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TL;DR
Apollo economist Torsten Slok says broad corporate data show no clear financial payoff from AI outside the technology sector. That conclusion describes aggregate trends, not proof that every non-tech company or task has received no benefit; some workplace studies report gains in specific workflows even as AI infrastructure spending rises.
Apollo chief economist Torsten Slok said an October 24 research note found no clear financial payoff from artificial intelligence outside the technology sector, as revenue per worker and profit margins rose among seven major technology companies but remained broadly flat for the other 493 S&P 500 firms. The finding highlights a gap between large, documented spending on AI infrastructure and evidence of broad returns, though it does not show that AI has produced no gains in individual businesses or tasks.
Apollo’s note, titled “No Signs of AI Payoff Outside the Tech Sector,” compares inflation-adjusted revenue per worker and profit margins for the so-called Magnificent Seven—Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia and Tesla—with the rest of the S&P 500. Apollo’s charts put the seven near $780,000 in revenue per employee in the third quarter of 2026, while the other 493 were around $525,000 and had remained in a similar range since 2021. The seven’s margins rose to roughly 30%, compared with about 10% for the rest.
The note also cites San Francisco Federal Reserve productivity measures, which Apollo says show no sign yet of AI lifting productivity growth. Separately, data from Ramp, a corporate spending platform with more than 85,000 U.S. business customers, show spending on AI models and computing concentrated among a small group. The top 10% of firms accounted for 99.5% of spending on model serving and inference, 99.0% of neocloud spending and 95.6% of spending on OpenAI and Anthropic, according to the figures cited by Apollo. Those figures describe Ramp customers, not the S&P 500 as a whole.
Evidence from specific workplace applications is less uniform. The source material cites a customer-support study reporting 14% more issues resolved per hour, with a 34% gain among novice workers, and retail experiments in which sales effects ranged from zero to 16.3%, depending on the workflow. It also reports that 83% of nearly 9,000 executives said AI had not yet affected productivity, while the average reported impact was 0.2% a year. The supplied material does not identify the underlying studies for those figures, so their methods and comparability cannot be assessed here.
Infographic 01 · The “zero” in numbers
What “zero financial payoff” actually measures.
Apollo’s headline rests on five charts. Here are their numbers, and what they can and cannot prove.
Who pays for AI? Share of spending by the top 10% of firms
Ramp customer data via Apollo · non-AI categories in grey for comparison
Spending is concentrated in every category, not only AI; AI is the most extreme.
What the five charts do and do not show
shown not shown
- Shown: revenue per worker and margins rising for the 7 tech giants, flat for the other 493
- Shown: no AI lift yet in US productivity statistics (San Francisco Fed TFP, output per hour)
- Shown: AI spending sits in few, mostly venture-funded firms (Ramp, 85,000+ US businesses)
- Not shown: that AI caused the gap; rates, tariffs and wages move the same lines
- Not shown: gains inside single functions, which can cancel out in an average
- Not shown: the S&P 493 itself in the Ramp data; those are Ramp’s customers
“The AI story will be decided in the S&P 493, not the Mag 7.”Torsten Slok, Apollo chief economist, 24 Oct 2026 (opinion)
Sources: Apollo Daily Spark (24 Oct 2026) with charts by Bloomberg, Macrobond, SF Fed, BLS and Ramp; Apollo (20 Oct 2026); Ramp AI Index. Values with ≈ are read off Apollo’s charts. Assessment: Thorsten Meyer.
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Spending Is Ahead of Visible Returns
The central issue is whether companies can turn expensive computing capacity into durable gains in revenue, output or lower costs. Apollo’s comparisons suggest that such gains are not yet visible across most large U.S. companies, while evidence from narrower tasks indicates that results can depend on how AI is used and which workers or processes are measured.
The spending side is substantial. Meta’s third-quarter results reported $34.91 billion in capital expenditures and negative free cash flow of $2.12 billion, compared with positive free cash flow of $10.6 billion a year earlier. Its 2026 capital-spending outlook was narrowed to $135 billion-$145 billion. In a filing, the company listed about $355.73 billion in leases not yet started and $454.52 billion in non-cancelable contractual commitments, plus up to $14.72 billion in contingent cloud purchases. Those categories total roughly $825 billion in future commitments; the figure is not all AI spending, and the obligations extend across multiple years.
