Bank of America has increased its outlook for the artificial intelligence data center systems market to about $1.7 trillion by 2030, up from a prior estimate of $1.4 trillion, implying a compound annual growth rate of 45% through the decade.
The bank highlighted expectations for accelerating AI sales and returns on that investment beginning in 2026. It identified upcoming initial public offerings from OpenAI and Anthropic as events that could improve market prospects. For 2027, the bank anticipates improvements in tokenomics and efficiency as new compute and memory architectures reach the market.
Specific segment-level revisions were significant. The AI accelerator market outlook was raised to roughly $1.2 trillion from $1.0 trillion, a move the bank attributes to stronger shipments of hyperscaler custom ASICs, including products such as Google TPU and AWS Trainium. Data center server CPU forecasts rose to about $110 billion, with AI CPUs now expected to represent $88 billion of that total, increased from a prior AI CPU estimate of $80 billion. The bank also lifted its AI networking forecast to around $316 billion from $240 billion.
Bank of America noted that as AI workload requirements broaden, diversification across compute and memory components will add to overall market value. The analysis envisions CPUs operating alongside existing GPU-CPU compute racks. It also expects SRAM-based ultra-low-latency memory racks to coexist with HBM-based GPU racks as different architectures serve distinct performance needs.
The research house updated company-level valuations based on these market changes. Micron Technology received a new price target of $950, up from $500, using a sum-of-parts approach that values the sustainable AI and HBM business at about $240 per share and the traditional DRAM and NAND business at roughly $710 per share.
The bank listed several top equity picks tied to the AI data center opportunity. Nvidia saw its price target raised to $320 from $300. Other top picks named include Broadcom, Micron, Advanced Micro Devices and Marvell Technology, with Marvell's target increased to $200 from $125.
Market context and implications
The revisions indicate a materially larger addressable market for hardware supporting AI workloads, driven by custom accelerators, increasing AI CPU penetration, and expanded networking requirements. The bank's stance links anticipated product rollouts and hyperscaler deployments to near- and medium-term revenue growth across semiconductor suppliers.