AI flops when isolated from repeatable production systems. Scalable AI needs modular pipelines, stable data sources, versioned models and automated monitoring. Productionising AI means reproducible training workflows, robust feature stores, monitoring for drift and automated rollbacks. Organisations adopting such systems move from disposable experiments to reliable, business-impacting AI at scale.