Torsten Slok, chief economist at Apollo Global Management, has a blunt message for corporate America: for every company outside the technology sector, the artificial intelligence boom has yet to show up on the bottom line.
In a note published in Apollo's Daily Spark newsletter on October 24, Slok argued that despite heavy investment, AI has delivered "zero financial payoff" to businesses that are not tech firms. The analysis centers on what Slok calls the "S&P 493," his shorthand for the S&P 500 minus the so-called Magnificent Seven: Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia and Tesla.
The view matters because it challenges one of the central assumptions behind the current AI investment cycle: that the technology will eventually lift the broader economy, not just the builders of the models themselves.
A tale of two economies
According to Slok, the data shows a clear split between the largest tech names and everyone else. Revenue per worker is rising for the Mag 7 but is flat for the rest of the index. Profit margins show the same pattern, and there are still no signs of AI boosting measured productivity growth across the wider economy.
"Despite massive investments and widespread hype around artificial intelligence, the technology has delivered zero financial payoff to corporate America outside of tech," Slok wrote in the note.
His chart set also points to what he describes as a concentration problem. AI spending is concentrated in a small number of firms, and the circular nature of the current boom appears in token spending too, a pattern the note connects to the idea that much AI use is flowing between a narrow group of companies rather than spreading through the real economy.
Where the AI spending is actually going
The note argues that the spending is not broadly shared. VC-backed companies are increasing their outlay on AI tokens, but mainstream corporate America does not need the latest model and is unwilling to pay for it, Slok said.
As long as agentic AI and token spending stay confined to a small part of the economy, he argued, the macroeconomic effects of AI will remain very limited. He also said mainstream companies are starting to treat the expense differently.
"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 said.
Why the gap could be hard to close
Slok was skeptical that this is simply a matter of non-tech companies lagging behind the tech giants. He argued it will be tough for corporate America to "turn increasingly cheap intelligence into higher revenue growth and higher profit margins."
His reasoning goes beyond the data. Slok argues that what works in a chip design lab or a data center does not automatically transfer to a bank, a retailer or a manufacturer.
"AI may be a great calculator, but in business, intelligence is mostly judgment," he wrote. "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."
In other words, the bottleneck for most companies may not be access to better models. It may be the harder problem of turning a general-purpose tool into better decisions, customer trust and higher prices.
The firm's conclusion is direct. "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."
The productivity question
The Apollo analysis also feeds a growing debate about whether the AI wave has delivered measurable gains beyond the companies that build and sell the technology. Slok's productivity chart relies on the utilization-adjusted total factor productivity series from the Federal Reserve Bank of San Francisco, which is adjusted for cyclical variation in how intensively capital and labor are used.
Separate studies have also found that AI has yet to deliver significant productivity gains for most organizations, adding to the picture painted by Apollo. While the tech giants can point to rising revenue per employee, the rest of the index has been roughly flat on that measure for years.
By one reading of the chart data, revenue per employee at the largest tech firms has climbed from around $550,000 to nearly $800,000 since 2022. For every other company in the S&P 500, the figure has hovered around $550,000 for the last seven years, according to Business Insider's summary of the note.
What to watch next
The counterargument to Slok's pessimism is that AI adoption simply takes time. Early digital transformation efforts were also slow to show up in macro statistics before spreading through the economy.
But Slok's point is that the payoff is not guaranteed, and the clock is running. As models become more commoditized and cheaper, the question is whether mainstream corporations can translate falling costs into actual gains in revenue and margin. He is not convinced that will be easy.
For investors, the implication is that the fortunes of the AI trade now depend on the least glamorous part of the market. If revenue per worker and margins start to move for the S&P 493, the broad-based payoff argument gains credibility. If they stay flat, the gap between Wall Street's expectations and Main Street's reality becomes harder to reconcile.
Have AI investments at your company translated into measurable results, or do they still look more like a cost center than a growth driver? That is the question the next earnings season will help answer.
Filed under: AI, TechNews, Economy, BigTech, Productivity, AI, TechNews