Surging demand for AI computing is propelling the semiconductor industry toward a record $1.3 trillion in revenue this year, but it is also making one resource increasingly scarce: server hardware.

The strain extends throughout the entire AI supply chain, particularly affecting the x86 server CPUs that Intel and AMD supply to the cloud market. Research firms Gartner, IDC, and TrendForce all acknowledge that demand remains resilient, memory prices are climbing steadily, and supply chain issues are likely to persist until 2027.

Their forecasts collectively paint a broader picture: Gartner focuses on the spike in chip sales and prices, IDC tracks server delivery activity, and TrendForce monitors component deliveries. Taken together, the data suggests that the industry's most pressing challenge is not demand growth but rather producing hardware in sufficient quantity. This development follows Nvidia's push into the CPU market, which adds further competitive pressure on both Intel and AMD.

AI Silicon Now Accounts for 30% of Every Chip Dollar

Gartner announced on April 8 that global semiconductor revenue is expected to exceed $1.3 trillion in 2026, representing a 64% year-over-year surge — the highest growth rate the research organization has recorded in 20 years. Chips designed specifically for AI are estimated to account for approximately 30% of total sales.

A significant portion of this spending is driven by hyperscale cloud providers racing to build out their AI infrastructure. Gartner predicts that investment in AI infrastructure will increase by roughly 50% in 2026, intensifying demand for CPUs, bespoke AI accelerators, and the servers that house them.

According to Rajeev Rajput, senior principal analyst at Gartner, the industry's third consecutive year of double-digit growth reinforces the central role of semiconductors within the AI technology stack. While some manufacturing bottlenecks have begun to ease, AI infrastructure continues to absorb nearly all new production capacity, leaving mainstream server components in critically short supply.

Memflation Pushes DRAM and NAND to Fresh Highs

Memory has emerged as one of the most acute pain points. Gartner coined the term "memflation" to describe the AI-driven surge in memory prices as demand consistently outpaces supply. The firm expects DRAM prices to rise 125% in 2026 and NAND flash prices to climb 234%, driving total memory revenue from $216.3 billion last year to $633.3 billion.

TrendForce reports that DRAM contract prices are likely to increase by an additional 13% to 18% in Q3, while NAND flash contract prices are projected to rise 10–15%.

Consumer demand for PCs and mobile devices has weakened, with buyers resisting higher prices, but this has not alleviated the pressure on data centers. Memory manufacturers continue to prioritize the high-margin server segment, keeping overall supply tight. The concentration of global DRAM production among Samsung, SK Hynix, and Micron — which collectively control over 95% of the market — means that capacity allocation decisions by just three companies ripple across the entire server supply chain. Meanwhile, the same manufacturers are diverting wafer capacity to High Bandwidth Memory (HBM) stacks used in AI accelerators, further constraining the RDIMM supply that x86 servers depend on.

x86 Servers Are the Bottleneck, Not Demand

The imbalance is clearly visible in the latest figures from IDC. In the first quarter of 2026, global server system revenues rose 30.7% year-over-year, while the number of servers shipped increased by only 3.3%. Companies are now paying substantially more for only marginally greater hardware capacity, with memory technology shortages cited as the primary constraint.

According to TrendForce, x86-based servers using RDIMM memory remain the most effective solution for many AI operations that require multitasking capabilities. As a result, Intel and AMD continue to dominate AI infrastructure growth even as memory shortages hamper platform deployment. That dominance faces a longer-term challenge from ARM-based server processors, such as AWS Graviton and Ampere Computing designs, which are gaining traction among hyperscalers seeking cost and power-efficiency advantages in AI inference workloads.

For corporate customers, the key takeaway is that components beyond processors now determine delivery timelines. Even if Intel and AMD expand production through new fabrication facilities and supply agreements, shortages in memory and other server components can still cause extended lead times for complete systems.

Buyers Warned on Contract Terms

Analysts advise buyers to look beyond current prices. While the sharpest price increases are expected to moderate after the first half of 2026, prices are projected to remain elevated through 2027. Gartner recommends that IT organizations avoid entering long-term supply contracts with unfavorable pricing terms.

Rajput noted that memflation could "destroy, or at least delay, non-AI demand into 2028." IDC predicts that NAND and memory supplies will remain tight until at least the first half of 2027, though the server market is expected to expand at a compound annual growth rate of 25.1% through 2030.

Taken together, the forecasts from Gartner, IDC, and TrendForce indicate that the AI infrastructure landscape is shifting. The central question is no longer whether businesses want to build AI systems, but whether they can secure the necessary hardware at a reasonable price.