GPU Fragmentation Is Killing AI Economics

TL;DR Enterprises face 3× more AI workloads than available GPUs heading into 2026 Traditional schedulers fail heterogeneous workloads (training + inference + RAG + analytics) Software like Kubex can unlock significant GPU capacity gains using MIG + dynamic fragmentationPower—not GPUs—will be the binding constraint by 2027. The GPU Supply Crisis (2026 Reality Check) By 2026, the GPU shortage isn’t a supply-chain hiccup anymore. It’s baked into the system. Even after pouring billions into CapEx, most enterprises still want 40% more GPU capacity than they actually have.