Why AI scale is breaking systems built for humans

AI adoption is rapidly transforming infrastructure demands, with 83% of technology leaders anticipating that their systems will fail under AI pressure within two years due to the 24/7, machine-driven load that AI imposes. Unlike previous technological shifts, AI does not add temporary spikes but creates continuous, unpredictable demand that traditional architectures cannot handle. This transformation shifts the focus from compute, storage, and network costs to the need for seamless coordination, as AI systems require databases to maintain consistency and availability under constant transactional pressure. The database layer is often the first to struggle, becoming a critical constraint as it must support multi-region, always-on operations without scheduled downtime. To meet the demands of AI, systems must be re-architected to be inherently distributed, ensuring strong consistency and automatic failure handling, with distributed SQL solutions like CockroachDB offering a viable path to manage these challenges by providing horizontal scalability and reliability. As AI's scale becomes inevitable, the ability of an organization's infrastructure to adapt and hold up under this pressure will determine whether AI serves as a durable competitive advantage or a persistent risk.