Apollo's chief economist finds no AI payoff outside tech, and names judgement as the missing input

TechCrunch reported on 25 October that Torsten Slok, chief economist at Apollo Global Management, has published a note concluding that AI has not improved the bottom line of any big corporation outside the tech industry. Slok studied what he calls the S&P 493: the S&P 500 minus Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia and Tesla. He found profit margins and revenue per worker flat, with no evidence that AI is improving productivity. His summary: "Despite massive investments and widespread hype around artificial intelligence, the technology has delivered zero financial payoff to corporate America outside of tech."

The bottleneck Slok names

TechCrunch asked the obvious question: are non-tech companies simply lagging behind the giants? Slok was sceptical. He argued it will be tough for corporate America to "turn increasingly cheap intelligence into higher revenue growth and higher profit margins."

His reason is the useful part. "AI may be a great calculator, but in business, intelligence is mostly judgment," he wrote. Then: "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."

Read that as a map of where the value sits. Intelligence has become cheap. Turning it into margin depends on everything on Slok's list, and every item on that list is held by a person. Someone has to decide which output to act on, own the result when it goes wrong, and keep the customer's trust while it happens.

This is The War Room's second claim, stated by an economist at a private equity firm: the dividing line is judgement, accountability and relationship capital, the layer above task execution.

What flat revenue per worker tells you

Revenue per worker is the figure to watch. If AI were producing more output per employee across the 493, it would be rising. Slok finds it flat.

Two consequences follow. Companies are paying for tools whose output nobody has connected to a decision that moves revenue. And boards will notice. Spending with no return brings a hard question at the next budget round: who here turns this into results? The people who can answer that with evidence strengthen their position.

To anyone worried about their job, the headline reads as comfort. Read further and Slok makes a sharper argument. The scarce input is the person who exercises judgement over the machine, and most organisations have yet to build their work around that person. AI does the routine work. You do the thinking. The companies that eventually make money from AI will be the ones that put thinking people in charge of it.

Your Next Move

1. Tie one AI-assisted task to a number this month. Pick a piece of work where you already use AI and trace it to something the business tracks: revenue, cost or cycle time. A usage log records activity. A number shows payoff, which is exactly what Slok cannot find in the S&P 493. If your employer already weighs AI use in reviews, our guide to showing impact when your employer grades your AI use sets out how to present it.

2. Write down the judgement calls in your role. Use Slok's list as a checklist: where do you carry accountability, hold trust, read the unwritten rules or make an ethical trade-off? Those are the parts of the job a model does not own. Make them visible in how you describe your work to your manager.

3. Put yourself between the tool and the decision. Volunteer to own the review step on one AI workflow in your team. That means checking the output, signing it off and answering for it. That step is judgement and accountability, the two things Slok says AI lacks. Take it before someone else is assigned to it.