Whitepaper (PDF)

IDC Spotlight: Rethinking Data Security and Insider Risk for Trusted AI Adoption

Nearly half of all organizational data is sensitive or confidential, yet most organizations lack the visibility to adequately protect it. As AI becomes embedded in enterprise workflows, data volume and sprawl create compounding risks: from insider threats and compliance violations to poor AI outputs that erode stakeholder trust. A data-centric security approach using unified discovery, classification, DSPM, and DLP gives organizations the context they need to secure data without slowing AI adoption.

‍Key Takeaways:

  • Data sprawl is the root of AI-era security risk
  • Unified visibility is what separates reactive from proactive security
  • Trusted AI outcomes require trusted data foundations

Explore our spotlight paper, created in partnership with IDC, to understand why a data-centric security model is paramount in the AI era. 

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