AI is no longer a future-state initiative. Enterprises are actively deploying AI agents, embedding AI-driven steps into business-critical workflows, and scaling automation across hybrid environments at a pace that is outrunning their ability to govern and manage execution outcomes.

But there is a problem hiding in plain sight. Most organizations have focused their AI investments on models, platforms, and data — and far less on what happens after an AI agent takes an action. Who governs that action? What happens when it fails? How do you ensure it executes within the boundaries the business requires?

This webinar is a dialogue between BMC and AWS that sits at the center of how enterprises are navigating this challenge, drawing on real patterns they are seeing across shared customers today.

Attendees will leave knowing the answer to the following question: “As AI agents enter production, how do enterprises maintain the execution reliability, governance, and control that mission-critical operations demand — without slowing down innovation?”

Key Takeaways:

1. A clear distinction between automation, orchestration, and agentic orchestration — reinforcing that enterprise AI doesn’t stall at the model, it stalls at scale, and why that matters operationally as AI scales.

2. Risk you can name: A clear way to articulate execution risk — not as a technical problem, but as a business continuity and governance challenge.

3. 3 actionable principles for approaching agentic orchestration design — directly applicable to your own environments.