AI has transformed how organizations create, manage, and use data. GenAI tools, enterprise copilots, custom AI applications, and autonomous agents are now embedded in everyday work—helping teams move faster, automate workflows, and unlock more value from enterprise data.
But they also create new data security risks. AI tools can access, ingest, use, and expose sensitive information. Employees can paste confidential content into public or shadow GenAI tools. Overprivileged copilots can surface information users should not see. And AI agents can move data across connected systems with limited human supervision.
As AI adoption accelerates, security and governance must keep pace. Organizations need visibility into AI data use, stronger access controls, and a governance framework that makes AI safe to scale.
Securing and Governing Data for AI explains how to protect sensitive information in the age of AI.
In this guide, you’ll learn:
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How GenAI tools, enterprise copilots, custom AI applications, and AI agents can expose sensitive data
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Why shadow AI, overprivileged access, incomplete data discovery, and ungoverned AI training pipelines increase risk
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How weak AI security governance can turn everyday AI use into damaging data loss
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Which roles, policies, and technical controls help organizations govern AI use and protect sensitive information
Download the guide and start building a foundation for scaling AI securely.