Morgan Stanley is telling investors that the AI infrastructure buildout has entered a new phase, one where the bottleneck is no longer just graphics processing units (GPUs)
In a new episode of the bank’s Thoughts on the Market podcast, Shawn Kim, Morgan Stanley’s head of Europe and Asia Technology Research, says the AI use case is transitioning from chatbots to agents, shifting hardware requirements from GPUs to central processing units (CPUs).
According to Kim, CPUs allow AI agents to remember instructions, understand user preferences, work across digital tools, plan workflows and adapt as circumstances change.
“Agentic AI also depends on three stacks: the brain, or the large language model, orchestration, where the CPU manages the doing, and knowledge, which is memory. Memory may be the most important layer. An agent that knows your preferences doesn’t tone, and task history becomes more useful over time. That creates a context flywheel. The more context it collects, the more personalized it becomes, and the harder it is to leave.”
With the shift in hardware requirements, Kim notes that it creates a new multi-year opportunity for investors.
“For investors, the implication is clear. Agentic AI changes the bottlenecks. We see CPUs as a new bottleneck, with memory seeing the highest content increase. We estimate as much as 60 % or $60 billion of incremental CPU total addressable market by 2030, within a total CPU market of more than $100 billion. We also estimate up to 70 % of incremental DRAM bit shipment tied to this theme. That makes us more positive on the supply chain, including memory, foundry, substrate, CPU and memory interface, and capacitors and CPU sockets. These areas benefit from content growth, pricing power, and capacity constraints into 2027.”
Some stocks that could benefit from the shift include AMD (AMD) and Intel (INTC), and both have been up and up as of late. AMD is up over 88% from its March lows, while INTC has surged more than 160% over the same period.
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