Data Governance

Data governance in the context of AI refers to the policies and controls that determine how organizational data interacts with AI systems. This includes:

• Classification: What data sensitivity levels exist, and which levels can be shared with which AI tools?
• Flow control: Tracking and controlling where data goes when employees use AI tools (prompts, file uploads, API calls)
• Retention: Understanding how AI vendors store and retain data submitted through their tools
• Training data: Whether vendor models are trained on customer data (opt-in vs. opt-out)
• Cross-border: Whether data sent to AI tools is processed or stored in jurisdictions that create compliance issues

AI complicates data governance because the data flow is often invisible — an employee pasting a financial report into ChatGPT creates a data transfer that traditional DLP tools may not catch.