BigID Introduces Data Labeling for AI to Enhance Data Governance

BigID has launched a new feature called Data Labeling for AI, designed to help organizations classify and control data usage in AI models, announced in a press release. This capability allows security and governance teams to apply usage-based labels to data, ensuring that only appropriate data is used in generative AI models, copilots, and agentic AI systems.

The Data Labeling for AI feature offers a scalable, policy-driven approach to data classification, enabling organizations to use predefined labels such as "AI-approved," "restricted," or "prohibited," or to create custom labels that align with internal risk frameworks and regulatory requirements. This helps prevent sensitive or high-risk data from entering large language models (LLMs) and other AI workflows.

Supporting both structured and unstructured data across cloud, SaaS, and collaboration environments, the feature enforces usage policies early in the data pipeline. It combines deep classification, policy enforcement, and remediation workflows to provide actionable insights and control over data usage in AI systems.