AI promises unprecedented opportunities for efficiency, innovation, and growth—but it also brings new risks, from data misuse to opaque decision-making and potentially harmful or risky output. As AI initiatives multiply, governance committees face the constant challenge of deciding where to focus their time. Every project – whether built internally, purchased, or hybrid – needs to be visible from the earliest stages of ideation. 

Effective governance requires rapid risk evaluations, visibility into relationships between data, models, and outputs, and aggregated insights to surface potential policy violations. It also requires strong data use governance to proactively identify sensitive data, align controls with regulatory frameworks, and enforce policies programmatically. 

In this demo, we’ll highlight how automated data policy enforcement turns governance decisions into instant, technical action. Sensitive data is automatically identified, classified, and remediated with targeted controls such as column masking and row filtering. These controls can be layered, enforced in real time, and consistently applied across cloud platforms, making data both protected and ready for AI at scale. 

Website: https://www.onetrust.com/