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Gartner Lifts 2026 Chip Forecast to $1.6T as AI Memory Demand Tightens Supply

The forecast shifts attention from accelerators alone to the memory and supply-chain capacity needed to run bigger AI systems—and leaves technology buyers facing elevated prices into 2027.

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Gartner Lifts 2026 Chip Forecast to $1.6T as AI Memory Demand Tightens Supply
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Gartner has lifted its 2026 semiconductor revenue forecast to 1.6 trillion dollars, up from 1.3 trillion. That is a projection, not a reported sales total, but it signals how dramatically artificial-intelligence infrastructure is reshaping the market. The less obvious pressure point is memory. As AI clusters get larger and faster, they need more than processors and accelerators. They also need CPUs, interconnects, power equipment, and much more memory in every server. Gartner expects memory to generate more than 54 percent of semiconductor revenue growth next year. NAND flash revenue is projected to rise 372 percent, while DRAM revenue could jump 247 percent. The firm links that surge to continued infrastructure deployments, higher memory content per server, and sustained demand for high-bandwidth memory, or HBM. New fabrication capacity is expected next year, but Gartner still sees supply staying tight. That matters for buyers because the cost pressure is expected to persist: prices should rise in the first half of 2026, then continue increasing, though more moderately, with meaningful relief unlikely before late 2027. Gartner also expects hyperscaler spending on AI infrastructure to grow by more than 50 percent in 2026, supporting demand for GPUs, tensor processing units, and other accelerators. The key constraint is whether new capacity can catch up with memory demand—and whether the broader AI spending behind the 1.6 trillion-dollar forecast holds through 2027.

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3 key points

Gartner’s upgraded outlook implies that memory—not just AI processors—will determine how quickly the semiconductor market can expand. It forecasts NAND revenue rising 372% and DRAM 247% in 2026, while hyperscaler AI infrastructure spending grows more than 50%. New fabrication capacity may arrive, but supply is expected to remain tight and pricing relief is unlikely before late 2027. The $1.6 trillion projection...

  1. 01

    Gartner raised its 2026 semiconductor forecast from $1.3 trillion to $1.6 trillion.

  2. 02

    Memory is expected to generate more than 54% of semiconductor revenue growth in 2026.

  3. 03

    AI data center revenue could reach 53% of the semiconductor market by 2030.

Gartner now expects worldwide semiconductor revenue to reach $1.6 trillion in 2026, up from $809 billion in 2025. The forecast puts AI infrastructure at the center of a market whose fastest-moving pressure point is memory: the chips that AI servers need in growing quantities alongside processors and accelerators.

The new estimate is higher than Gartner’s previous $1.3 trillion forecast. It is a projection, not a reported sales total, but its scale reflects a sharp change in what the industry expects to sell into AI buildouts over the next two years.

The new arithmetic

AI clusters are becoming larger and faster, according to Gartner, increasing their need for CPUs, accelerators, interconnects, power equipment and memory. The firm expects AI data center revenue to account for more than 30% of the semiconductor market in 2026, rising to 53% by 2030.

That mix matters because the forecast is not driven only by the specialized processors associated with AI. Gartner expects memory to account for more than 54% of semiconductor revenue growth in 2026. It projects NAND flash revenue to grow 372% and DRAM revenue to grow 247% during the year.

Memory becomes the limiting input

Gartner ties the memory surge to continued AI infrastructure deployments, higher memory content in each AI server, and sustained demand for high-bandwidth memory, or HBM. Added fabrication capacity is expected next year, but Gartner still expects supply-demand conditions to remain tight as AI deployments use more memory.

The demand side is also expanding. Gartner projects hyperscaler spending on AI infrastructure will rise by more than 50% in 2026, increasing demand for GPUs, tensor processing units and other accelerators. That spending forecast is a key condition beneath the broader $1.6 trillion estimate.

The purchasing problem outlasts the surge

For enterprise buyers, the forecast carries a less welcome implication: Gartner does not expect meaningful pricing relief until late 2027. It expects higher prices in the first half of 2026, followed by persistent but moderating increases through the rest of the year. Gartner senior principal analyst Rajeev Rajput advised CIOs to be cautious about supply agreements with unfavorable pricing that extends beyond 2027.

Gartner expects the market to reach $1.9 trillion in 2027. Whether that trajectory holds will depend heavily on the same forces that lifted the forecast: sustained AI infrastructure spending, the amount of memory required per server, and whether new capacity can ease a market Gartner expects to stay constrained through most of next year.

Sources

  1. networkworld.comAI is turning the semiconductor market into a $1.6 trillion industry

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