在2026外滩年会上，全球金融决策者围绕人工智能投资的宏观经济效应展开讨论。美国前财政部长罗伯特·鲁宾表示，"不能寄希望于技术进步自动消化债务压力"1。哈佛大学教授杰森·弗曼指出，过去五年美国累计生产率增长中，AI的贡献可能仅为0.5至1个百分点，"也不排除实际贡献为零"1。AI的生产率贡献仍存疑虑，且可能被就业替代和风险成本抵消1。
巨大的资金投入与宏观回报之间存在明显时间差。人民银行原行长周小川指出，"如今有如此巨额的资金流向人工智能及相关基础设施"1，但这些投资的宏观税收回报尚未兑现。数据中心扩张成为资金流向的重要载体，全球数据中心用电量预计将从2024年的415太瓦时增至2030年的约945太瓦时，增幅超过一倍1。
Global financial and fiscal leaders gathered at the 2026 Bund Conference to examine whether artificial intelligence investments are delivering promised economic benefits. The discussion, held October 19-22 and organized by the China Finance Forty Forum and Tsinghua University, revealed significant uncertainty about AI's actual contribution to productivity and broader economic returns 1.
Former U.S. Treasury Secretary Robert Rubin cautioned against assuming technological progress would automatically resolve fiscal pressures, stating "we cannot rely on technological advancement to automatically absorb debt pressures" 1. Harvard University professor Jason Furman offered a more precise assessment, estimating that AI may have contributed between 0.5 and 1 percentage point to cumulative U.S. productivity growth over the past five years, while noting that "it is not ruled out that the actual contribution could be zero" 1. These skeptical views reflected concerns that AI's productivity gains could be offset by job displacement and other costs.
The scale of capital deployment underscores the urgency of these questions. Global data center electricity consumption is projected to surge from 415 terawatt-hours in 2024 to approximately 945 terawatt-hours by 2030, more than doubling in just six years 1. Despite this massive infrastructure investment, Zhou Xiaochuan, former governor of the People's Bank of China, highlighted a critical timing mismatch: enormous amounts of capital are now flowing into artificial intelligence and related infrastructure, yet the macroeconomic tax returns have not materialized 1. This gap between microeconomic efficiency gains and macroeconomic returns remains a central puzzle for policymakers assessing whether current AI investment levels are economically justified.
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