Data Center Knowledge reports that billions of dollars in compute capacity remains locked and unavailable even as AI demand continues to surge across hyperscaler and enterprise customers. Interconnection delays, power constraints, and supply chain bottlenecks are cited as primary factors preventing deployed hardware from coming online at full utilization. The gap between installed capacity and accessible capacity has direct implications for AI model training timelines and cloud service availability. Analysts expect the bottleneck to persist through at least late 2026 without accelerated grid and interconnection investments.