Generative AI has moved quickly from experimentation to enterprise adoption, but many teams still struggle to move beyond demos into scalable, reliable, and governed production systems. This talk will explore what it really takes to build production-ready Generative AI solutions in enterprise environments, with a focus on the data and platform foundations that make these systems successful. It will cover how data engineering, data quality, retrieval architecture, governance, observability, and cloud-native design influence the performance and trustworthiness of AI systems. Attendees will gain a practical understanding of the architectural patterns, risks, and design decisions involved in deploying Generative AI responsibly at scale.