Artificial intelligence has not improved the financial performance of large corporations outside the technology sector, according to a recent note from Torsten Slok, chief economist at Apollo Global Management.
Slok focuses on what he calls the S&P 493, the S&P 500 minus the seven largest technology companies: Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia and Tesla. He finds that profit margins and revenue per worker at the remaining companies appear flat, with no evidence that AI is boosting productivity.
“Despite massive investments and widespread hype around artificial intelligence, the technology has delivered zero financial payoff to corporate America outside of tech,” Slok said.
He notes that revenue per worker and profit margins are rising for the Magnificent Seven but remain flat for the S&P 493. There are also still no signs that AI is accelerating productivity growth. With no impact on the bottom line, mainstream companies are beginning to treat token spending not as a source of growth but as a cost center that weighs on margins.
Slok is skeptical that non-tech companies are simply lagging the tech giants. He argues it will be difficult for corporate America to turn increasingly cheap “intelligence” into higher revenue growth and higher profit margins. “AI may be a great calculator, but in business, intelligence is mostly judgment,” he wrote. According to the economist, 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.
Against this backdrop, the financial markets carried out discussions last week on whether the ongoing artificial intelligence boom was indeed a bubble or not. Ken Griffin, the founder of Citadel, argued at the Future of Global Markets Conference for the sentiment that “right now we might be seeing bubbles again”. At the same time, he pointed out that bubbles usually take place during the time of serious economic changes, and in the aftermath of bubbles, the economy is adapted for many years ahead. He referred to the internet, which is regarded as a bubble of its time, and now it seems that it is so integrated into people’s lives that it is impossible for his son to imagine life before the internet.
Jon Gray of Blackstone took a nearly opposite view. In the 1990s telecom bubble, he said, companies built fiber hoping demand would come and used a lot of leverage to do it. With AI, the situation is the reverse: Blackstone’s portfolio companies are building capacity and struggling to keep up with demand. “Demand is almost parabolic,” Gray said, calling the shortage of compute indisputable.
Slok stresses that the AI story will be decided in the S&P 493, not among the Magnificent Seven. So far, there is no evidence that revenue growth or margins are improving outside the tech sector. Venture-backed companies continue to spend more on tokens, but mainstream corporate America does not need the latest models and is unwilling to pay for them. As long as agentic AI and token spending remain confined to a small part of the economy, the macroeconomic effects of AI will be limited, he argues.
