Fasoo AI, a leader in data-centric security and AI-ready data management, today announced its participation in the Gartner Security & Risk Management Summit 2026, where it will demonstrate its data-centric AI security platform and present a session on managing AI-driven data loss risks.
“As enterprises operationalize AI, data governance must evolve from static protection to continuous risk management,” said Jason Sohn, Executive Managing Director at Fasoo AI. “Organizations need a holistic framework that classifies, tags, monitors, and controls sensitive data throughout AI workflows to reduce exposure risks and ensure trusted AI operations.”
Fasoo AI will lead a speaking session titled “Managing AI-Driven Data Loss: Where It Happens, When It Matters, and How to Control It,” presented by Ron Arden, EVP, CTO & COO at Fasoo AI. The session will take place on June 1 at 3:15 PM in Potomac D. It will address how AI adoption is outpacing traditional data protection frameworks, introducing new risks across generative AI platforms, copilots, and shadow AI usage. Attendees will gain a practical framework to:
• Identify where sensitive data is exposed across AI workflows
• Understand when and how data loss risks emerge
• Implement scalable and enforceable controls aligned with business priorities
• Define AI risk appetite and operationalize AI-aware data loss prevention (DLP)
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By focusing on real-world use cases, the session will provide actionable insights for security leaders seeking to enable AI innovation without compromising data protection.
At Booth #329, Fasoo AI will highlight how organizations can secure sensitive data across generative AI, copilots, and evolving digital workflows by embedding persistent protection and governance directly into the data itself. As enterprises accelerate AI adoption, traditional security controls are increasingly challenged by how data flows into and through AI systems, requiring a shift toward data-centric security architectures.
Key components of Fasoo AI’s data-centric approach include:
• Data Discovery and Classification Before AI Ingestion: Gain visibility into sensitive data across structured and unstructured environments and enforce classification policies before data enters AI systems, ensuring only authorized and properly governed data is used for AI training and inference.
• AI-Ready Content with Version Integrity: Establish a trusted data foundation by maintaining persistent identifiers, version history, and content integrity, enabling AI systems to reference only the most up-to-date, approved, and contextually accurate information.
• Persistent ACL Enforcement at AI Output: Apply dynamic, file-level encryption and granular access controls at the point of AI output, ensuring generated content is filtered and governed in real time based on user roles, permissions, and security policies.
Security and risk leaders can explore how Fasoo AI enables a more controlled and scalable approach to AI adoption, aligning data protection with evolving governance and compliance requirements. By embedding visibility, classification, and policy enforcement directly into the data layer, organizations can better manage AI-driven risks while maintaining the flexibility needed to support innovation and business growth.
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