Five Control Domains That Make AI Frameworks Effective
SC Media, Thursday, February 5th, 2026
Every major cloud and data platform now publishes guidance on how organizations should secure artificial intelligence (AI). From Google's Secure AI Framework (SAIF) and Amazon Web Services' CAF-AI and Generative AI best practices to Microsoft's Secure AI and Responsible AI standards, enterprises are surrounded by frameworks.
Add in guidance from NIST, the Cloud Security Alliance, and OWASP, and we have a rich, but often overwhelming landscape of AI security blueprints.
These frameworks are valuable. They define principles, highlight risks, and establish a common language between security, engineering, and leadership teams. But many organizations struggle to move beyond documentation and compliance checklists. They find that frameworks describe what good looks like, but they rarely explain how to enforce trust when AI systems operate dynamically at runtime.