The New Operating Model for AI: Observability in the Age of Agentic Systems

AI is no longer sitting in controlled pilots, it’s embedded across customer experiences, developer workflows, and core systems. But unlike traditional applications, AI introduces unpredictable workloads, opaque decision-making, new security exposures, and volatile cost structures. IT leaders are now grappling with a fundamental loss of visibility and control, often reacting to issues after they surface rather than proactively managing them. The result is a growing gap between AI ambition and operational readiness, where scaling innovation increases risk instead of reducing it.

Leading organizations are closing this gap by rethinking observability for an AI-first environment. This means moving beyond traditional monitoring to achieve real-time, end-to-end visibility across models, agents, applications, and cloud infrastructure. By connecting these layers, teams can better understand system behavior, anticipate disruptions, optimize performance, and manage costs with greater precision. At the same time, they are embedding governance, security, and trust directly into operations—shifting from reactive firefighting to a more predictive, controlled approach to AI at scale.

Join Dynatrace, AWS and a select group of your peers for a candid, off-the-record discussion on what it truly takes to operate AI in production. Together, we’ll explore how to build real-time visibility across complex AI ecosystems, how to balance innovation with control in dynamic environments, and how to establish the operational discipline needed to scale AI with confidence, reliability, and trust.