Goldman Sachs has significantly revised upward its forecast for the global AI server market, now projecting it will reach $1.24 trillion by 2030 — a figure that underscores the extraordinary scale of infrastructure investment being driven by the AI revolution. The revision reflects the relentless pace of AI capability advancement and the resulting demand for the specialized computing hardware needed to train and deploy increasingly powerful AI systems.
The upward revision comes as hyperscale cloud providers — Amazon Web Services, Microsoft Azure, Google Cloud, and Oracle — race to expand their AI computing capacity to meet surging enterprise demand. These companies have collectively committed hundreds of billions of dollars to data center construction and GPU procurement, with Goldman Sachs estimating that AI-linked companies would invest more than $500 billion in capital spending during 2026 alone.
The firm’s previous forecasts have proven conservative, with actual AI infrastructure spending repeatedly exceeding projections as the pace of AI adoption in enterprise settings outstrips expectations. The revised $1.24 trillion forecast for 2030 reflects a more realistic assessment of how rapidly AI is becoming embedded in business-critical operations across industries from finance and healthcare to manufacturing and logistics.
A key driver of the accelerating forecast is the growth of agentic AI — autonomous AI systems that can take actions, make decisions, and complete complex tasks without human intervention. These systems require substantially more computing infrastructure than conversational AI, as they need to maintain persistent memory, execute multi-step workflows, and interact with external tools and databases continuously.
The AI server market encompasses not just GPU-equipped servers for model training and inference, but also the networking equipment, storage systems, power infrastructure, and cooling technology required to support high-density AI computing. Goldman Sachs notes that as AI workloads intensify, the demand for every component of this ecosystem grows proportionally — from high bandwidth memory chips to specialized optical networking to liquid cooling systems.
Gartner has complemented Goldman Sachs’s market forecast with its own projection that data center power demand will surge 26% in 2026, driven primarily by AI workloads. This energy demand is prompting infrastructure and operations leaders to invest heavily in high-efficiency cooling systems, advanced power delivery, and grid access agreements — investments that further validate the long-term infrastructure spending trajectory that Goldman Sachs’s forecast captures.
