The operating system for enterprise AI is not just about replacing traditional data infrastructure with advanced models, but rather about coupling these models with robust orchestration layers that deliver high-quality data. The complexity of AI does not disappear; instead, it's amplified by the reliance on trustworthy, fresh data. Orchestration platforms become the lynchpin in the AI era, abstracting away the complexity of underlying components while providing consistent interfaces for development, deployment, and monitoring. As data teams transform to design comprehensive systems that adapt to changing requirements, they'll establish the rules and frameworks that AI agents operate within. The future is not about doing the same things with better tools, but about fundamentally reimagining data engineering around the new orchestration paradigm. Organizations will need to invest in their orchestration layer alongside their AI layer, focus on frameworks rather than features, build for composition rather than customization, and prioritize observability from day one to succeed in the AI era.