AI governance moves from observability to provable control

As artificial intelligence agents move from experimental tools into production systems, enterprise governance is being forced to answer a harder question. It is no longer enough to know what an agent did. Organizations increasingly need to prove what the agent was authorized to do, why it was allowed to take a specific action and whether that authority remained intact as tasks moved across multiple agents and systems. That challenge is becoming more urgent as agentic systems spread across regulated enterprises, where security, auditability and sovereignty requirements can limit reliance on external software-as-a-service control planes. In the latest episode of theCUBE Research’s AppDevANGLE podcast, I spoke with Sudeep Goswami, chief executive officer of Traefik Labs Inc., and Andreas Prins, who leads sovereignty strategy at SUSE Group, about how AI governance architectures must evolve as autonomous agents begin making decisions and delegating work across increasingly complex enterprise environments. “When you have an agent that is handing a task to another agent, that authority should shrink and not leak…