AI-Driven Memory Chip Shortage: A Perfect Storm of Supply Chain Disruptions

In the hierarchy of the digital revolution, memory chips have long been the “quiet labourers." While CPUs (Central Processing Units) and GPUs (Graphics Processing Units) command the spotlight as the “brains” of the personal computers and artificial intelligence eras, memory, specifically Dram (Dynamic Random-Access Memory) and Nand Flash, has traditionally been far less visible. For decades, the industry followed a predictable, if volatile, rhythm of boom-and-bust cycles, from the 1990s internet explosion and smartphones in the 2010s to the post-pandemic correction of 2023. The current cycle, however, is fundamentally different. The AI-driven surge in demand is not merely another upswing—it is reshaping the structure of the global memory supply chain. This “AI Supercycle” has created a perfect storm. Beginning in 2024, major memory manufacturers reduced output of conventional Dram, such as DDR4, widely used in smartphones, PCs, and consumer electronics, to avoid oversupply. At the same time, demand for advanced memory, especially high-bandwidth memory (HBM) and high-capacity DDR5, soared as cloud providers and technology giants rapidly expanded AI data centres and infrastructure. The impact is already being felt—and will likely intensify. This strategic reallocation of silicon wafer capacity is producing two closely linked effects that could trigger a new round of global supply-chain strain. First, the AI supercycle is structurally crowding out legacy sectors. As generative AI models move from training to inference and deployment, they require enormous computing power supported by high-speed, large-capacity memory and consume three times the production capacity of conventional memory. To meet this demand, major memory suppliers Samsung, SK Hynix, and Micron have scaled back production of DDR4 and other conventional memory used in laptops, smartphones, automobiles, and gaming devices. The result is growing shortages in consumer electronics and industrial sectors that depend on mature but still essential memory technologies. The logic behind this shift is straightforward. AI infrastructure (data centre, servers) builders—cloud service providers and large technology firms—order memory in massive volumes and are far less price-sensitive than consumer electronics manufacturers. Companies such as Nvidia, Google, Amazon, Microsoft, and others sit at the front of the allocation line. HBM, which can generate profit margins of 50–70 per cent, has been in short supply since 2022, when demand for AI accelerators surged far faster than memory output. For suppliers, prioritising AI memory is simply rational. This relationship is mutually reinforcing. AI infrastructure cannot scale without sufficient HBM, pushing tech giants to secure long-term supply agreements. Meanwhile, memory producers are enjoying the dividends of the AI boom. In 2025, Micron’s stock rose sharply, Samsung’s operating profits surged to their highest level in years, and SK Hynix benefited from strong demand and global investor interest. Second, the memory shortage risks becoming a broader supply-chain problem. Unlike the pandemic-era chip crunch, which was driven largely by logistics and temporary disruptions, today’s shortage stems from a structural reorientation of manufacturing. Memory production is increasingly a zero-sum game: every wafer devoted to HBM stacks for AI servers is a wafer unavailable for smartphones, PCs, or vehicles. Market signals underscore the strain. Industry analysts estimate that average Dram prices could rise by an unprecedented more than 50 per cent in early 2026, while global supply growth for Dram and Nand is slowing sharply. Memory accounts for 15–20 per cent of a smartphone’s bill of materials, meaning higher chip prices will inevitably be passed on to consumers. PC manufacturers have warned of double-digit price increases, while automakers face mounting pressure from surging costs of automotive-grade memory. Even if memory makers decide to rebuild capacity for consumer electronics, relief will not come quickly. New semiconductor fabrication plants take at least two years to construct and equip, and the industry remains wary of overinvestment that could trigger another collapse once demand cools. In the meantime, reports of hoarding—from street-level traders to major manufacturers—have emerged in markets from Shenzhen to Tokyo to California, amplifying volatility. Geopolitics further complicates the picture. Tariffs and export controls act as cost multipliers, fragmenting supply chains and extending delivery times. Instead of easing shortages, trade barriers risk locking regions into persistent imbalances. Looking ahead, the memory-chip shortage should be understood as a structural stress test of the global supply chain rather than a temporary disruption. While capacity expansion, improved supply-chain resilience, and technological breakthroughs, such as advances in 3D Dram or emerging alternatives like high-bandwidth flash, may eventually ease the pressure, these adjustments will take time and remain uncertain. The durability of the current memory supercycle ultimately depends on the sustainability of AI investment itself: without a clear and profitable AI business model, demand growth could slow. Moreover, memory constraints are only one potential bottleneck. Energy availability and infrastructure limitations could also cap the pace of AI deployment, even if memory supply improves. Taken together, the memory bottleneck highlights a broader reality of the AI era. From AI data centres to your next smartphone, memory chips have become everyone’s problem. Whether the current shortage evolves into a prolonged global supply-chain strain will depend not only on semiconductor manufacturing but also on how governments, firms, and markets manage risk, investment, and expectations in an age where digital expansion is anything but frictionless. (Alex He is a senior fellow at the Centre for International Governance Innovation and an expert on digital governance and global economic relations. Views expressed are personal and do not necessarily reflect those of Firstpost.) Bangladesh’s geography makes it strategically constrained, hemmed in by India on three sides, Myanmar to the south, and the Bay of Bengal. Its economic dependence on India is structural, not cyclical, with imports of textiles, cotton, electricity, and food creating a $9.4 billion trade deficit in 2023-24. The ready-made garment sector, contributing 84% of exports and 11% of GDP, relies heavily on Indian inputs. Natural vulnerabilities, including floodplains and shifting rivers, compound geopolitical risks, while diversification into pharmaceuticals, shipbuilding, and technology remains limited. For Dhaka, accommodation with India, rather than defiance, is essential for sustained economic and strategic stability. Get the latest stories delivered straight to your inbox.