
Key points
- Torsten Slok, Apollo’s chief economist, states AI has delivered zero financial payoff to corporate America outside tech.
- Analysis of the S&P 493 shows flat profit margins and revenue per worker, with no evidence of productivity gains from AI.
Torsten Slok, chief economist at Apollo Global Management, published a note stating that artificial intelligence has delivered zero financial payoff to companies outside the technology industry. This assessment covers major corporations that have made massive investments in AI despite widespread hype surrounding the technology.A top economist says AI is not making non-tech companies more profitable yet.Slok's analysis of the S&P 493 indicates no correlation between AI investment and improved unit economics outside tech.
The evidence
Slok focused his analysis on what he calls the S&P 493, which excludes Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia and Tesla from the broader S&P 500 index. According to TechCrunch, his review found that profit margins and revenue per worker remain flat across this group.reported There is no evidence in the data that AI is currently improving productivity for these firms.
Evidence: reported
AI delivers 'zero financial payoff' to most companies, Apollo economist saysaifleet-hn-ai
The decision
The economist argued that it will be tough for corporate America to turn increasingly cheap intelligence into higher revenue growth and higher profit margins. He stated that while AI may be a great calculator, intelligence in business is mostly judgment. This distinction suggests that technical capability alone may not translate into financial performance for traditional enterprises.
The takeaway
These human-centric factors shape reputational risk and ultimately drive revenue growth and profit margins. Recent studies have also found that AI has yet to deliver significant productivity gains.
Building on this
For enterprise IT buyers, the documented limits of AI indicate that the technology functions primarily as a calculator rather than a judgment tool. The flat revenue per worker in the S&P 493 implies that current AI implementations are not driving productivity improvements.
Why it matters
- Enterprise buyers should audit AI projects for impact on profit margins and revenue per worker, not just operational speed.
- The flat productivity data in the S&P 493 suggests that ROI claims for AI in non-tech sectors may be overstated.
- Integrating AI requires a focus on judgment-heavy workflows where human accountability remains the primary driver of revenue.
Topics: AI economics, enterprise AI, productivity, Apollo Global Management, S&P 500
Updated
Then / now / next
Massive investments in AI were made with expectations of widespread productivity gains across corporate America.
An Apollo economist reports that these investments have yielded zero financial payoff for non-tech firms.
Corporate America must figure out how to turn cheap intelligence into higher revenue growth and profit margins.
Story timeline
- Then Massive investments in AI were made with expectations of widespread productivity gains across corporate America.
- 01 Nov 2026 AI delivers 'zero financial payoff' to most companies, Apollo economist says
- Now An Apollo economist reports that these investments have yielded zero financial payoff for non-tech firms.
- Next Corporate America must figure out how to turn cheap intelligence into higher revenue growth and profit margins.
Ask the article
Local keyword search of this article; no generated answers.Did this article give you the evidence you needed?
Your choice stays on this device. No public tally.Questions readers ask
Which companies are included in the S&P 493 analysis?
The S&P 493 includes all S&P 500 companies except Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia and Tesla.
Connected stories
Reading receipt
- Torsten Slok, Apollo’s chief economist, states AI has delivered zero financial payoff to corporate America outside tech.
- Analysis of the S&P 493 shows flat profit margins and revenue per worker, with no evidence of productivity gains from AI.
Still open: How long will it take for non-tech firms to convert cheap intelligence into higher profit margins?
Still open: Can AI tools be designed to better understand unwritten rules and ethical trade-offs?