然而，无论是《赢得竞赛：美国人工智能行动计划》还是如今的"创世纪计划"，特朗普政府想要发展AI 技术的雄心面临着现实因素的掣肘。值得注意的是，当前全球AI发展十分迅猛，但更好的性能需要更 多的模型、数据以及算力。然而，想要训练大模型，建设和发展数据中心，都离不开大量的能源消耗， 这种消耗大量能源的模式是不可持续的。 加拿大卡车自动驾驶公司Waabi的创始人兼首席执行官拉克尔.乌尔塔森曾表示，据估计，一个大型语言 模型(LLM)单次训练所消耗的电量相当于130户美国家庭一年的用电量。随着模型变得更加庞大，这一 数字还会继续增加。 更重要的是，大力发展AI对美国经济而言并非百利而无一害。对于美国的劳动力市场，有分析指出， AI的迅速发展和普及正在削弱劳动力需求。对于一些初级的入门岗位，都可以使用AI，这让很多刚毕 业的大学生很难找到合适的工作。 国金证券在《全景式扫描AI对美国经济的影响》研究报告中指出，2022年的AI横空出世产生了"影子财 政"的效果，而2025年行业头部企业开始缩圈，聚合产业资源并持续宣布长远的规划则更像是"影子财政 2.0"。对实体经济而言，AI支出的退坡和放缓对美国经济的打击要远胜于已经 ...

Economic Impact of AI - AI-related investments contributed 1.57 percentage points to the US GDP growth in the first half of 2025, surpassing the contribution from private consumption at 1.06 percentage points[6] - In Q1 2025, AI investments boosted GDP growth by 1.3 percentage points, exceeding the peak contribution during the dot-com bubble (1.16 percentage points in Q2 1999)[6] - The nominal value added from data processing services increased to 1.75% of GDP, up from an average of 1.04% from 2013-2019, while manufacturing's share fell to 9.98%, marking a significant decline[12] AI and Employment - The penetration rate of AI technology in the workforce remains low, with only 6 out of 20 major industries exceeding a 10% usage rate, the highest being the IT sector at approximately 25%[43] - Job losses attributed to AI are overstated; the primary reasons for layoffs are related to macroeconomic factors rather than direct AI impacts[48] - AI's influence on hiring plans is evident, with companies likely to hire fewer employees in the future, but current layoffs are more linked to economic cycles[43] Financial Sector Vulnerabilities - In 2025, the total bond issuance by major tech firms reached $103.8 billion, indicating a growing reliance on external financing amid concerns over the sustainability of AI investments[78] - The private credit market has seen significant growth, with total assets under management rising from approximately $100 billion in 2010 to nearly $2.2 trillion by 2024[80] - The increasing dependence on private credit raises concerns about transparency and risk, particularly as tech firms face pressures to demonstrate profitability[79]