What did Apollo’s economist say about AI’s impact on non-tech firms?

Apollo’s chief economist, Torsten Slok, released a note on October 25, 2026, arguing that artificial intelligence has delivered zero financial payoff to corporate America outside the tech sector. The claim rests on an analysis of the S&P 493, the S&P 500 index minus the seven largest tech companies. Slok reports that profit margins and revenue per worker in the remaining 493 firms appear flat, with no evidence that AI is improving productivity. The note was published on TechCrunch, where Slok’s remarks were quoted.

How did Slok measure AI’s effect on productivity?

Slok examined two key metrics: profit margins and revenue per employee. He compared these figures over recent quarters, looking for upward trends that might correlate with AI investment. The analysis found no statistically significant change in either metric across the S&P 493 cohort, suggesting that AI deployments have not translated into measurable financial gains for these companies.

What does Slok say about the nature of AI in business?

Slok argues that AI is "a great calculator" but lacks the judgment required in business contexts. He lists accountability, trust, culture, unwritten rules, ethical trade-offs, and fairness as dimensions that AI does not understand. These factors, he notes, shape reputational risk and ultimately drive revenue growth and profit margins. The implication is that AI’s current capabilities are insufficient to replace human decision-making in complex commercial environments.

Are there any studies that support Slok’s findings?

The note references recent studies that also find AI has yet to deliver significant productivity gains. While the specific studies are not named in the TechCrunch article, the consensus among cited research appears to align with Slok’s conclusion that AI’s impact on non-tech firms remains limited.

What are the practical implications for non-tech companies?

If AI does not improve revenue per worker or profit margins, non-tech firms may need to reassess their investment strategies. The focus might shift toward incremental process automation rather than large-scale AI initiatives, or toward hybrid models that combine AI with human oversight to address the judgment gap highlighted by Slok.

How does this contrast with the tech sector’s experience?

Tech giants such as Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia, and Tesla are excluded from the S&P 493 analysis because they already embed AI across product lines, infrastructure, and customer interactions. Their financial performance shows measurable gains attributed to AI, underscoring a sector-specific advantage that non-tech firms have not yet replicated.

What should investors watch for next?

Investors may monitor whether non-tech companies begin to close the judgment gap by integrating AI with human decision frameworks. Additionally, the emergence of new AI models that incorporate ethical reasoning or contextual understanding could shift the productivity calculus for these firms.

Where can I read more about AI’s business impact?

For a broader view of AI’s role in enterprise, see the discussion on the Google and Meta Release TorchTPU: Native PyTorch on TPUs.

AI Financial Payoff: What the Numbers Say

Slok’s analysis hinges on two financial levers that most investors monitor: profit margins and revenue per employee. In the S&P 493, both metrics have hovered within a narrow band over the past two years, even as companies report rising AI spend. The lack of a measurable lift suggests that AI deployments have not yet translated into higher earnings or labor efficiency at scale.

Incentives and Risks for Non-Tech Firms

Non-tech companies face a dilemma: invest in AI to stay competitive or allocate capital to other growth levers. The data imply that the return on AI investment is low, raising the risk of stranded capital. Moreover, deploying AI without addressing judgment and cultural fit can expose firms to reputational risk, regulatory scrutiny, and operational disruptions.

What Changes Next?

The next wave of AI may bring models that embed ethical reasoning and contextual awareness, potentially bridging the judgment gap. Companies that pilot such models in high-stakes decision contexts—such as pricing, risk assessment, and customer engagement—could see a shift in the AI financial payoff curve. Until then, the prevailing evidence points to modest gains confined to routine, data-heavy tasks.

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