Apollo Chief Economist Says AI Has Delivered 'Zero Financial Payoff' Outside Tech, Citing Flat Margins at S&P 493

Since Saturday, Oct. 24, when Apollo Global Management chief economist Torsten Slok published his latest Daily Spark note, the argument over whether AI spending is paying off has a fresh set of numbers behind it. Slok's verdict is blunt: "Despite massive investments and widespread hype around artificial intelligence, the technology has delivered zero financial payoff to corporate America outside of tech."

The note is titled "No Signs of AI Payoff Outside the Tech Sector." Slok, a partner at Apollo, splits the S&P 500 into two groups. One is the Magnificent 7: Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia and Tesla. The other is what he calls the S&P 493.

The gap in the numbers

Inflation-adjusted revenue per employee for the Magnificent 7 has climbed to roughly $780,000, according to Slok's data. For the S&P 493, it sits around $525,000, and Apollo's charts show it flat since the fourth quarter of 2019.

Profit margins show the same split. The Magnificent 7 are near 30%. The other 493 companies are stuck around 10%.

On productivity, Slok uses the San Francisco Fed's utilization-adjusted total factor productivity series. He finds no sign yet that AI is accelerating productivity growth across the economy.

Those figures describe a performance gap. The claim that AI explains the gap, or its absence outside tech, is Slok's interpretation of the indicators. The note does not isolate AI from everything else moving those margins.

Token spending as a cost

Slok argues that mainstream companies are souring on the spending itself. "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," he wrote.

Using data from Ramp chief economist Ara Kharazian and the Ramp AI Index, Apollo shows how narrow the buying is. The top 10% of firms account for 99.5% of spending on model serving and inference, 99% of neocloud spending, and more than 95% of spending tied to OpenAI and Anthropic. Cloud computing is nearly as lopsided, with the top 10% responsible for 95.7%.

The heaviest spenders are also the youngest. Among the top 1% of AI spenders, 80.4% are venture-backed. Among median AI spenders, 13.1% are.

Slok's conclusion: as long as agentic AI and token spending are confined to a small part of the economy, the macro effects stay very limited. He also says established companies have little reason to pay for the newest model when a cheaper one does the job.

The judgment argument

Slok's skeptical case is partly about what the technology cannot do. "AI may be a great calculator, but in business, intelligence is mostly judgment," he wrote. He added that 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."

His forward-looking question is whether, as models become commoditized, mainstream companies can "turn increasingly cheap intelligence into higher revenue growth and higher profit margins." His answer: "That may be harder than it sounds."

Where critics of the note land

Economist Brad DeLong responded on his blog the same day. He agreed that AI's effects outside tech are not yet visible in revenue, margins or measured productivity. But he argued the larger gains move through channels shareholders cannot easily capture: user surplus, new business formation, and platform incumbents using AI to deepen their moats.

DeLong's point is narrower than a defense of the boom. He wrote that those gains do not "produce a hyperboom in measured GDP or an explosion in profits that justifies current market valuations."

Joe Weisenthal of Bloomberg noted on X that the top token spenders in Slok's data are "overwhelmingly VC-backed companies," which "may have implications if VC-funding starts to slow."

What's at stake

The money involved is large. Companies are pouring billions into chips, data centers, software and models, and AI executives have promised an "age of abundance." Slok's note says the payoff, so far, is landing at a handful of megacap firms and their suppliers.

An earlier, shorter version of the pattern had already shown up in other studies that found AI has yet to deliver significant productivity gains. Slok's contribution is putting the dividing line at the S&P 493.

The open question is who keeps buying. If venture-funded firms account for most of the heavy token spending and VC funding slows, the demand that supports AI providers' revenue could shrink before mainstream companies show the margin gains that would replace it. Slok's own framing is that the AI story "will be decided in the S&P 493, not the Mag 7," and so far he sees no evidence of improvement there.