In short
Chipflation—memory chips (DRAM, NAND, and AI-specific HBM/HPM) stop getting cheaper, become scarce, and drive up costs due to AI infrastructure demand.
Guest backgrounds
No guests mentioned; host is Shawn Kim, head of Morgan Stanley’s Europe and Asia technology team.
Key claims
Memory prices rose more than sixfold in the last year; AI is memory-hungry (new AI chips use ~7x more HPM; full systems ~65x more). Demand shifts: server DRAM demand to ~59% by 2028 (from 37% in 2023) and enterprise SSD/NAND to ~65% (from 18%). Supply can’t ramp quickly, creating a two-tier market (long-term/prepaid priority for large AI/cloud buyers).
Notable examples
potential 2027 PC memory shortfall ~15% (~58M PCs) and smartphone shortfall ~12% (~134M units); memory market growing ~$220B (2025) to ~$890B (2026).
Written by AI. May contain mistakes. Listen to the episode to check what was said.
Chapters
Tap a time to open that second in VOUnderstanding Memory Chips
0:20 to 1:06
An overview of different types of memory chips and their roles.
“It holds whatever the machine needs at that moment, whether that is a web search, a video, a spreadsheet, or an AI model answering a question.”
The Rise in Memory Demand
1:06 to 2:14
Exploring the increasing demand for memory chips driven by AI.
“a sharp break from decades when the cost of DRAM generally kept falling.”
The Impact of Memory Shortages
2:14 to 3:02
Consequences of memory shortages on various industries and pricing.
“Large AI and cloud buyers can sign long-term agreements, prepay, and secure priority access.”
Economic Implications of Rising Memory Costs
3:02 to 3:48
Assessing the broader economic impact of memory chip pricing trends.
“Expectations for 2026 memory revenues rose 71 % in just three months.”
Transcript
Automatic transcript. May contain errors.0:00Shawn Kim:Welcome to Thoughts on the Market. I'm Shawn Kim, head of Morgan Stanley's Europe and Asia technology team. Today, we're talking about chipflation, when memory chips stop getting cheaper over time and become more expensive and even harder to find. It's Monday, June 8th at 3 p.m. in London. Memory chips are easy to ignore until your laptop slows down, your phone costs more, or your cloud build jumps. Memory is the computer's workspace. It holds whatever the machine needs at that moment, whether that is a web search, a video, a spreadsheet, or an AI model answering a question. DRAM is a fast memory inside servers, PCs, and phones.
0:44Shawn Kim:NAND is what stores files in a solid-state drive. An HBM, or high bandwidth memory, is the high-performance version sitting right next to the AI chip, helping them move huge amount of data quickly. The last one, HPM, is key because AI has become intensely memory hungry. Memory prices have risen more than sixfold over the last year, a sharp break from decades when the cost of DRAM generally kept falling. The pressure is coming from AI infrastructure build-outs. We see server accounting for about 59 % of DRAM demand by 2028, up from 37 % in 2023. We also see enterprise solid-state drive reaching 65 % of NAND demand, up from 18%.
1:29Shawn Kim:And simply put, data centers are taking a much bigger share of the memory pie. AI memory use is climbing fast, at every scale. A newer AI chips uses 7 times more HPM than early generations. A full system uses about 65 times more. Across an entire AI data center build-out, the jump gets even bigger. HVM has gone roughly from 10 terabytes in 2020 to about 18 petabytes in 2026, orders of magnitude more. This demand is running into supply chain that cannot respond quickly. New memory capacity takes years to build, qualify, and ramp up. Supply relief is a process, not a switch. And that creates a two-tier market.
2:18Shawn Kim:Large AI and cloud buyers can sign long-term agreements, prepay, and secure priority access. Traditional buyers, including PC makers, smartphone makers, and industrial hardware companies must compete for what remains. This impacts everyday products. In 2027, we see PC memory demand potentially facing a 15 % shortfall, equivalent to about 58 million PCs. Smartphones could face a 12 % shortfall, equivalent to about 134 million units. Companies may have to raise prices, cut specifications, delay launches, and accept lower profits. The dollar number is striking. We see the memory market growing from about$220 billion in 2025 to about$890 billion in 2026.
