Projecting a 62.7% growth, booming memory demand, tight supply, and AI-driven data centre expansion are set to reshape global semiconductor revenues through 2026.
The global semiconductor revenues are projected to surge by 62.7% in 2026, according to a report by Omdia. This points to one of the strongest growth phases for the industry, driven by sustained demand for memory chips and constrained supply.
The revised forecast reflects exceptional momentum in the DRAM and NAND markets, with DRAM revenues expected to nearly double and NAND potentially expand by up to four times compared with 2025 levels.
The outlook is being shaped by persistent supply limitations, particularly in conventional memory integrated circuits, as manufacturers prioritise production of high-bandwidth memory (HBM), which offers higher margins but lower volumes. This shift is contributing to elevated pricing across memory categories and is likely to keep supply tight through much of 2026.
Demand is being driven largely by enterprise and data centre requirements. A significant server refresh cycle is expected, alongside continued capital expenditure by hyperscale operators.
Organisations are upgrading legacy systems to support increasingly complex workloads, including those related to artificial intelligence, boosting demand for high-performance memory and processing components.
Moreover, the computing and data storage segment is projected to lead overall growth, with revenues forecast to rise around 90% year-on-year and exceed $700 billion. This is attributed to strong demand for data centre servers and memory-intensive applications, combined with higher average selling prices.
Consumer electronics and wireless segments are also expected to contribute to revenue gains. Although smartphone shipment volumes may remain relatively stable, increased memory costs are likely to raise device bill of materials.
New product cycles, including foldable devices and AI-enabled features, are expected to support growth, alongside demand for wearables.
However, risks remain, including challenges in scaling supply, geopolitical pressures, and uncertainty over long-term returns on significant investments in AI infrastructure.
