Apollo economist says AI has delivered zero financial payoff to non-tech corporate America

The chief economist of Apollo Global Management has published a note arguing that artificial intelligence has produced no measurable financial benefit for large US companies outside the technology sector, despite the enormous sums being spent on it, according to TechCrunch.

The economist, Torsten Slok, builds his case on what he calls the "S&P 493" — the S&P 500 with seven mega-cap technology names stripped out: Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia and Tesla. Within that group, TechCrunch reports, Slok finds that profit margins and revenue per employee have remained essentially flat, and that there is no sign AI is lifting productivity. "Despite massive investments and widespread hype around artificial intelligence, the technology has delivered zero financial payoff to corporate America outside of tech," Slok wrote.

Not just a matter of slow adopters

A natural objection is that non-tech companies are simply early on the adoption curve, and that the gains will show up in the financials once deployments mature. Slok sounds skeptical of that reading. As TechCrunch relayed, he argues it will be difficult for corporate America to convert ever-cheaper intelligence into faster revenue growth or wider margins.

His reasoning is that raw computational ability is not what drives business results. "AI may be a great calculator, but in business, intelligence is mostly judgment," Slok wrote. He added that AI does not grasp accountability, trust, culture, unwritten rules, ethical trade-offs or fairness — the factors he says shape reputational risk and, ultimately, the revenue growth and profit margins companies are chasing.

Part of a wider pattern

Slok's note does not stand alone. TechCrunch points out that recent studies have likewise concluded that AI has yet to deliver significant productivity gains. TechCrunch also disclosed that Apollo, a private equity firm, previously owned the publication.

Why it matters

The justifications for the current AI buildout — data center construction, chip orders, enterprise software spending — rest heavily on the assumption that the technology will eventually raise productivity across the whole economy, not just enrich a small set of hardware and cloud vendors. Slok's S&P 493 framing is a direct challenge to that assumption: if margins and revenue per employee at the vast majority of large US companies have not moved after years of AI adoption, then whatever payoff exists so far is concentrated in the seven companies his analysis excludes.

For corporate buyers, the note is a prompt to demand measurable returns before scaling spending further, rather than treating AI budgets as an inevitability. For investors, it raises an uncomfortable question about the revenue being booked by AI vendors: is it being paid for out of genuine productivity gains generated elsewhere in the economy, or out of budgets that have yet to see any benefit at all? If the latter, the gap between the investment boom and the measured payoff becomes a risk in its own right.