Meta Extends Server Lifespan to 7 Years Amid AI Chip Shortage
Meta Platforms is extending the lifespan of certain data center servers from six to seven years due to a significant supply shortfall. As a result, the company aims to maintain infrastructure capacity while navigating hardware constraints. This move comes as it prepares to report first-quarter 2026 earnings, with analysts expecting strong revenue growth.
Previously, the company had already increased server longevity to five and a half years in 2025. Consequently, that adjustment reduced depreciation expenses by billions. Now, the shift to seven years reflects a continued strategy to stretch existing resources. Moreover, this approach builds on changes that began in 2022, when the company first moved beyond a four-year lifecycle.
Memory Chip Shortage Intensifies
The decision highlights a broader shortage of memory chips affecting the tech industry. In particular, data centers are expected to consume about 70% of global memory chip output in 2026. Meanwhile, major manufacturers like Samsung, SK Hynix, and Micron Technology have shifted production toward AI-focused components.
As a result, supply growth for DRAM remains limited, rising only modestly compared to historical trends. At the same time, prices for server-grade memory have surged, with DDR5 costs roughly doubling in early 2026. According to Sassine Ghazi, the chip shortage is expected to continue through 2026 and 2027. Therefore, companies relying on AI infrastructure face ongoing supply pressure.
Supply Chain Pressure and Strategic Deals
In response, Meta has expanded partnerships and diversified its supply chain. For instance, it recently signed a major agreement with Amazon Web Services to access Graviton5 CPU capacity. Additionally, the company strengthened its collaboration with Broadcom for custom chips and secured deals with AMD and Nvidia.
Consequently, capital expenditures are projected to rise sharply in 2026. However, supply bottlenecks persist across key components, delaying server production timelines. At the same time, the company is restructuring its workforce, with plans to reduce staff to improve efficiency. Altogether, these actions reflect the balance between aggressive AI expansion and the limits imposed by global supply chains.