3:10Shawn Kim:Expectations for 2026 memory revenues rose 71 % in just three months. That implies roughly$600 billion of incremental memory revenues in 2026, more than the annual market for smartphones, PCs, or servers, each taken on its own. The broader economy may not see a significant direct inflation shock. We estimate the direct impact on headline CPI at about 0.1 % in 2026, but the pressure is showing up in producer prices, in corporate margins, cloud costs, capital spending plans, and delayed technology upgrades. AI has turned memory from the cheapest part of the digital economy into one of its most contested resources.
3:55Shawn Kim:These tiny chips most people never think of may now decide what gets built or delayed and how much we all end up paying. thanks for listening if you enjoyed the show please leave us a review wherever you listen and share thoughts on the market with a friend or colleague today
4:15the preceding content is informational only and based on information available when created it is not an offer or solicitation nor is it tax or legal advice it does not consider your financial circumstances and objectives and may not be suitable for you
From the publisher
The Head of our Europe and Asia Technology Team, Shawn Kim, explains how AI’s appetite for memory chips is boosting the cost of everything from data centers to smartphones, with consequences that may reach far beyond the tech industry.
Read more insights from Morgan Stanley.
----- Transcript -----
Shawn Kim: Welcome to Thoughts on the Market. I’m Shawn Kim, Head of Morgan Stanley’s Europe and Asia Technology Team.
Today, we’re talking about chipflation – when memory chips stop getting cheaper over time, and become more expensive and even harder to find.
It’s Monday, June 8th, at 3pm in London.
Memory chips are easy to ignore, until your laptop slows down, your phone costs more, or your cloud bill jumps.
Memory is the computer’s workspace. It holds whatever the machine needs at that moment, whether that is a web search, a video, a spreadsheet, or an AI model answering a question. DRAM is the fast memory inside servers, PCs and phones. NAND is what stores files in solid-state drives. And HBM, or high bandwidth memory, is the high-performance version sitting right next to the AI chip, helping them move huge amounts of data quickly.
That last one – HBM – is key because AI has become intensely memory hungry. Memory prices have risen more than six-fold over the last year, a sharp break from decades when the cost of DRAM generally kept falling.
The pressure is coming from AI infrastructure buildouts. We see servers accounting for 59 percent of DRAM demand by 2028, up from 37 percent in 2023. We also see enterprise solid-state drives reaching 65 percent of NAND demand, up from 18 percent. And simply put, data centers are taking a much bigger share of the memory pie.
AI memory use is climbing fast, and at every scale. A newer AI chip uses 7.2 times more HBM than earlier generations. A full system uses about 65 times more. Across an entire AI data center buildout, the jump gets even bigger. HBM has gone from roughly 10 terabytes in 2020 to about 18 petabytes in 2026, orders of magnitude more.
This demand is running into a supply chain that cannot respond quickly. New memory capacity takes years to build, qualify and ramp up. Supply relief is a process, not a switch. And that creates a two-tier market. Large AI and cloud buyers can sign long-term agreements, prepay and secure priority access. Traditional buyers, including PC makers, smartphone makers and industrial hardware companies, must compete for what remains.
This impacts everyday products. In 2027, we see PC memory demand potentially facing a 15 percent shortfall, equivalent to about 58 million PCs. Smartphones could face a 12 percent shortfall, equivalent to about 134 million units. Companies may have to raise prices, cut specifications, delay launches, and accept lower profits.
The dollar numbers are striking. We see the memory market growing from about $220 USD billion in 2025 to about $890 billion in 2026. Expectations for 2026 memory revenue rose 71 percent in just three months. That implies roughly $600 USD billion of incremental memory revenue in 2026, more than the annual market for smartphones, PCs, or servers, each taken on its own.
The broader economy may not see a significant direct inflation shock. We estimate the direct impact on headline CPI at about 0.1 percent in 2026. But pressure is showing up in producer prices, in corporate margins, cloud costs, capital spending plans and delayed technology upgrades.
AI has turned memory from the cheapest part of the digital economy into one of its most contested resources. These tiny chips most people never think of may now decide what gets built or delayed, and how much we all end up paying.
Thanks for listening. If you enjoy the show, please leave us a review wherever you listen and share Thoughts on the Market with a friend or colleague today.