Why Your Architecture is Killing Your AI Strategy

​Summary: Nuno Oliveira, former Country Chief Architect at Barclays Bank, leads a closed-door session on fixing enterprise data quality at the architectural level. It confronts the brutal reality that AI can't run on a legacy data swamp built from decades of shadow IT and siloed systems. Focus: how data quality and AI readiness must be ruthlessly engineered into the foundation, not bought as a SaaS dashboard.

​Every Enterprise Board is currently mandating the deployment of Generative AI and advanced analytics. But for the CTOs and Chief Data Officers executing this mandate, the operational reality is brutal: you cannot build high-speed AI on top of a legacy data swamp. Enterprise data quality is rarely a "data science" problem; it is an enterprise architecture problem. Decades of shadow IT, siloed applications, and duct-taped system integrations have created a fundamentally broken data foundation.

​To tear down the unvarnished reality of fixing enterprise data quality at the architectural level, we are locking the doors with Nuno Oliveira. Nuno is an expert in untangling massive corporate IT complexities. As the former Country Chief Architect & Europe Lead Enterprise Architect for Barclays Bank, and former CTO & Chief Architect for Capgemini Iberia, he has driven massive IT rationalization programs and led application architecture strategies during highly complex European divestitures. Nuno operates on a singular philosophy: data quality and AI readiness cannot be bought via a new SaaS dashboard—they must be ruthlessly engineered at the foundational architecture level.