Revenue per worker is climbing at the Magnificent Seven while the other 493 companies in the S&P 500 remain largely stuck in place, according to new analysis from Apollo Global Management.

Corporate America has spent the past several years telling shareholders that artificial intelligence will change everything. According to Apollo Global Management chief economist Torsten Slok, it has so far mostly changed things for seven companies.

In a note published on October 24, 2026, Slok argues that AI is lifting revenue per worker at the Magnificent Seven. Everywhere else in the S&P 500, the same measure has barely moved. The finding matters because revenue per employee is one of the cleanest ways to gauge whether a technology is genuinely making a business more productive. The metric is calculated by dividing a company's revenue by its headcount, so it moves higher only when sales outpace the size of the workforce behind them.

One index, two markets

Slok divides the S&P 500 into two camps. The first is the Magnificent Seven: Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia and Tesla. The second is everyone else — a group he calls the "S&P 493." The split effectively captures two different markets operating under a single benchmark. Because the S&P 500 is weighted by market capitalization, its largest constituents carry more influence over headline index performance than the hundreds of smaller members behind them.

The gap between them is wide. Inflation-adjusted revenue per employee at the Magnificent Seven has climbed to roughly $780,000, up from approximately $565,000 in early 2023. The S&P 493, by contrast, remains at around $525,000 — a level that has held steady since 2019, meaning the rest of the index has effectively run in place through the entire AI boom.

Profitability tells a similar story. Profit margins at the Magnificent Seven stand near 30%, according to the findings, while the rest of the index is running at about 10%.

A narrow spending base

The concentration extends to AI spending itself. The top 10% of firms account for 99.5% of model-serving and inference spending — the cost of running trained AI models in production — and the same small slice of companies represents more than 95% of expenditure on services from OpenAI and Anthropic, two of the leading commercial AI model providers. That leaves less than 1% of such outlays attributable to the remaining firms in the index.

Not the first warning

The theme is not new for Slok. In a June 2026 analysis, he flagged the same pattern, noting that rising revenue per employee was limited to the Magnificent Seven when compared with small-caps and the broader index. Four months later, the picture has not meaningfully changed. The October note reinforces the idea that the AI productivity story remains a Big Tech story rather than an economy-wide one.

What it means for investors and companies

For investors, the most immediate takeaway concerns concentration risk. If AI-driven gains are confined to seven companies, then the AI trade is effectively a bet on those seven companies rather than on the S&P 500 as a whole.

The findings also suggest a cautious outlook for AI-themed investments outside the tech sector. Companies pitching AI as a margin booster may face greater skepticism if their revenue per employee keeps flatlining at around $525,000.

A break by the S&P 493 above its 2019-era revenue-per-employee level would be the first real sign that AI is spreading beyond Silicon Valley's biggest names. If the measure stays flat while the Magnificent Seven keeps climbing past roughly $780,000, the gap between the leading group and everyone else will only become harder to ignore.

Given that the top 10% of firms account for 99.5% of model-serving and inference spending, any meaningful shift in that share would signal whether the broader market is finally buying in — or still watching from the sidelines.

Source: CryptoBriefing