Real-Time Data Should Be Central to Every Snowflake AI Architecture

Mark Van de Wiel argues that AI systems operating on stale data produce costly errors, examining three emerging enterprise AI use cases — natural language query interfaces, workflow automation agents, and personal digital assistants — and the risks each faces when underlying data is outdated. Snowflake’s semantic views, role-based access control, and audit logging help mitigate governance and accuracy risks, but only if real-time data synchronization is treated as foundational to AI adoption.