## Classify Data for AI Usage Eligibility

- Automatically assign AI usage labels like “safe,” “restricted,” or “prohibited” based on sensitivity, risk, and compliance rules.
- Customize label definitions to match internal policies and regulatory obligations.
- Enable consistent governance over what data can be used for prompts, copilots, and models.

## Label Structured & Unstructured Data Across the Enterprise

## Understand Data Sensitivity & Ownership Before Model Use

- Leverage identity-aware classification to map data to owners, sensitivity levels, residency, and consent.
- Build a richer picture of the data before it’s used in AI, and enforce labeling based on its true context.
- Align data use with governance from the start.

## Enforce Policy and Prevent AI Misuse at the Source

- Block restricted data from entering AI pipelines before it becomes a liability.
- Use label-driven policies to automate enforcement across data sources and toolchains.
- Minimize exposure by shifting control left — before models or copilots see the data.

### AI Usage Eligibility Enforcement

- Define and enforce what “safe for AI” really means inside your organization.
- Automatically label data based on risk, regulation, or business rules.
- Make it easy to distinguish what can or can’t be used in AI.

### Sensitive Data Protection in AI Pipelines

- Prevent personal, proprietary, or sensitive information from feeding AI models.
- Identify content that shouldn’t be used — and label it before it enters RAG workflows or prompts.
- Enforce compliance without slowing innovation.

### RAG & Copilot Governance

- Label and govern data that flows into retrieval-augmented generation pipelines or copilots.
- Apply proactive controls before suggestions are generated on top of restricted content.
- Reduce hallucinations and misuse from the source.

### Audit & Reporting for AI Compliance

- Track how labeled data is used, accessed, and shared across your environment.
- Prove AI usage aligns with policy and meets internal and external compliance mandates.
- Generate logs and reports with full label visibility.

### Cross-Team Collaboration & Transparency

- Give privacy, security, and AI teams a shared language for AI data use.
- Use a unified labeling taxonomy to reduce confusion and improve governance alignment.
- Drive faster decisions with clear classification.

### Unified Labeling & Remediation

- Integrate labeling into your broader data governance workflows.
- Take action on policy violations directly in BigID — from access restriction to user notifications.

Close the loop between visibility and enforcement.

## AI Labeling Isn’t Just Classification. It’s Risk Control.

BigID gives you the visibility, policy enforcement, and automation to govern AI data usage at scale — before it becomes a problem.