Omdia Raises 2026 Semiconductor Forecast to 62.7%: AI Memory Crunch Pushes DRAM to Nearly Double, Supply Relief Delayed to 2027
The semiconductor industry is heading for its largest single-year revenue expansion on record, according to Omdia, which has revised its 2026 growth forecast upward to 62.7%.
The revision, released April 23, is driven almost entirely by AI memory demand. DRAM is forecast to nearly double in market value compared to 2025. NAND could quadruple. Neither market will see meaningful supply relief before 2027.
Key figures
- Total semiconductor revenue growth, 2026: +62.7%
- Computing and data storage growth: +90% year-on-year, crossing $700 billion
- DRAM: approximately 2x market value versus 2025
- NAND: approximately 4x market value versus 2025
- Supply relief timing: “well into 2027” at earliest
The structural cause
HBM is the central bottleneck. The memory fabs that produce High Bandwidth Memory for AI accelerators are running at capacity — but HBM delivers fewer units per wafer while commanding significantly higher prices per unit. The consequence is a supply squeeze on conventional DRAM and NAND while the fabs remain fully occupied.
Hyperscaler capex and an enterprise server refresh cycle are converging in 2026. Organizations are retiring legacy hardware to handle LLM inference workloads, creating simultaneous demand across data center, cloud, and edge deployments. Average selling prices are rising as a result of both shortage and a shift toward higher-specification silicon designs.
“Supporting the progression of AI beyond simple Q&A use cases has exponentially increased demand for memory and processing ICs, fueling semiconductor industry revenues overall,” said Myson Robles-Bruce, Senior Principal Analyst at Omdia.
The pricing dynamic
Omdia flags that the growth is price-driven, not volume-driven. Unit shipments for most categories are either flat or declining. Revenue growth is being created by higher ASPs across server DRAM, HBM, NAND in enterprise SSDs, and even consumer-device memory.
The parallels to previous semiconductor supercycles — crypto mining demand, the 2017–2018 memory cycle — exist, but Omdia characterises the current dynamic as broader in scope and more persistent in demand structure. The company is monitoring tariff risk, energy costs, and geopolitical supply chain disruptions as potential downside factors.
Consumer pullthrough
Beyond data centers, the memory crunch reaches consumer electronics. Smartphone bill-of-materials costs are rising because DRAM pricing is set globally. Even with flat unit shipments, OEMs pay more per device. The cycle is pushing a range of premium smartphone launches and AI-enabled wearables that carry higher memory specs into a tighter supply environment.
Implications for AI infrastructure costs
For buyers — hyperscalers, enterprise IT, and AI lab operators — the forecast has a direct implication: memory line items on infrastructure budgets will increase through 2026 and into 2027, independent of model efficiency improvements. Training runs that have grown more cost-effective through algorithmic improvements will partly see those savings absorbed by rising DRAM prices.
The $700 billion computing and storage figure, if it lands as forecast, would represent roughly 30% of total global semiconductor revenues for the year — a concentration in AI-adjacent workloads with no recent historical precedent.