AI Risk in SaaS: What Security Teams Are Missing

This piece argues that AI risk is already pervasive across modern SaaS ecosystems, driven less by model weaknesses and more by embedded AI features, inherited permissions, opaque vendor practices, and sprawling integrations that lack visibility and governance. It explains that failures often appear as quiet data leakage, over-permissioned agents acting as allowed, vendor training on customer data, and automated decisions without effective oversight. The recommended approach is pragmatic governance: inventory where AI exists, map data access and permissions, review vendor data sharing, and manage AI as operational infrastructure to regain control without hindering productivity.