Most AI agent deployments don't fail because the technology doesn't work. They fail because teams underestimate what it takes to move from a promising pilot to a production system that handles real customers, at volume, every day.

In this session, we examine the gap between pilot and production in enterprise AI deployments - what causes promising initiatives to stall, and what the teams that successfully scale have in common. We look at the decisions that matter most: how to define success before you build, how to evaluate quality at scale, and how to maintain consistency across channels and languages without rebuilding from scratch every time.

We'll cover the metrics CX leaders should be using to assess AI agent performance - containment rate, first-contact resolution, AHT, CSAT - and why the teams seeing the strongest results are moving away from deflection as a primary objective. We'll also address the operational realities: compliance, security, integration with existing contact center infrastructure, and how to build a path from legacy IVR to agents that improve over time.

Attendees will leave with a clear framework for assessing where their deployment is and what it takes to get to production - and a sharper view of what good looks like across the industry.

Key takeaways:

• Discover why most AI agent pilots stall before reaching production - and the decisions that determine which path you're on
• Learn about the metrics that actually matter for evaluating AI agent performance: containment, first-contact resolution, AHT, and CSAT
• Find out how leading teams are moving from deflection-first automation to agents that resolve at the first interaction
• Understand what enterprise-grade deployment requires: compliance, integration, reliability, and how to avoid rebuilding for every new channel
• Obtain practical framework for assessing readiness and defining what production-quality AI CX looks like for your organization