Why does AI on the endpoint create new security challenges?
Smaller language models, AI PCs, and AI applications are rapidly delivering more workloads onto enterprise devices, exposing enterprise IP and creating vulnerability to stealth risks. Each application can interpret information, generate content, make recommendations, and act autonomously.
Enterprises need to determine:
The Impact
AI adoption, governance and control in lockstep.
As AI software gains autonomy, enterprises need boundaries they can define and govern to adopt new capabilities with confidence and speed.
Solution Overview
How does IGEL envision trusted AI execution?
IGEL envisions layers of trust that extend IGEL Preventative Security Model® to AI applications and workloads. Enterprises can assess whether software comes from a trusted source, reaches devices through controlled channels, and operates within defined boundaries.
What are the benefits of governing AI at the endpoint?
Resources
Article · Channel Insider
Shadow AI Policy Needs Endpoint Controls
Shadow AI governance requires endpoint visibility and network controls.
Research · Frost & Sullivan
From Detection to Prevention: Reimagining Endpoint Security for the AI Era
Building the Foundation for a New Security Model
Blog · John Walsh
AI Needs Guardrails That Keep Pace With Its Capabilities
The objective isn’t to stop AI autonomy. It is to establish the boundaries that allow us to use it safely, confidently, and at speed.
Build a secure foundation for Enterprise AI at the endpoint.
Explore how IGEL Preventative Security Model® and IGEL Adaptive Secure Endpoint Platform™ supports endpoint control and governance as AI applications and workloads evolve. Get hands-on with what’s next. Join our AI Group.