For investors, employees and customers, the distinction matters: infrastructure investment is measurable, but its eventual returns remain uncertain. If firms cannot show that AI improves outcomes enough to cover computing, staffing and financing costs, spending could weigh on margins. Conversely, aggregate company measures may miss benefits concentrated in particular departments or firms.
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How Apollo Reached Its Conclusion
Apollo’s October 24 note drew wider attention after coverage by outlets including TechCrunch, PYMNTS and Bloomberg. Its argument rests on company-level comparisons, productivity indicators and Ramp spending data. Slok interprets the gap between technology firms and other companies as evidence that AI’s financial benefits have not broadly appeared beyond the sector selling the technology.
That interpretation is not the same as a controlled measurement of AI’s causal effect. A flat average for 493 companies may conceal firms that improved and others that did not, while broad financial results can also be affected by labor costs, interest rates, tariffs and other factors. Ramp’s customer base is another limitation: its spending patterns cannot automatically be treated as representative of all U.S. businesses. The evidence supports a restrained conclusion—no broad payoff is apparent in these indicators yet—rather than a claim that AI has delivered no value anywhere outside tech.
The investment cycle adds to the scrutiny. The source material reports that SpaceX borrowed $40 billion to buy AI chips, and that large technology companies are planning major infrastructure outlays. Such commitments increase attention to access to capital and the ability of AI services to generate revenue sufficient to justify the cost. They do not, on their own, establish whether the investments will succeed or fail.
“Artificial intelligence has delivered zero financial payoff to corporate America outside of tech.”
— Torsten Slok, Apollo chief economist
What the Aggregate Data Cannot Show
Apollo’s analysis does not isolate AI from other causes of changes in company revenue, margins or productivity. It also does not establish how much AI individual firms use, whether measured effects take time to appear, or how gains are distributed among workers and business functions. The reported task-level results point to possible benefits, but the supplied source material does not provide enough study details to verify their design or compare them directly with Apollo’s corporate indicators.
The full cost and timing of infrastructure plans are also uncertain. Meta’s reported commitments cover multiple categories and years, and not all are AI-related. Spending forecasts for other major technology companies are projections, not booked commitments. The available information does not establish whether the announced capacity will be fully used or generate returns matching its cost.
Evidence to Watch in Company Results
The next test will be whether companies report sustained improvements in measurable outcomes—such as revenue per worker, output, customer-service resolution rates or operating margins—alongside their AI spending. Investors and businesses will also watch future filings for changes to capital plans, financing costs and commitments to data centers, chips and cloud services.
For now, Apollo’s note offers a broad snapshot rather than a final verdict on AI’s economic impact. Further productivity data and company-level evidence may clarify whether the gains seen in some specific applications spread across industries, and whether those benefits outweigh the growing cost of computing.
Key Questions
What does Apollo mean by no AI payoff outside tech?
Apollo’s note points to flat revenue per worker and profit margins among the 493 S&P 500 companies outside the Magnificent Seven, alongside productivity measures that it says show no AI boost yet. This is an interpretation of broad indicators, not a direct test of every company’s AI use.
Does the analysis prove that AI has produced no benefits outside technology?
No. Aggregate averages can hide gains at individual firms or in particular tasks, and the comparisons do not isolate AI from other economic factors. The evidence cited includes some reported improvements in customer support and retail workflows.
What is included in Meta’s roughly $825 billion in commitments?
The source material adds about $355.73 billion in leases not yet started, $454.52 billion in non-cancelable contractual commitments and up to $14.72 billion in contingent cloud purchases. The obligations span several years, and the total is not all AI-related.
Why are companies’ AI returns difficult to measure?
Company-level results can reflect many influences besides AI, while benefits may be concentrated in certain teams or processes. Spending data also show that AI-related purchases are concentrated among a small share of the businesses tracked by Ramp, which may not represent the wider economy.
Source: ThorstenMeyerAI.com
