Apollo finds no AI payoff outside tech, and the margin now depends on judgement

Apollo's chief economist, Torsten Slok, wrote on 24 October that artificial intelligence has delivered "zero financial payoff to corporate America outside of tech". His Daily Spark note splits the S&P 500 in two. At the Mag 7, revenue per worker and profit margins are rising. At the other 493 companies, both are flat. He also finds no sign yet of AI lifting productivity growth. The line that matters for anyone working inside one of those 493 companies is his conclusion: mainstream corporate America is "starting to view token spending not as a source of growth but as a cost center that weighs on margins."

The budget line has changed sides

The safe position inside a large company has been visible AI adoption. You used the tools, mentioned them in the review and volunteered for the pilot. Slok's note describes the point where that position stops paying. Once finance teams file tokens under cost, every licence and every agent has to justify itself against the margin it was meant to improve.

He also separates two kinds of buyer. VC-backed companies are spending more and more on tokens. Mainstream corporate America, in his words, "does not need the latest model and is unwilling to pay for it." He expects the macroeconomic effects of AI to stay very limited for as long as agentic AI and token spending are confined to a small part of the economy.

Now read that from the desk of an operations lead at a retailer, an insurer or a manufacturer. Finance will audit the tool budget. The people who can show revenue or margin moved by their AI use keep the budget and the influence. The people who can show only usage become a cost line themselves.

Where the value actually sits

The second half of the note is the more useful half. Slok asks whether mainstream companies can turn "increasingly cheap intelligence into higher revenue growth and higher profit margins". His answer is that it "may be harder than it sounds." The reason he gives: "AI may be a great calculator, but in business, intelligence is mostly judgment." Judgement depends on context. AI, he writes, "does not understand accountability, trust, culture, unwritten rules, ethical trade-offs or fairness". Those are the things that shape reputational risk and, in the end, drive revenue and margins.

Apollo's chief economist is pointing at the layer above task execution as the place where the payoff gets decided. AI does the routine work. You do the thinking. At the 493, the spend has yet to show up in the accounts. The gap between the spend and the result is a judgement gap. Someone has to decide which tasks the tools take, where the output goes and who answers for it when it is wrong.

Slok's bottom line is that "the AI story will be decided in the S&P 493, not the Mag 7." Individual careers will be decided the same way: inside ordinary companies, by the people who connect the tools to the numbers.

Your Next Move

1. Tie one AI workflow to a figure finance already tracks. Take the workflow you use most and link it to revenue, margin, cycle time or cost per case. If you cannot name the figure, that workflow is the first one a margin review will cut.
2. Own the decision layer around the tools. Volunteer for the work Slok says AI cannot do. Set the rules for where output can be trusted, who signs it off and what happens when it is wrong. In his account, AI does not understand accountability.
3. Prepare your evidence before the budget conversation. If your employer already scores AI use, read how to show impact in an AI-graded performance review, and what the law gives you. Then bring the figure from step one.