What is the biggest AI security risk identified by experts?

The biggest AI security risk is the "visibility gap" in tracking LLM usage, hindering effective security and incident response.

When will executives be held liable for AI actions?

Palo Alto Networks predicts 2026 will see the first major lawsuits holding executives personally liable for rogue AI actions.

How do AI-BOMs differ from traditional software SBOMs?

AI-BOMs are crucial for tracking runtime model dependencies, unlike traditional SBOMs which focus on fixed software dependencies resolved at build time.

Home / Technology / Shadow AI: Enterprise's Costly Blind Spot

Shadow AI: Enterprise's Costly Blind Spot

2 Jan

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Summary

Most firms lack advanced AI security strategies.
Rogue AI lawsuits could target executives in 2026.
Visibility gap hinders AI security and incident response.

Shadow AI: Enterprise's Costly Blind Spot

Four in 10 enterprise applications will feature AI agents this year, yet only 6% of organizations possess robust AI security strategies, according to Stanford research. Palo Alto Networks forecasts that 2026 will usher in the first major lawsuits holding executives personally accountable for AI actions. A pervasive "visibility gap" regarding LLM usage and modification hinders effective AI security, transforming incident response into guesswork.

A survey revealed 62% of security practitioners cannot identify where LLMs are deployed within their organizations. This lack of transparency exacerbates risks like prompt injection (76%), vulnerable LLM code (66%), and jailbreaking (65%). Traditional security tools struggle with adaptive AI models, leading to "shadow AI" incidents costing an average of $670,000 more than standard breaches.