No signs of AI payoff outside the tech sector
No signs of AI payoff outside the tech sector
Partner, Chief Economist
合伙人，首席经济学家
Despite massive investments and widespread hype around artificial intelligence, the technology has delivered zero financial payoff to corporate America outside of tech. Revenue per worker is rising for the Mag 7 but is flat for the S&P 493, see the first chart below. Profit margins are rising for the Mag 7 but are flat for the S&P 493, see the second chart below. And there are still no signs of AI boosting productivity growth, see the third chart below. With no impact on the bottom line, mainstream corporate America is pulling back and starting to view token spending not as a source of growth but as a cost center that weighs on margins.
尽管在人工智能领域投入了巨额资金并进行了广泛的炒作，但该技术在科技行业之外尚未给美国企业带来任何财务回报。“七巨头”（Mag 7）的员工人均收入正在上升，但标普 493 指数成分股的这一指标却持平（见下方第一张图表）。“七巨头”的利润率在上升，而标普 493 指数成分股的利润率则持平（见下方第二张图表）。此外，目前仍没有迹象表明人工智能正在推动生产力增长（见下方第三张图表）。由于对净利润没有影响，主流美国企业正在缩减投入，并开始将代币支出视为拖累利润率的成本中心，而非增长源泉。
VC-backed companies are spending more and more on tokens, but mainstream corporate America does not need the latest model and is unwilling to pay for it. As long as agentic AI and token spending are confined to a small part of the economy, the macroeconomic effects of AI will be very limited, see the fourth and fifth charts below.
风险投资支持的公司在代币上的支出越来越多，但主流美国企业并不需要最新的模型，也不愿为此买单。只要代理人工智能（agentic AI）和代币支出仅局限于经济的一小部分，人工智能的宏观经济效应就将非常有限（见下方第四和第五张图表）。
The question looking ahead is whether, even as models become commoditized, mainstream corporate America can turn increasingly cheap intelligence into higher revenue growth and higher profit margins. That may be harder than it sounds. AI may be a great calculator, but in business, intelligence is mostly judgment. Judgment depends on context, and the answer varies with which human or which model you ask. Perhaps most importantly, AI does not understand accountability, trust, culture, unwritten rules, ethical trade-offs or fairness, all of which shape reputational risk and ultimately drive revenue growth and profit margins.
展望未来，问题在于即使模型变得商品化，主流美国企业能否将日益廉价的智能转化为更高的收入增长和利润率。这可能比听起来更难。人工智能或许是一个出色的计算器，但在商业中，智能更多地体现为判断力。判断力取决于背景，而答案会因你询问的对象（无论是人类还是模型）而异。或许最重要的是，人工智能无法理解责任、信任、文化、潜规则、道德权衡或公平性，而所有这些因素都塑造了声誉风险，并最终驱动着收入增长和利润率。
The bottom line is that the AI story will be decided in the S&P 493, not the Mag 7, and so far, there is no evidence that revenue growth or margins are improving outside the tech sector.
归根结底，人工智能的故事将由标普 493 指数成分股而非“七巨头”来决定，而到目前为止，没有证据表明科技行业之外的收入增长或利润率正在改善。
Note: Inflation adjusted to 2019 Q4. Sources: Bloomberg, Macrobond, Apollo Chief Economist
注：通胀调整至 2019 年第四季度。资料来源：彭博社、Macrobond、阿波罗首席经济学家。
Sources: Bloomberg, Macrobond, Apollo Chief Economist
资料来源：彭博社、Macrobond、阿波罗首席经济学家。
Note: Total Factor Productivity (TFP) is the utilization-adjusted series from the San Francisco Fed (Fernald, 2014), adjusted for cyclical variation in factor utilization. Sources: Federal Reserve Bank of San Francisco, US Bureau of Labor Statistics, Apollo Chief Economist
注：全要素生产率（TFP）采用旧金山联储（Fernald, 2014）的利用率调整序列，并针对要素利用率的周期性变化进行了调整。资料来源：旧金山联邦储备银行、美国劳工统计局、阿波罗首席经济学家。
Sources: Ara Kharazian, Chief Economist, Ramp; Apollo Chief Economist
资料来源：Ramp 首席经济学家 Ara Kharazian；阿波罗首席经济学家。
Sources: Ramp AI Index, Apollo Chief Economist
资料来源：Ramp AI 指数、阿波罗首席经济学家。
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