// enterprise security

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theme-ai AI & ML enterprise security contextual understanding

Sep 1

AI Rewrites Data Loss Prevention as Context Replaces Rules

Security vendors are replacing DLP's decades-old signature-matching approach with large language models that understand intent and context. The shift addresses the core problem that made rule-based DLP a productivity tax: it couldn't distinguish between a legitimate research file shared with a partner and actual intellectual property theft. LLM-based DLP can make that distinction. Incumbents with existing customer relationships (Forcepoint, Symantec, Proofpoint) and well-funded generalists (Microsoft, Google) have structural advantages over pure-play DLP startups from the previous cycle.

theme-ai ai safety ai alignment enterprise security

Aug 7

Enterprise security teams unprepared for autonomous AI threats

Source: SiliconANGLE

Agentic AI systems—software that operates independently to complete complex tasks—are breaching corporate defenses faster than security teams can develop countermeasures, exposing a gap between AI capability deployment and defensive infrastructure. Autonomous agents can navigate networks, escalate privileges, and exploit multi-step vulnerabilities without human intervention, making traditional perimeter-based security obsolete. Organizations are caught between vendors racing to commercialize agentic capabilities and security practices built around human-paced attack timelines.