AMD Price Target Jumps to $720 as Bank Forecasts AI CPU Market to Triple by 2030

AMD Joins $1 Trillion Club as BofA Lifts Price Target to $720

Advanced Micro Devices (AMD) reached a $1 trillion market capitalization this week, becoming the latest semiconductor company to hit this milestone2

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. BofA Securities analyst Vivek Arya responded by raising his AMD price target from $620 to $720 while maintaining a Buy rating, naming AMD as the firm's top CPU pick1

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. The new target implies AMD's market cap could climb to approximately $1.2 trillion over the next 12 months, representing about 14% upside from the stock's recent close of $629.261

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. The upgrade reflects BofA's projection that the server CPU market will triple as agentic AI transforms how data centers balance workloads between CPUs and GPUs.

Server CPU Market Projected to Reach $211 Billion by 2030

BofA Securities models the server CPU total addressable market growing dramatically from $61.4 billion in 2026 to $210.6 billion in 20301

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. AI-related chips would account for 86% of that total, up from 69% this year, with approximately $180 billion driven by AI workloads1

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. The bank forecasts AI CPU units rising from 16 million to 53 million over the same period, reaching roughly 1.5 times accelerator units by 2030 versus about 0.7 times today1

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. Average selling prices for server CPUs are expected to climb from approximately $1,600 in 2026 to approximately $2,600 in 2030, with high-end AI CPU package values potentially reaching $4,000-$5,000 or more2

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. This price expansion stems from the mix shift toward higher-value AI configurations as data centers optimize for agentic workloads.

Agentic AI Makes CPU and GPU Demand Symbiotic

The upgrade centers on how agentic AI fundamentally changes the relationship between CPUs and GPUs in AI systems. Ben Bajarin, CEO and Principal Analyst at Creative Strategies, explained during a BofA-hosted investor call that while GPUs handle token generation in AI inference, CPUs execute the resulting tasks including tool calls, code execution, retrieval, and database interactions1

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. A slow CPU leaves expensive GPUs waiting idle, degrading both system performance and user experience. "Agentic AI makes CPU/GPU demand symbiotic," Arya noted, emphasizing that CPU latency and task-completion speed are increasingly critical to GPU utilization1

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. BofA's framework moves away from simple CPU-to-GPU ratios toward assessing how many tasks GPUs initiate, how many CPUs can execute concurrently, and how quickly results return to the GPU2

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. This shift means CPUs expand the AI system TAM rather than substitute for accelerators, rejecting the zero-sum view of CPU versus GPU competition2

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Anthropic Deal Validates CPU Infrastructure Thesis

Real-world deployments already support BofA's thesis about growing CPU importance in AI infrastructure. Akamai Technologies announced an $11.6 billion, seven-year agreement with Anthropic specifically aimed at supporting growing CPU workloads, with the potential to expand by another $9 billion to reach a $20 billion commitment1

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. This deal demonstrates that the scarce resource in AI systems is no longer simply GPU calculation capacity but how quickly the entire system can keep expensive GPUs productive1

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. Meta's Muse product was also cited as evidence of the CPU's expanding role in AI systems, though BofA cautioned that Meta's CPU-rich setup may not reflect GPU-heavy operators more broadly2

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. These deployments signal a fundamental shift in how hyperscalers and cloud providers architect AI infrastructure, with implications for semiconductor demand patterns through the end of the decade.

AMD Positioned with Broadest CPU Portfolio for AI Era

Chip designers are pursuing different architectural approaches to meet agentic AI demands. Nvidia favors fewer, faster cores that hand results back to GPUs quickly, while ARM Holdings is planning chips with more cores to run multiple tasks concurrently1

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. According to Arya, AMD offers the broadest portfolio across both x86 architecture and emerging approaches, positioning it as the most direct equity expression of the server CPU market expansion1

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. BofA notes that x86 should remain entrenched in legacy cloud and enterprise software environments, while ARM is best positioned for greenfield AI workloads, with Bajarin projecting ARM-based server CPU unit share approaching 40% by decade-end2

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. For this reason, Arya raised his 2027 and 2028 estimates by 2% to 3% and lifted his valuation multiple on AMD to 30 times 2028 earnings from 27 times1

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. AMD's competitive x86 server CPU lineup and growing share in AI-optimized data center configurations make it well-positioned to capture value as the market expands. Watch for AMD's roadmap execution as agentic AI deployments scale and any updates to hyperscaler capital expenditure plans that could accelerate or delay the projected TAM ramp through 2030.