Gartner：AI 数据中心资本开支到 2030 年将远超可回收收入
AI datacenter capex will far exceed forecast revenue through 2030
Gartner 预计，AI 数据中心到 2030 年需要产生 8.5 万亿美元收入才能覆盖已宣布的资本开支、融资成本和预期投资回报，而同期可归属于 AI 数据中心的全部企业与消费者 AI 收入预计不超过 3.6 万亿美元。Gartner 高级总监分析师 Will Sommer 表示，这一期间的企业与消费者 AI 收入不足以支撑所有已规划 AI 资本开支取得盈利回报。Gartner 还指出，成本压力将迫使超过 80% 的 neocloud 提供商停止独立运营，而超大规模厂商有能力消化这些财务压力。
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Investors are pouring more into AI data center infrastructure than they can hope to recoup by 2030, according to Gartner.
“Enterprise and consumer AI revenue will be insufficient to support profitable returns on all planned AI capital expenditures during this period,” said Gartner Senior Director Analyst Will Sommer.
AI data center owners would need to generate $8.5 trillion in revenue through 2030 to cover announced capital spending, financing costs and expected investment returns, he said. “However, total enterprise and consumer AI revenue that can be attributed to AI data centers during this period is forecast to reach no more than $3.6 trillion.”
Gartner joins a growing chorus warning that major AI players may be over-committing themselves. Bain and Co. recently made a similar forecast, estimating that annual spending on AI infrastructure could reach $1.5 trillion by 2031 and that the AI services market would need to top $6 trillion annually to pay for it.
This is particularly bad news for neocloud providers, said Gartner. While the hyperscalers are large enough to absorb the financial pressures, the research company suggests that the cost pressure will force more than 80% of neocloud providers to cease independent operations.
The Bain and Gartner surveys don’t cover quite the same ground, but their conclusions are very similar: a lot of AI infrastructure investment is never going to make a return, and companies need to prepare themselves for some degree of financial loss.
This article first appeared on Network World.