decision, your organization needs a clear picture of how it could affect individuals, what regulatory obligations it triggers, and where the business risk sits. That’s what an AI risk assessment is for: a structured way to surface those risks before launch, not after something goes wrong.
This guide walks through the key questions privacy, legal, and compliance teams should ask when assessing an AI system, from data inputs and model behavior to downstream decisions and human oversight. It’s built to help you document risks, controls, and accountability in a way that holds up to scrutiny, whether that’s an internal review or a regulator’s. To run AI risk assessments consistently across every system and team, see how TrustArc’s AI governance software brings this process into one workflow.
What you’ll learn:
- Identify the core questions to ask before any AI system goes live, covering data use, model behavior, and human oversight
- Document risks, controls, and accountability in a way that’s audit-ready
- Apply a consistent assessment process as you scale AI across teams and systems
