South Korean semiconductor giant SK Hynix has crossed the historic $1 trillion market valuation mark, becoming one of the biggest beneficiaries of the global AI boom. The company’s shares surged around 15% during trading on May 27, lifting its market capitalization to around $1.12 trillion (about 1,680 trillion won). The rally made SK Hynix only the third Asian technology company to surpass the trillion-dollar milestone after Samsung Electronics and TSMC.
SK Hynix shares have reportedly climbed more than 900% over the past year and more than tripled during 2026 alone. At the same time, global investors have rapidly shifted attention from only AI processor makers toward memory suppliers as well. The development becomes significant as just days before SK Hynix crossed the trillion-dollar threshold, US-based Micron Technology also entered the trillion-dollar club, while Samsung had achieved the milestone earlier in May. Together, Samsung, SK Hynix, and Micron are now collectively valued at over $3 trillion, clearly showing how memory chipmakers have suddenly become central to the AI economy.
The reason behind this explosive growth is a severe global shortage of advanced AI memory chips. Unlike traditional DRAM, HBM chips are extremely difficult and expensive to manufacture because they rely on vertically stacked memory dies connected through microscopic through-silicon vias. Production requires advanced packaging, high yields, and sophisticated thermal engineering. According to several reports, memory chip prices doubled during the first quarter of 2026 and may rise another 60% in the following quarter because of supply constraints. Several chipmakers have already sold out large portions of their HBM production capacity through 2026 and beyond.
Particularly, SK Hynix’s rise has been fueled almost entirely by its dominance in high-bandwidth memory. The firm is currently one of the biggest suppliers of advanced HBM chips used in Nvidia’s AI accelerators, including the memory systems powering large-scale AI training clusters and hyperscale data centers. Estimates suggest that modern AI servers use several times more DRAM memory than traditional cloud servers, while each advanced GPU package may contain multiple HBM stacks connected through complex 3D packaging technologies. As generative AI models grow larger and more computationally demanding, memory bandwidth has become one of the most critical bottlenecks in AI infrastructure.
Just a few years back, the memory industry faced collapsing DRAM prices, excess inventory, and weak PC and smartphone demand. SK Hynix reported heavy losses as global chip oversupply intensified. But the AI boom completely reversed the cycle. According to available financial data, the company’s revenue jumped from around $24.9 billion in 2023 to around $48 billion in 2024, while operating profits surged sharply as HBM’s margins expanded. By the first quarter of 2026, reports indicated the company generated around $25 billion in quarterly operating profit alone.
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Ashutosh is a Senior Writer at The Tech Portal, largely reporting on new tech, and intersection of technology and business. Ashutosh’s career spans across nearly a decade of technology writing across multiple platforms and languages.
