Dev Tools · 1h ago
GPU Allocation Governance Replaces Scarcity as Top AI Infrastructure Challenge
By May 2026, "access to GPUs" dropped from the #1 enterprise concern to #4, while "cost per inference" surged to #1. Organizations with $50M GPU clusters find 95% of capacity idle under usage-based billing due to workload coordination failures. Static partitioning on mixed workloads wastes 40–60% of capacity even when clusters appear fully allocated.
Meridian48 take
The article correctly identifies that GPU allocation governance, not supply, is now the bottleneck—but the real test is whether enterprises will adopt dynamic scheduling or continue throwing hardware at a management problem.
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GPU Scarcity Isn't the Problem Anymore. GPU Allocation Governance Is. →
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