The buzz around Artificial Intelligence has promised a revolution in productivity and profits. But a sobering analysis from Apollo Global Management suggests a different story is unfolding: a tale of two economies in the age of AI.
The 'Magnificent Seven' and the Great Divide
According to Torsten
Slok, chief economist at Apollo, the financial benefits of the AI boom are almost entirely concentrated within a group of seven tech titans. This cohort, often called the 'Magnificent Seven'—Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia, and Tesla—are seeing both revenue per worker and profit margins climb significantly. In contrast, for the other 493 companies in the S&P 500 index, these same metrics have remained stubbornly flat. The data paints a clear picture: while Big Tech is selling the AI revolution, the rest of corporate America has yet to see a financial payoff.
The Cost of Entry Is a Mountain
For companies outside this elite group, AI is currently looking less like a profit engine and more like a significant cost centre. The investment required to build and integrate meaningful AI capabilities is enormous, with Big Tech planning to spend hundreds of billions on AI infrastructure. This massive capital outlay creates a high barrier to entry. While many companies are experimenting with AI tools, the spending is often viewed as an expense that weighs on margins rather than a clear driver of growth. Apollo's analysis notes that mainstream businesses are becoming unwilling to pay for the latest, most expensive AI models when the return on investment isn't clear.
No Widespread Productivity Boom… Yet
One of the core promises of AI was a surge in economy-wide productivity. However, the data so far shows no signs of this happening. Slok's assessment points out that despite the hype, key productivity indicators have not improved for the vast majority of companies. While the Magnificent Seven are becoming more efficient, showing a significant rise in revenue per employee from around $550,000 in 2022 to nearly $800,000, that figure has been stagnant for the S&P 493. This suggests that companies are purchasing AI services but are not yet able to translate that spending into doing more with less. The productivity paradox—investing in technology without immediate gains—appears to be in full effect.
Who Is Actually Paying for AI?
The analysis reveals that a huge portion of AI spending is driven by a small number of firms, many of which are venture-backed startups. According to the research, the top 10% of businesses account for over 95% of the spending on tools from major AI labs. This creates a somewhat circular economy where the profits of AI sellers are being funded by investor capital rather than by cash generated from end-customer demand. Slok argues that this dynamic is not sustainable indefinitely. The real test for the AI market will be whether mainstream companies can eventually turn the technology into higher revenue and profit margins, a challenge that may be harder than it seems.
The Human Element AI Can't Replace
Beyond the financial data, Slok highlights a fundamental limitation of current AI: it lacks business judgment. He argues that critical business drivers like accountability, trust, culture, and understanding ethical trade-offs are beyond the scope of AI. These human elements are what ultimately shape a company's reputation and drive longterm revenue and profits. While AI can be a powerful calculator or tool, it cannot replicate the nuanced judgment that defines successful business strategy. This suggests that the true value of AI will be realised not by replacing human intelligence, but by augmenting it in the right context.
