BigID, the leading platform for data security, privacy, compliance, and AI governance, launched Shadow AI Discovery, a new capability that helps organizations uncover unauthorized AI models, surface high-risk datasets, and take direct action to reduce AI exposure across the enterprise.

Security teams are flying blind when it comes to AI, unable to track where models are deployed, what data they consume, or whether usage aligns with policy. Shadow AI introduces risks that traditional tools miss, leaving organizations exposed to data leakage, IP misuse, and regulatory violations.

Shadow AI Discovery automatically uncovers unmanaged models, flags personal or regulated training data, and maps out who's using what, where, and how. With integrations across model repositories, developer tools, cloud, and collaboration platforms, BigID gives teams a full view of their shadow AI footprint.

Shadow AI Discovery is built for action, not just visibility. Security and governance teams can trigger enforcement policies, restrict risky access, and launch remediation workflows directly within BigID. It's the control layer security teams have been missing to respond to shadow AI risk at scale.

Key Takeaways

• Discover unmanaged, rogue, and unauthorized AI models across your environment
• Detect and classify sensitive or regulated data used by AI systems
• Surface hidden AI activity across cloud, SaaS, developer tools, and collaboration platforms
• Correlate models to underlying data and enforce policy-based remediation
• Reduce exposure and improve AI security posture with actionable intelligence

"Security teams can't just find risky AI - they need to stop it," said Nimrod Vax, Chief Product Officer and Co-Founder at BigID. "Shadow AI Discovery gives organizations the end-to-end visibility and control they need to uncover hidden models, identify risky data use, and take action before it becomes a problem."