Apollo Economist: AI Has Delivered Zero Financial Payoff Outside the Tech Sector

Quick Facts

• Apollo chief economist Torsten Slok found no improvement in revenue per worker or profit margins for S&P 500 companies outside the Magnificent 7 since AI spending began climbing.
• The top 10% of firms account for 99.5% of model-serving and inference spending, with mainstream companies increasingly treating token costs as overhead rather than growth investment.
• Big tech is on pace to spend roughly $730 billion on AI infrastructure in 2026, up 78% from $410 billion in 2025, yet Slok says none of it shows up as a return outside those seven balance sheets.

Torsten Slok, chief economist at Apollo Global Management, published a note on October 24 arguing that AI has delivered zero financial payoff to corporate America outside of tech. The finding drew immediate attention across financial markets and the technology industry.

Slok's analysis centers on what he calls the S&P 493: the S&P 500 minus Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia, and Tesla. For that group, revenue per worker and profit margins have shown no meaningful movement despite years of AI adoption and spending.

The Numbers Behind the Gap

The divide between the Magnificent 7 and the rest of the market is stark. Revenue per employee at the seven largest tech firms has risen from $550,000 to nearly $800,000 since 2022. For S&P 493 companies, that figure has barely moved from $550,000 over roughly seven years.

The margin picture is equally lopsided. Profit margins for the Magnificent 7 have climbed to nearly 30%. Margins for the S&P 493 remain around 10%, with no discernible upward trend.

Slok's note also cited data from the Ramp AI Index showing that AI spending is highly concentrated. The top 10% of firms account for 99.5% of model-serving and inference spending and more than 95% of OpenAI and Anthropic spend across corporate customers.

Mainstream Companies Treating AI as a Cost

Slok wrote that mainstream corporate America is pulling back and starting to view token spending not as a source of growth but as a cost center. That framing matters for software vendors and AI platform companies whose growth projections assume broad enterprise adoption translating into measurable business outcomes.

He was blunt about the limits of the technology itself. "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."

His bottom line: "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."

A Massive Spending Gap With No Broad Payoff

The findings arrive as hyperscaler capital expenditure reaches record levels. Alphabet, Meta, and Microsoft together spent about $78 billion on capex last quarter alone, an 89% jump from a year ago. UBS projects hyperscalers will spend $4.1 trillion on AI infrastructure from 2026 to 2028, tripling the $1.3 trillion deployed over the previous six years.

Slok's argument is that this capital is generating returns almost exclusively for the companies deploying it, not for the businesses buying access to it.

Independent Research Points the Same Direction

Slok's conclusions align with findings from other researchers. A February 2026 National Bureau of Economic Research study interviewed 6,000 executives, mostly CEOs and CFOs. Two-thirds reported that their companies use AI, but 90% said AI had no impact on productivity or employment over the previous three years.

The same executives said they hope for productivity gains in the future, a gap between expectation and current results that mirrors what Slok describes in the market data.

What This Means for Software Companies

For founders and executives at software companies, Slok's note raises a pointed question: if customers cannot demonstrate that AI tools improve their revenue or margins, how long will they continue paying for them? The shift from viewing AI spend as a growth investment to treating it as overhead is a direct threat to pricing power across the sector.

Slok closed with a warning that carries weight for anyone building AI-powered products for non-tech buyers. "As long as agentic AI and token spending are confined to a small part of the economy," he wrote, "the macroeconomic effects of AI will be very limited."