Intel Corporation (INTC.US) "bull market narrative" is becoming increasingly popular! AI reasoning is driving up CPU demand as the 18A advanced process technology gradually enters its prime.

Against the backdrop of a surge in CPU demand in data centers and the advancement of the 18A advanced chip manufacturing process, Wall Street financial giants have shown increasingly bullish sentiment towards the x86 architecture CPU superpower, Intel Corporation (INTC.US), in recent days. Citigroup Group has raised its target price for Intel Corporation from $95 to $130, while another prominent investment firm, Melius Research, has raised its target price from $100 to $150 for Intel Corporation. This highlights the dual ignition and promotion of Intel Corporation's super bull market narrative by the "data center CPU demand frenzy + 18A advanced chip manufacturing process profit prospects continuing to improve". It is reported that Intel Corporation has requested PC manufacturers to use chip products manufactured based on its 18A advanced chip production process. Wedbush Securities, a Wall Street investment behemoth, believes that this is a positive signal that this semiconductor manufacturing giant is prioritizing expanding its profit margins. Wedbush Securities analyst Matt Bryson wrote in a report to clients on Wednesday, "In our view, this strategy is very reasonable, as Intel Corporation should prioritize using older and already expanded process nodes for the production of higher-margin Xeon data center-level CPUs, while Intel Corporation's ability to enable updated capacity (due to its existing clean room space) is a strategic advantage that allows it to leverage this advantage." "In our view, the question is actually how strong the performance of the 18A node and chip products manufactured based on this process are (CEO Chen Liwu recently hinted at rapid yield improvements)." During the 54th Annual Global Technology, Media and Telecommunications Conference hosted by Morgan Stanley on Wall Street, Intel Corporation CEO Chen Liwu stated that Intel 18A (i.e., advanced chip manufacturing process below 2nm) is already supporting mass production of Panther Lake, with yields increasing by about 7% per month, surpassing Intel Corporation's internal expectations. According to the latest developments revealed by Chen Liwu, the 0.5 PDK of Intel 14A has been released, with plans to offer 0.9 PDK to external customers in October, and the team has begun long-term advanced chip manufacturing process planning for the 10A and 7A nodes. Chen Liwu also stated that with the focus of AI computing infrastructure shifting from training to inference, CPUs are becoming increasingly important and indispensable in the AI era, with the ratio of CPU to GPU configuration accelerating from 1:8 to 1:1, and even reaching 4:1. In addition, Intel Corporation's business plan shows that it is actively seeking ASIC business, providing customized AI CPU or AI GPU chip solutions. CPU Renaissance With the launch of Anthropic's Claude Cowork, and the explosion of super AI agents like OpenClaw that can autonomously perform tasks in 2026, the global wave of AI intelligent agents is rapidly sweeping the world. The bottleneck in AI computing architecture is transitioning from GPUs focused on matrix multiplication throughput to data center CPUs focused on control flow, task scheduling, memory/IO coordination, creating a severe situation of supply shortage for high-performance CPUs in large-scale AI data centers. Wall Street analysts are expanding the narrative of AI computing infrastructure from "GPU dominance/single-core driven" to a reevaluation of the full-stack computing power system led by "AI GPU/ASIC+CPU+HBM/DRAM/NAND storage chips+optical interconnection-dominated high-speed data center connectivity system." As AI intelligent agents become popular worldwide, the investment focus of AI computing power is shifting from the "competition around GPU" to the "full-stack computing system driven by AI intelligent agents." The next round of excess alpha returns will no longer be limited to the strongest leaders in the AI GPU/AI ASIC fields but will systematically spread to CPU, storage, PCB, liquid cooling systems, ABF substrates, and extensive wafer foundry services in the full-stack AI computing power infrastructure layer. In this transition of the AI mainstream narrative, CPUs, optical interconnections, and storage chips may be the biggest winners. In the past two years, the AI narrative has been almost monopolized by GPUs, while CPUs have been considered as "supporting characters" in the AI arms race; but with the advent of open source tools like OpenClaw, which are AI intelligent agents dominating the inference workload, data arrangement, task scheduling, memory access, network communication, and multi-tool calls are all significantly increasing, the market has come to realize: without a powerful