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AI spending is generating revenue for technology vendors, but most other S&P 500 companies have yet to show comparable gains in productivity or profit margins, a report by Apollo’s Daily Spark Analysis showed.
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Artificial intelligence has helped fuel a boom in technology spending, but the financial benefits remain hard to see in much of corporate America. Apollo Global Management chief economist Torsten Slok said on Oct. 24 that revenue per worker and profit margins for the Magnificent Seven technology stocks are rising, while remaining flat across the other 493 companies in the S&P 500.
Notably, Slok’s analysis found no clear evidence that AI is boosting productivity growth, despite heavy investment in the technology. Revenue per worker and profit margins rose among the Magnificent Seven but remained flat across the other 493 companies in the S&P 500, according to the report. “Despite massive investment and widespread hype around artificial intelligence, the technology has delivered zero financial payoff for corporate America outside of tech,” Slok wrote.
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Running AI models at scale can quickly increase costs, as many providers pay by token usage, so bills rise as employees make more requests or AI agents process data and handle increasingly complex tasks. Slok said that mainstream companies have started to see token spending as a cost rather than a source of growth. Venture capital-backed businesses spend more on tokens, he noted, while established companies have less incentive to pay for the new models when cheaper alternatives can do the job.
That creates a problem for AI vendors hoping to turn growing adoption into a lasting revenue stream. Selling more computing power and model access can boost suppliers’ sales, but customers need to see corresponding gains in productivity, revenue or operating costs to keep spending at the same pace. Furthermore, if AI spending increases without a measurable improvement in business performance, the additional spending can weigh on margins.
“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.” Slok added. “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 earnings growth or margins are improving outside of the tech sector.”
Slok’s analysis also points to a broader limitation: AI adoption remains concentrated among a relatively small group of companies. Unless use spreads across multiple industries and produces measurable results, the technology’s effect on the wider economy may remain limited.
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The same tension is emerging in India’s financial technology sector. A PwC India survey A report by Business Standard on September 11 found that 84% of fintech respondents surveyed have yet to see measurable financial results from their AI investments.
That didn’t stop the companies from going ahead. The survey also found that 48% of respondents identified proprietary intelligence as a leading strategic priority. Meanwhile, 30% expected customer experience to drive the adoption of AI agents in the next three to five years, followed by cost reduction and productivity gains at 22%.
Trust is another hurdle for businesses looking to deploy AI agents in financial services. According to the survey, 41% of respondents identified trust and customer adoption as the biggest barriers to scaling agent payments, while 33% pointed to fraud, security and risk management as major concerns.
AI agents could expand the role of technology in business by handling multistep tasks instead of simply responding to requests, although their ability to access tools, process information and act on company systems also brings additional usage costs and security concerns.
Nvidia has developed tools to address some of these risks, previously, Introducing its Open Agent Security Platforma hardware-and-software security stack designed to help businesses control AI agents and restrict potentially harmful actions. Rising token consumption has also urged companies including Microsoft, Meta and Amazon to increase AI use as employees adopt the tools and agency workloads rise. The trend highlights a growing challenge for businesses: encouraging wider AI adoption without spiraling operating costs.
OpenAI CEO Sam Altman also acknowledged the problem, describing AI token fees as a “huge issue” for customers seek better value from their spending. The infrastructure behind the AI boom carries its own price tag with Amazon, Google, Meta and Microsoft having committed huge sums to data centers, chips and the power to run AI workloads.
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