Gartner 警告 3.5 万亿美元 AI 基础设施支出到 2030 年底可能减值
Gartner Warns $3.5 Trillion of AI Infra Spending Vulnerable to Diminishing by 2030-End
Gartner 预计，若 AI 供应商维持当前资本支出轨迹，到 2030 年底将有超过 3.5 万亿美元的 AI 基础设施支出减值。其研究显示，2026 年 AI 供应商预计在 AI 基础设施上花费近 1 万亿美元，2027 至 2030 年还将追加投资 6 万亿美元，而同期可归属于 AI 数据中心的整体企业及消费者 AI 收入预计上限为 3.6 万亿美元。Gartner 还预计，到 2032 年可能有超过 4 万亿美元资产价值面临减值风险，且超过 80% 的 neocloud 供应商将因缺乏差异化商业模式和成本压力而停止运营。
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By the end of 2030, Gartner, Inc., a business and technology insights company, expects that more than $3.5 trillion of AI infrastructure spending will diminish on the condition that AI providers maintain their current trajectory of capital spending
“In 2026, AI providers are expected to spend nearly $1 trillion on AI infrastructure, and are forecast to invest an additional $6 trillion between 2027 and 2030,” said Will Sommer, Senior Director Analyst at Gartner.
Their research suggests current enterprise and consumer AI revenue won’t support profitable returns on planned AI capital expenditure during this period.
Through 2030, AI data centre owners must generate a cumulative $8.5 trillion in revenue to cover announced capital spending, financing costs, and a 12% return on invested capital (ROIC), which Gartner Inc. assumes is the “hurdle rate of investment capital”, according to Sommer.
Total enterprise and consumer AI revenue that can be attributed to AI data centres during this period is forecast to cap at $3.6 trillion. Since most AI-native providers operate asset-light business models, providers that own significant AI infrastructure are expected to earn less than half of AI revenue.
If ROIC isn’t sustainable on rapidly depreciating assets, write-downs can certainly compensate. Based on Gartner projections, a continued AI infrastructure investment trajectory could leave more than $4 trillion in asset value exposed to write-down risk through 2032.
In this scenario, Gartner does not expect the 12% ROIC to be achieved until the end of 2032 at the earliest.
Neoclouds will be vulnerable to the imbalance between revenue and capital spending. Hyperscalers, for example, have massive and highly diversified revenue sources that could plausibly sustain AI investments for years. On the other hand, neoclouds must soon earn returns on AI-optimised IaaS and associated platforms to sustain operations.
Gartner estimates AI-optimised IaaS spending will grow from $66 billion in 2027 to $174 billion in 2030.
Gartner predicts that over 80% of neocloud providers will cease operations due to the lack of differentiating business models and cost pressure.