Navigating Secure AI Deployment: Architecture For Enhancing AI System Security And Safety
Red Hat, Thursday, January 8th, 2026
In the previous articles, we discussed how integrating AI into business-critical systems opens up enterprises to a new set of risks with AI security and AI safety [link], and explored the evolving AI security and safety threat landscape, drawing from leading frameworks such as MITRE ATLAS, NIST, OWASP, and others [link]. In this article, we'll examine the architectural considerations for deploying AI systems that are both secure and safe.
A resilient AI architecture must be designed with a defense-in-depth philosophy, integrating controls that address both traditional cybersecurity threats and unique AI safety risks. The following components are essential pillars of an enterprise-grade AI system implementation that puts security front-and-center. These components are layered on top of each other to create a comprehensive security posture.