Artificial intelligence is rapidly moving from experimentation into the core of enterprise operations, reshaping how organizations design and manage their operating models. What were once isolated use cases are now embedded across customer experiences, digital services, infrastructure, and critical workflows. As organizations advance toward agentic AI systems capable of acting autonomously, they are unlocking new speed and innovation, but also introducing greater complexity and unpredictability. How are organizations evolving their operating models to support AI at scale without losing control?

Traditional IT operating models were never designed for dynamic, AI-driven environments. Many organizations lack visibility into how AI systems behave in production and struggle to connect system performance to business impact. Leading enterprises are addressing this by strengthening observability across their environments and leveraging AI to move from reactive operations to more intelligent, automated execution—while increasingly focusing on business observability to understand how digital performance directly influences revenue, customer experience, cost, and risk.

Join peers and industry leaders for a discussion on how organizations are evolving their operating models to support AI and agentic systems at scale. Explore how leaders are improving visibility across complex environments, enabling intelligent automation, and connecting technology performance to real business outcomes—while maintaining resilience, control, and accountability.