Sheridan Orr

Most AI projects fail - not because the model was wrong, but because nothing around it was right. No workflow integration. No ability to scale. Constant prompt drift, endless fine-tuning, and security gaps. If that exposure sits within customer communications, there is no higher-stakes environment for AI to be deployed carelessly, and no faster way to erode trust. This session will explore how to design the infrastructure layer needed to support scalable, secure, and consistent AI performance.

Learning Objectives

• Identify common risks and failure points when deploying generative AI without infrastructure
• Apply a tested approach to designing AI infrastructure that supports security and performance
• Assess current AI implementations against enterprise readiness criteria

Key Takeaways

• A practical framework for moving from AI pilot to scalable CX implementation
• Tools to identify and mitigate risks in customer-facing AI deployments
• A clear approach to evaluating and strengthening AI infrastructure for customer-facing operations