The sandbox wasn’t enough: Why AI agent governance requires runtime observability

AI agent governance can’t rely on pre-deployment testing or isolated sandboxes alone; CIOs need runtime observability to see how agents actually behave in production, where context, tools, and users can change outcomes. The business impact is reduced operational risk, better compliance, and faster issue detection, while the strategic implication is that AI adoption now requires the same kind of continuous monitoring and control frameworks IT uses for critical applications. For IT organizations, this means building governance into the live execution layer—tracking actions, decisions, and anomalies in real time rather than treating AI controls as a one-time approval process.