Most enterprise cloud strategies were designed for predictable applications—not probabilistic AI systems that consume dynamic data, take autonomous actions, and create difficult to forecast costs. This talk will explain why those traditional assumptions must change as organizations move AI from experimentation into production. I will introduce five practical principles covering strategy alignment, workload placement, application and data modernization, platform thinking, and operational resilience. Attendees will learn how business outcomes, data constraints, operating cost, reliability, and security should shape architecture decisions. Join this session to leave with a practical framework for determining whether your cloud strategy is truly ready to deliver AI at scale.
