Your developers are already running AI locally: Why on-device inference is the CISO’s new blind spot
Summary
An analysis of security management blind spots and response strategies arising from internal enterprise developers running AI models on local devices instead of the cloud.
Key Points
- Traditional cloud-based AI control methods (such as CASB) are being rendered ineffective by local inference (Shadow AI 2.0).
- High-performance laptop hardware, model quantization technology, and convenient deployment ecosystems have made local LLM execution commonplace.
- Data loss prevention (DLP) systems do not function during local execution, increasing risks from unmanaged infrastructure.
- Among technical teams, even 70B-class models have reached levels where they can be run at practical speeds locally.
Notable Quotes & Details
Notable Data / Quotes
- MacBook Pro with 64GB unified memory can often run quantized 70B-class models
Intended Audience
CISOs, security officers, and IT managers