Enterprises need serverless platforms for efficient AI and agentic workflows, with data preparation being a key challenge. Dataflow on Google Cloud facilitates batch and streaming pipelines for analytics and AI. Significant enhancements now address compute efficiency for long-running batch jobs and boost inference power for AI workloads. The general availability of Pause/Resume for Dataflow batch jobs allows users to restart failed jobs from their last checkpoint, saving compute and improving productivity. This feature also enables dynamic reallocation of compute resources for higher priority AI tasks. Furthermore, Dataflow now supports G4 VMs powered by NVIDIA RTX PRO 6000 Blackwell GPUs. These new GPUs offer substantial performance improvements, including increased memory and bandwidth, for AI inference. This allows Dataflow jobs to handle models with over 70 billion parameters directly. Customers can leverage native Dataflow ML capabilities like RunInference and GPU-enabled autoscaling with these new GPUs. Together, Pause/Resume and the new GPUs optimize batch job costs and accelerate demanding AI workloads. These advancements aim to simplify AI development and deployment for customers.