AI Payoff Absent Outside Tech: Non-Tech Margins Flat

Despite massive investments and widespread hype around artificial intelligence, the technology has delivered zero financial payoff to corporate America outside of tech.Revenue per worker is rising for the Mag 7 but is flat for the S&P 493, see the first chart below. Profit margins are rising for the Mag 7 but are flat for the S&P 493, see the second chart below. And there are still no signs of AI boosting productivity growth, see the third chart below. With no impact on the bottom line, mainstream corporate America is pulling back and starting to view token spending not as a source of growth but as a cost center that weighs on margins.

VC-backed companies are spending more and more on tokens, but mainstream corporate America does not need the latest model and is unwilling to pay for it. As long as agentic AI and token spending are confined to a small part of the economy, the macroeconomic effects of AI will be very limited, see the fourth and fifth charts below.

The question looking ahead is whether, even as models become commoditized, mainstream corporate America can turn increasingly cheap intelligence into higher revenue growth and higher profit margins. That may be harder than it sounds. AI may be a great calculator, but in business, intelligence is mostly judgment. Judgment depends on context, and the answer varies with which human or which model you ask. Perhaps most importantly, 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.

The bottom line is that 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.

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Note: Inflation adjusted to 2019 Q4. Sources: Bloomberg, Macrobond, Apollo Chief Economist

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Sources: Bloomberg, Macrobond, Apollo Chief Economist

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Note: Total Factor Productivity (TFP) is the utilization-adjusted series from the San Francisco Fed (Fernald, 2014), adjusted for cyclical variation in factor utilization. Sources: Federal Reserve Bank of San Francisco, US Bureau of Labor Statistics, Apollo Chief Economist

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Sources: Ara Kharazian, Chief Economist, Ramp; Apollo Chief Economist

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Sources: Ramp AI Index, Apollo Chief Economist

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