CPU at the center of the system, GPU clusters cannot operate efficiently. This essentially means that CPUs are returning from being "underestimated infrastructure" to the center stage of chip technology, with clear implications of a "Renaissance" reminiscent of the past. In the early stages, large-scale model inference was mainly based on "single request-single generation," with CPUs mainly handling data transfer, request routing, and basic scheduling, acting as typical auxiliary control surfaces; but in the era of AI intelligent agents and reinforcement learning, the system load transitioned from single forward inference to a complex closed loop encompassing task planning, tool invocation, sub-agent coordination, environmental interaction, state management, and result verification. The "orchestration layer" fundamentally involves CPU-intensive tasks such as strong control flow, branch judgments, system calls, and memory access, which cannot be efficiently replaced by GPUs. Therefore, CPUs are transitioning from their previous "supporting role" to becoming the new bottleneck that determines system throughput, latency, and resource utilization efficiency. Surge in Data Center CPU Demand + Rise of Advanced Chip Manufacturing The 18A can be seen as the manufacturing end verification point for the narrative of "data center CPU demand frenzy + continuous improvement in profit prospects of the 18A advanced chip manufacturing process." Wedbush interprets Intel's request for PC manufacturers to adopt 18A chips as "profit margin protection." The key logic is that Intel Corporation's management is striving to allocate more of the limited older node capacity to high-margin Xeon, server, and industrial clients, while using 18A to handle new client-side products, thereby optimizing capacity allocation and margin structure. Almost simultaneously, Tom's Hardware cited a Nikkei report stating that Intel has redirected its limited Intel 7 capacity towards server and industrial clients, as these areas have higher profit margins, and the demand for AI-driven data center CPUs has been steadily increasing since 2025. Chen Liwu's statement at the 54th Annual Global Technology, Media and Telecommunications Conference hosted by Morgan Stanley is aimed at informing the market that 18A is not just a node on the technology roadmap but is already in the mass production support stage for Panther Lake, with yields increasing by about 7%-8% per month, transitioning from "engineering risks" to "commercially verifiable." If 18A mass production stabilizes, it will not only support PC-side Panther Lake but also establish a trust foundation for future server CPUs, AI head-nodes, ASIC foundries, and 14A customer introductions; this is the core of Intel Corporation being revalued by the market as a "U.S. advanced chip manufacturing vanguard asset," rather than a "lagging process company." At the same time, as AI transitions from training to inference and Agentic AI, the strategic importance of CPUs in AI data centers will significantly increase. While GPUs handle large-scale matrix calculations, CPUs are responsible for scheduling, I/O, memory management, workflow orchestration, security isolation, database access, network stack, and multi-agent workflow execution. As AI applications evolve from "single inference" to "continuous running software labor," CPU demand will shift from traditional server upgrade cycles to AI infrastructure expansion cycles. Citigroup's latest model also echoes this point: it predicts that the total potential market size of data center server CPUs [i.e., CPU TAM] will expand from $29.3 billion in 2025 to $131.5 billion in 2030, with a compound annual growth rate of approximately 35%, leading the institution to raise its target price for Intel Corporation from $95 to $130. The highest target price of $150 from Wall Street comes from star analyst Ben Reitzes of Melius Research. Melius includes Intel Corporation in its reevaluation framework of AI semiconductor "bottleneck assets." Reitzes believes that as the demand for AI computing infrastructure continues to face supply bottlenecks, semiconductor companies such as Intel Corporation that focus on AI computing bottlenecks will have more market value or potential for growth compared to traditional software companies and non-semiconductor "big tech giants." In terms of Intel Corporation's fundamentals, Melius' logic mainly centers around two points: first, Agentic AI is driving a renewed acceleration in x86 server CPU demand, with the transition of AI from training to inference and intelligent agent execution requiring more CPUs to handle scheduling, I/O, memory management, workflow orchestration, and security control; second, there is potential for significant growth value release in Intel Foundry (i.e., Intel Corporation's advanced chip manufacturing outsourcing business) under the leadership of Chen Liwu.