With 24.5 million connected vehicles, those small interactions add up fast. BMW’s fleet now generates more than 16.6 billion requests each day, processing 184 terabytes of data and 100 million API calls with sub-second latency, AWS reported. BMW now runs more than 600 AI use cases across the business, the company said. Engineers use AI to run crash simulations without building physical prototypes. Procurement teams use it to analyze supplier contracts and generate tender documents. Factory systems use it to inspect welds in real time and flag defects before an order moves down the assembly line. All of it runs on a shared enterprise platform. The platform lets internal teams, including non-technical specialists like battery engineers and logistics planners, build and deploy their own AI tools without writing infrastructure code. More than 12,000 developers work inside BMW’s Software Factory on AWS, the company noted. BMW also uses AI to run automatic root cause analysis on cloud service outages, cutting incident diagnosis from hours to minutes, AWS reported. The system correctly identifies the root cause in 85% of cases. BMW’s Factory Floor Detects Defects and Moves Parts Without Human Input Before BMW built its Connected AI Platform on AWS, the team behind its Intelligent Personal Assistant—the in-vehicle system that learns driver preferences and suggests relevant features on the road—had to wait overnight for the model to complete its training. Now, the platform runs on Amazon Elastic Kubernetes Service and distributes computing work across multiple GPUs at once rather than processing sequentially on a single machine. Training times dropped from hours to 30 minutes at under 5 euros (about $5.70) per run, AWS reported. The same infrastructure now delivers 60% faster time to market for new connected vehicle features and cuts infrastructure costs by 20%. When BMW migrated legacy systems using AI-powered