Apollo Global: AI Payoff Limited to Big Tech, Mainstream US Firms See Zero ROI
Apollo Global Management’s chief economist Torsten Slok reports that artificial intelligence has delivered no financial payoff to US businesses outside the technology sector. While the Magnificent Seven tech giants see rising revenue per worker and profit margins, the rest of the S&P 500 shows flat productivity and margins. Mainstream companies now view AI spending as a cost center rather than a growth driver, with venture-backed firms accounting for the vast majority of token consumption.
Key points
- Apollo Global Management chief economist Torsten Slok states that AI has provided zero financial payoff to US corporate America outside the technology sector.
- Revenue per worker for the Magnificent Seven tech firms rose from approximately $550,000 in 2022 to nearly $800,000, while the rest of the S&P 500 remained flat at $550,000.
- Profit margins for the top tech group are expanding, whereas the remaining 493 S&P 500 companies maintain static margins of approximately 10%.
- Venture-backed companies dominate AI adoption, with the top 10% of firms accounting for 95.6% of spending on models from OpenAI and Anthropic.
- Mainstream corporations are treating AI token spending as a cost center that weighs on margins, with some firms like Accenture capping monthly staff spending at $29.
- Reports from PwC and Deloitte corroborate Apollo’s findings, showing that most chief executives have seen neither increased revenue nor decreased costs from AI investments.
The Divergence in AI Productivity
A new analysis from Apollo Global Management highlights a stark economic divide in the adoption of artificial intelligence within the United States. Torsten Slok, the chief economist at the global asset management firm, argues that the technology has yet to deliver any tangible financial payoff to corporate America outside of the technology sector. In a recent posting on the firm’s Daily Spark blog, Slok detailed how the broader market is beginning to view AI expenditures not as engines of growth, but as burdensome cost centers that suppress corporate margins.
The data presented by Apollo draws a sharp contrast between the so-called Magnificent Seven tech giants and the remainder of the S&P 500. According to Slok, revenue per worker has surged for the top tech firms, which include hyperscalers, Apple, Nvidia, and Tesla. In 2022, this metric stood at approximately $550,000 per employee. By the time of the report, it had climbed to nearly $800,000. This growth is accompanied by expanding profit margins, suggesting that these companies are successfully monetizing their AI investments.
Mainstream Companies Face Stagnation
In contrast, the other 493 companies in the S&P 500 have seen little to no benefit. Revenue per employee in this broader group has remained stagnant at the $550,000 level. Furthermore, profit margins for these non-tech firms have stayed flat at approximately 10%. Slok noted that there is currently no evidence that AI is lifting productivity growth for the majority of the US economy. This stagnation suggests that for most businesses, the integration of AI has not translated into operational efficiency or top-line revenue growth.
The spending patterns reveal that the burden of AI adoption is heavily concentrated. Data from the corporate spending platform Ramp indicates that the top 10% of firms account for 95.6% of spending on AI models from providers such as OpenAI and Anthropic. The vast majority of these top spenders are backed by venture capital. This concentration implies that the current AI boom is driven by a small cohort of high-risk, high-reward entities rather than broad corporate adoption.
Cost Centers and Spending Caps
Mainstream corporations are increasingly pulling back from aggressive AI spending. Slok observed that these companies do not require the most advanced models and are unwilling to pay premium prices for them. Consequently, many firms are treating token spending as a cost that weighs on their financial performance. Some large employers have already implemented strict limits. For instance, professional services firm Accenture recently capped staff spending on Anthropic’s Claude model at $29 per month. This move signals a shift from experimental adoption to cost containment.
Corroborating Industry Reports
Apollo’s findings align with other recent industry analyses. A report from PwC earlier this year found that the majority of chief executives had not experienced increased revenue or decreased costs from AI, despite significant investments. Similarly, research from Deloitte has shown that productivity gains have been elusive for many organizations. These reports suggest that the initial hype surrounding AI has not yet materialized into widespread economic benefits for the general business community.
Market Reactions and Historical Context
Slok’s assertions have met with pushback on social media, with some commentators arguing that the picture painted is incomplete. Others have drawn parallels to the historical adoption of personal computers, noting that productivity growth often lagged behind widespread adoption by a decade or more. This historical context suggests that the current lack of financial payoff might be a temporary phase in the technology’s lifecycle. However, the immediate data points to a significant disconnect between investment and return for most US businesses.
Key takeaways
- Apollo Global Management reports zero financial payoff from AI for US businesses outside the tech sector.
- Magnificent Seven tech firms saw revenue per worker rise from $550,000 to nearly $800,000 since 2022.
- The rest of the S&P 500 shows flat revenue per worker and static 10% profit margins.
- Venture-backed firms dominate AI spending, with the top 10% accounting for 95.6% of token costs.
- Mainstream companies view AI as a cost center, with some firms like Accenture capping monthly spending at $29.
- Reports from PwC and Deloitte corroborate that most CEOs have seen no revenue or cost benefits from AI investments.
Sources
The WireByte editorial team synthesises technology news from multiple primary sources, verifies the facts, and links every source. Articles are produced with AI assistance and reviewed under our editorial policy.
