BigID, a frontrunner in data security, compliance, privacy, and AI governance, has introduced its latest feature: Data Labeling for AI. This new solution empowers organizations to identify and manage the data eligible for use in generative AI systems, such as copilots and autonomous AI agents. By assigning labels based on usage policies, security and governance teams can now control data flow into AI models, helping mitigate potential risks tied to data misuse, exposure, or regulatory non-compliance.

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One of the most pressing questions facing data and security teams is: “Is this data suitable for AI use?” BigID addresses this concern with a scalable, rules-based framework for tagging and classifying data for AI applications. Businesses can deploy built-in labels like “AI-approved,” “restricted,” or “prohibited,” or design their own labels aligned with internal governance standards and compliance mandates.

This labeling functionality supports both structured and unstructured data across multiple environments, including cloud platforms, SaaS tools, and collaborative ecosystems. By embedding labeling practices early in the data pipeline, BigID ensures organizations can proactively restrict sensitive data from being exposed to AI systems. The platform integrates advanced data classification, policy application, and remediation workflows, turning visibility into actionable control.

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Highlights of the New Capability:

  • Automatically categorize data as safe, restricted, or not permitted for AI applications
  • Create tailored labeling systems to reflect organizational policy and regulatory frameworks
  • Prevent exposure of confidential or sensitive information in LLMs, copilots, and retrieval-augmented generation (RAG) setups
  • Apply AI usage labels consistently across all data formats and platforms

“Security professionals need the ability to manage what data is introduced to AI before issues arise,” said Dimitri Sirota, BigID’s CEO and Co-Founder. “Our Safe-for-AI labeling capability enables organizations to assign the appropriate labels, implement relevant policies, and take decisive actions to protect both their data and AI initiatives.”

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Source: prnewswire