AI Has Made Memory Chips One of the World's Most Profitable Products (8 minute read)
Memory chip makers are posting record-breaking profits as AI demand pushes Samsung, SK Hynix, and Micron into the ranks of the world's most profitable companies.
What: Samsung reported first-quarter 2026 net profit exceeding $30 billion (94% from semiconductors), with the three major memory chip makers collectively projected to generate roughly $350 billion in net profit for the year—vaulting Samsung past Alphabet, Microsoft, and Apple to become the world's second-most profitable company.
Why it matters: The profit explosion stems from a supply crunch where memory makers prioritized specialized high-bandwidth memory (HBM) for AI training, constraining conventional memory chips, while inference workloads for deployed AI models are now driving additional demand for general-purpose server memory—creating a "super boom cycle" expected to intensify next year.
Deep dive
- Memory prices in Q1 2026 grew nearly 100% quarter-over-quarter, roughly double the initially projected 50% increase, according to TrendForce
- Samsung's Q1 2026 net profit of $30 billion exceeded not only its prior quarterly record but nearly matched its historical high for an entire year
- The three memory chip makers (Samsung 36% market share, SK Hynix 32%, Micron 22% for DRAM) are expected to rank among the world's top 10 most profitable companies in 2026—none cracked the top 10 a year ago
- Samsung shares have risen 72% since the start of 2026, SK Hynix up 90%, and Micron up 65%
- The supply crunch is expected to worsen in 2027, with Samsung stating "available supply is far short of customer demand" based on prebooked orders
- The profit surge follows a two-phase demand pattern: first, specialized HBM production for AI training (paired with Nvidia GPUs) constrained conventional memory supply
- Second, inference workloads for deployed AI models sparked additional demand for general servers using conventional DRAM and NAND flash memory
- The three companies collectively control the overwhelming majority of both DRAM (90%) and NAND flash (55%) markets
- While questions persist about whether AI services will generate commensurate profits, infrastructure providers are capturing an "epic windfall"
- Memory makers gave priority to HBM production over conventional chips used in smartphones, PCs, and general servers, creating the supply constraint that drove prices up
Decoder
- HBM (High-Bandwidth Memory): Specialized memory chips designed for AI training workloads, typically paired with Nvidia GPUs for training large language models
- DRAM: Dynamic random-access memory, the main volatile memory used in computers and servers for active tasks
- NAND flash: Non-volatile memory used for storage in SSDs, smartphones, and data centers
- Inference: The phase of AI computing where trained models respond to user queries, as opposed to training new models
- LLM (Large Language Model): AI models like GPT that require massive memory during training
Original article
The AI boom has pushed the memory-chip industry into a super boom cycle with record-smashing profits. Samsung has reported first-quarter net profit equivalent to more than $30 billion, blowing away its prior quarterly record and almost topping the company's high for full-year profit. The historic run doesn't look likely to end soon. The supply crunch is expected to grow worse next year.