AI data centers are the core reason RAM and SSD shortages may last into 2027 and possibly 2028: they are absorbing HBM, server DRAM, NAND flash and enterprise SSD capacity faster than suppliers can add it. HBM for AI accelerators consumes DRAM manufacturing resources, while enterprise SSD demand competes for NAND th...

Create a landscape editorial hero image for this Studio Global article: Why are global memory and SSD shortages expected to last until 2028?. Article summary: Global memory and SSD shortages are expected to last into 2027 or possibly 2028 because AI data-center demand is absorbing huge amounts of DRAM, HBM, NAND flash, and enterprise SSD capacity faster than suppliers can add . Topic tags: general, general web. Reference image context from search candidates: Reference image 1: visual subject "# DRAM Shortage to Persist Until 2028, With AI Demand Consuming 40% of Global Supply. The global memory market is facing a structural crisis. A perfect storm of explosive AI growth" source context "DRAM Shortage to Persist Until 2028, With AI Demand Consuming 40% of Global Supply — BigGo Finance" Reference image 2: visual subject "Thank you for your interest in our company. Please complete the form
RAM and SSD shortages are not being driven by one missing part. The memory market is being repriced around AI infrastructure: data-center buyers need high-bandwidth memory, server DRAM, NAND flash and enterprise SSDs at scale. TrendForce says DRAM suppliers are reallocating advanced process nodes and new capacity toward server and HBM products, while NAND demand is increasingly split between consumer and AI applications [10].
That is why forecasts now stretch beyond a normal quarterly squeeze. TechwireAsia, citing Nikkei Asia, reported that leading U.S. and South Korean suppliers were increasing DRAM output at a pace that would meet only about 60% of demand by 2027 [2]. Altium’s market analysis says limited fab expansion, mostly sold-out NAND production and multi-year HBM contracts could keep tightness in place into late 2027–2028 [
4].
AI data centers changed the buyer mix for memory. Everstream explains that AI data centers rely on GPUs that require HBM, a three-dimensional stack of DRAM chips, and that HBM requires more wafer area than standard DRAM [8]. TrendForce says suppliers in 1Q26 continued reallocating advanced nodes and new capacity toward server and HBM products to support rising AI server demand [
10].
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AI data centers are the core reason RAM and SSD shortages may last into 2027 and possibly 2028: they are absorbing HBM, server DRAM, NAND flash and enterprise SSD capacity faster than suppliers can add it.
AI data centers are the core reason RAM and SSD shortages may last into 2027 and possibly 2028: they are absorbing HBM, server DRAM, NAND flash and enterprise SSD capacity faster than suppliers can add it. HBM for AI accelerators consumes DRAM manufacturing resources, while enterprise SSD demand competes for NAND that would otherwise serve client SSDs, PCs and phones [8][10].
Memory production cannot scale instantly: reports say current DRAM output growth may meet only about 60% of 2027 demand, and some new facilities are not expected online until 2027–2028 [1][2].
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The result is a structural allocation problem. Capacity that might otherwise support conventional DDR5, LPDDR, client SSDs, PCs or smartphones is being pulled toward AI and server products where demand is stronger and margins are higher [9][
10]. IDC similarly describes the shortage as being driven partly by a reallocation of manufacturing capacity away from consumer electronics toward higher-margin memory solutions for AI, with knock-on effects for device makers and end users [
9].
HBM is not separate from the DRAM ecosystem. It is built from stacked DRAM and uses specialized manufacturing and packaging resources [8]. As memory makers allocate more capacity to HBM, less of the same manufacturing base is available for traditional DRAM products used in other systems [
8].
Industry reports also identify SK hynix, Samsung and Micron as shifting wafer production toward HBM for AI accelerators [13]. That makes business sense: AI and server memory can command priority, while commodity memory for consumer devices becomes more exposed to allocation limits and price increases [
9][
10].
SSDs are affected because they depend on NAND flash, and NAND is also being pulled toward data-center use. TrendForce says NAND flash demand is increasingly polarized between consumer and AI applications, with enterprise SSDs becoming the largest segment; in the same 1Q26 outlook, it forecast client SSD prices to rise by more than 40% [10].
Storage suppliers have also warned of allocation constraints driven by data-center, hyperscaler and AI server build demand, with DRAM and NAND prices rising and extended lead times expected [16]. In other words, the SSD issue is not just retail demand for laptop upgrades. Consumer and client SSD buyers are competing with enterprise storage orders tied to cloud and AI infrastructure [
10][
16].
Large cloud service providers have both the budget and the urgency to reserve memory supply ahead of other buyers. TrendForce says U.S.-based cloud service providers locking in capacity are widening the DRAM supply-demand gap and forcing other buyers to accept higher prices [10]. TechwireAsia reported that AI demand and limited capacity are expected to keep memory prices high and shipments weak through at least 2027 [
2].
That helps explain why shortages can persist even if total output rises. New supply may arrive, but the first claim on it often goes to AI servers, HBM, server DRAM and enterprise SSD contracts rather than the consumer PC, phone or client SSD channels [9][
10].
Memory production capacity cannot be added as quickly as a purchase order. TechwireAsia reported that meeting demand would require memory production to expand by around 12% annually through 2027, while current growth was about 7.5%; the same report described a roughly 40% gap and output that would meet only about 60% of demand by 2027 [2].
Gigazine’s summary of related reports says most added facilities were not expected to become operational until 2027 or, at the latest, 2028 [1]. That factory timing is a major reason 2028 appears in shortage forecasts: a fab expansion approved today does not instantly create qualified, high-yield DRAM or NAND supply [
1][
2].
The shortage is harder to route around because it spans multiple memory and storage categories at once. Reports have described severe tightness across HDDs, DRAM, HBM and NAND in 2026 [5]. When several adjacent product classes are constrained at the same time, buyers have fewer easy substitutes.
That matters for both enterprises and consumers. Enterprises may face longer procurement cycles for servers and storage, while PC, smartphone and client SSD markets are more exposed to higher component costs as AI infrastructure absorbs more of the available supply [9][
10][
16].
Yes. The 2028 timeline is a forecast, not a fixed date. Tightness could ease earlier if AI infrastructure spending slows, if long-term orders are digested, or if new capacity comes online faster than expected. It could also last longer if cloud and AI customers keep locking up HBM, server DRAM, NAND and enterprise SSD supply faster than producers can expand output [2][
4][
10].
For buyers, the practical takeaway is to plan around elevated prices and longer lead times rather than assuming a quick return to cheap RAM and SSDs. TrendForce’s 1Q26 outlook forecast sharp quarterly price increases for server DRAM and client SSDs, and TechwireAsia reported sustained memory cost pressure through at least 2027 [2][
10]. The most accurate way to read 2028 is as a risk window: plausible under current AI demand and capacity assumptions, but still dependent on how fast supply and demand move from here.
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