阿波罗分析显示除了最大的科技巨头之外没人会从AI那里得到好处
尽管在人工智能领域投资了上百万美元，但世界最大的投资公司之一的分析显示，除了最大的技术公司之外，大多数美国公司还没有看到任何财政回报。
在星期六发表的分析中，阿波罗全球管理公司称认为，“S&P 493”指S&P500减去技术公司Alphabet Inc.,Amazon.com Inc.,Apple Inc.,Meta平台 Inc.,Microsoft Corp.,Nvidia Corp.和Tesla Inc.”尚未受益于其在AI上的投资。
阿波罗分析师Torsten Slok 称认为，虽然"伟大七人"从AI中看到了真正的利润，但其他公司的工人人均利润率和收入仍然平平，没有证据表明该技术正在提高生产力。 Slok写道：「美国主流企业正在退缩
斯洛克从一系列的图表中得出了他的结论，这些图表衡量了三个主要的衡量标准：每个工人的收入，利润幅度和生产力的增长。 虽然AI为7个科技巨头发送了这些标准，在技术公司，每个雇员的收入从2022年的平均55万美元猛增到今年的近80万美元，阿波罗的分析是显示。 但这一数字在S&P 493中一直平平，自2019年以来一直保持在550,000美元左右：
从2023年第三季度起，科技企业的利润率飞涨
尽管许多AI乐观主义者预测
研究使人们怀疑那些预测AI会将世界带入"丰盛时代"的人的声称，在这个时代，每个人都可以少花时间在工作上，多花时间去追求自己在工作之外的利益。 虽然一些风险资本支持的起步企业正与谷物作对并增加其在AI符上的支出，但更多的已建公司却在回避这一点，即Slok 称。 他写道：“美国主流公司不需要最新模式，“只要代理AI和象征性支出仅限于经济的一小部分，AI的宏观经济影响将非常有限。”
但Slok 称不仅仅是向AI投出钱财，“展望未来的问题是，即使模型变得商品化，主流公司美国能否将日益廉价的智能转化为更高的收入增长和更高的利润幅度。” “这可能比听起来更困难。”
斯洛克认为，AI的问题在于商业界的智能大多与判断有关。 而AI虽然在计算，研究和生成事物方面非常出色，但判断需要更多的上下文，而答案往往会因问到哪些人或模型而有所不同。 Slok解释说，大赦国际仍然必须克服重大挑战，才能相信它，包括它不能理解商业文化、问责制、道德取舍、公平和信任，所有这些都是造成声誉风险和推动收入和利润增长的因素。
“底线是AI的故事将在S&P 493中决定，而不是伟大七大
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Apollo analysis shows no one besides the biggest tech giants is seeing benefits from AI
Despite all of the hype and the multiple millions of dollars invested in artificial intelligence, most of corporate America outside of its biggest technology firms is yet to see any financial payoff, according to an analysis by one of the world’s largest investment firms.
In the analysis published on Saturday, Apollo Global Management Inc. said that the “S&P 493,” which refers to the S&P 500 minus technology firms Alphabet Inc., Amazon.com Inc., Apple Inc., Meta Platforms Inc., Microsoft Corp., Nvidia Corp. and Tesla Inc., has not yet benefited from its investments in AI.
Apollo analyst Torsten Slok said that while the Magnificent Seven has seen real profits from AI, the profit margins and revenue per worker of other companies remains flat, with no evidence that the technology is enhancing productivity. “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,” Slok wrote.
Slok drew his conclusions from a series of graphs that measured three key metrics: revenue per worker, profit margins and productivity growth. While AI has sent these metrics sky-high for the seven tech giants, there’s no indication of that happening with anyone else, he said. At the tech firms, revenue per employee has jumped from an average of $550,000 in 2022 to almost $800,000 this year, Apollo’s analysis shows. But that figure has remained flat within the S&P 493, lingering at around $550,000 since 2019:
A look at profit margins reveals a similar story, with profit margins at the tech firms soaring since the third quarter of 2023, while remaining more or less flat for everyone else:
The chart tracking productivity growth is a little messier, but shows that AI has had little impact in terms of helping the average company to get more work done with the resources at its disposal, despite the predictions of many AI optimists:
The research calls into question the claims of those who have predicted that AI will lead the world into an “age of abundance,” where everyone is able to spend less time on working and more time pursuing their interests outside of it. While some venture capital-backed startups are going against the grain and increasing their spending on AI tokens, more established firms are shying away from this, Slok said. “Mainstream corporate America does not need the latest model and is unwilling to pay for it,” he wrote. “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.”
Some may argue that it’s simply a matter of non-technology firms lagging behind their innovation-oriented counterparts, but Slok said it’s not simply a matter of throwing money at AI and reaping the rewards. “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,” he wrote. “That may be harder than it sounds.”
The problem AI has, according to Slok, is that intelligence in the business world is mostly related to judgment. And while AI is great at calculating and researching and generating things, judgment requires much more context, and the answer will often vary depending on which human or model is asked the question. AI still has to overcome significant challenges before it can be trusted, Slok explained, including its inability to understand business culture, accountability, ethical trade-offs, fairness and trust, which all factor into reputational risk and drive revenue and profit growth.
“The bottom line is that the AI story will be decided in the S&P 493, not the Magnificent Seven, and so far there is no evidence that revenue growth or margins are improving outside of the tech sector,” Slok wrote.
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