Semiconductor Sector Rebounds as Samsung Predicts AI Chip Shortage Until 2028
By TopHolding Editorial · Sunday, August 2, 2026 at 9:01 PM
Chip stocks see a $1 trillion selloff followed by a sharp recovery as Samsung and SK Hynix report record profits amid a persistent AI component shortage.
The global semiconductor industry is navigating a period of intense volatility as the 'AI trade' matures. After a brutal selloff that saw chip stocks shed more than $1 trillion in market value, the sector experienced a sharp relief rally this week. The rebound was spearheaded by Lam Research, which surged 17%, and memory giants Micron and AMD, following strong earnings results that reassured investors about the durability of hardware demand.
In South Korea, industry leaders Samsung Electronics and SK Hynix reported record-breaking figures, though the market's reaction was mixed. Samsung posted a massive surge in operating profit, driven by all-time high sales in DRAM and NAND flash memory. The company issued a bullish long-term outlook, predicting that the current 'chip crunch'—a shortage of high-end AI components—could persist until 2028. This suggests that the structural demand for AI infrastructure remains vastly undersupplied.
However, the bar for success has risen to extraordinary levels. SK Hynix saw its shares fall despite reporting a 257% jump in revenue and a staggering 557% increase in operating profit. The dip was attributed to results that narrowly missed even higher 'whisper numbers' from analysts and concerns over the rising costs of producing High Bandwidth Memory (HBM). SK Hynix, which recently secured a $500 billion multi-year supply deal with Nvidia, remains at the center of the AI supply chain, yet its stock performance highlights a growing sensitivity to any signs of deceleration.
The broader market landscape is also shifting. Apple recently reclaimed its title as the world's most valuable company, surpassing Nvidia as investors rotated slightly back toward consumer hardware stability. As the industry evolves, analysts are now looking beyond just chip design to other bottlenecks, such as energy supply and data center utility capacity, which are increasingly seen as the primary constraints on the next phase of AI growth.