Morgan Stanley analysis predicts agentic AI will shift enterprise value from GPUs to CPUs and memory, potentially creating $60 billion incremental CPU TAM by 2030.
As artificial intelligence evolves from single-task generation to autonomous, multi-step "agentic" systems, the economic value of AI infrastructure is undergoing a fundamental shift. Morgan Stanley's latest research reveals that CPUs and memory, rather than GPUs alone, are emerging as critical bottlenecks in this next phase. "Agentic AI widens the trade beyond GPUs, with CPUs becoming the control plane for multi-step workflows and system orchestration," the report noted. The transition marks a structural pivot from raw compute to orchestration, with each model call now requiring greater coordination, persistent memory and system-level processing—widening the overall AI spend pool beyond accelerators.
Morgan Stanley quantifies this opportunity through a new analytical framework. CPU-side orchestration accounts for 50–90% of total workload latency in agentic systems, materially raising general-purpose compute intensity. The brokerage estimates $32.5–60 billion of incremental CPU total addressable market by 2030, within a broader server CPU TAM exceeding $100 billion. On the memory side, agentic workloads could drive 15–45 exabytes of additional DRAM demand by 2030, equivalent to 26–77% of 2027 annual DRAM supply.
The architecture of AI clusters themselves is shifting to accommodate agentic workloads. Rather than GPU-dominated designs, systems are moving toward CPU-centric or hybrid configurations to manage reasoning, tool execution and memory orchestration, pushing the CPU-to-GPU ratio higher at the cluster level. Memory is no longer passive storage but an active system component supporting persistent context and continuous learning, driving broader infrastructure demand across CPUs, DRAM, foundry capacity, ABF substrates and interconnect layers.
The investment implications extend across the full technology stack. "Supply-constrained enablers (foundry, ABF, BMC, interconnect) should capture outsized economics as system complexity rises," Morgan Stanley said. CPU vendors, memory suppliers, storage companies, advanced packaging and substrate providers, foundries, equipment makers and server manufacturers all stand to benefit. The outlook suggests a significant rebalancing within semiconductors, with Morgan Stanley projecting orchestration CPUs will carve out an $82.5–110 billion data center market by 2030, with agentic workloads contributing the bulk of incremental growth. "The beneficiaries of this shift are global and full-stack," the report concluded, emphasizing that winners will be those delivering end-to-end system efficiency rather than point solutions. Over the next five years, CPUs and memory could rival GPUs as the primary drivers of AI-related semiconductor revenue growth.