Google operates the world’s largest private network, supporting global services and rapidly growing AI workloads. As demand accelerates, traditional capacity planning—based on weeks of manual coordination each quarter—has become increasingly difficult to scale. To address this, Google built AI-assisted systems for network and infrastructure planning. Predictive models and digital twins forecast traffic and optimize fiber capacity, while agentic systems manage server allocation, inventory, and shipment planning - balancing competing priorities such as YouTube and Search. These systems transform capacity planning from a reactive process into a proactive, automated discipline, reducing operational toil and improving reliability. This keynote shares lessons from building and operating AI-driven capacity planning at planet scale in the AI era.
Akriti Bhat is a software engineer focused on building reliable distributed systems at Meta Platforms, and previously led AI-assisted capacity planning for fiber networks at Google, transforming manual infrastructure planning into scalable, automated systems. Krishna Madhuri Kompella's work at Google transforms traditional capacity planning into a proactive, automated system, shifting from manual resource management to an agentic network that anticipates and adapts to the explosive growth of AI workloads.
