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TL;DR
Companies are committing enormous sums to AI infrastructure, but Apollo economist Torsten Slok says broad financial gains outside the technology sector are not visible in aggregate data. Research and company experiments show measurable benefits in some specific workflows, while the scale, durability and financing of the spending remain open questions.
Slok’s Apollo note compares revenue per worker and profit margins at the seven largest technology companies—Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia and Tesla—with the other 493 S&P 500 companies. Apollo’s charts show revenue per worker and margins rising for the seven, while the broader group has remained comparatively flat. The note also cites San Francisco Federal Reserve productivity measures that, in its reading, show no clear AI-driven acceleration so far.
Those trends describe company-level outcomes, not a direct measurement of AI’s effect. A flat average can conceal companies that gained or lost, and the data cannot isolate AI from factors such as labor costs, interest rates or tariffs. Apollo’s conclusion that AI has delivered “zero financial payoff” beyond tech is Slok’s interpretation of aggregate indicators, not proof that no individual company or team has benefited.
The investment bill is easier to see in filings. Meta’s third-quarter results, released October 21, 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. The company narrowed its 2026 capital-spending outlook to $135 billion to $145 billion. Its October 22 filing lists roughly $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 obligations span multiple years and are not all exclusively for AI.
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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The Gap Between AI Bills and Returns
The tension matters to investors, company leaders and workers because infrastructure costs arrive before many firms can show returns. Spending on data centers, servers, chips and cloud capacity can support future services, but it also raises depreciation, power and financing costs. If revenue or productivity gains do not follow, margins and cash flow may come under pressure.
There is evidence of more focused payoffs. The source material cites research finding customer-support workers resolved 14% more issues per hour with AI assistance, with a 34% gain among novice workers. Retail experiments reported sales changes ranging from zero to 16.3%, depending on the workflow. These results suggest gains can depend on the task, implementation and workers involved; they do not establish a comparable return across entire companies.
One survey cited in the source found 83% of nearly 9,000 executives reported no productivity impact so far, while the average reported effect was 0.2% a year. The figures are survey results, not a definitive economy-wide measure. Taken together, they show why the debate is not simply whether AI can help, but whether specific benefits can scale enough to justify rapidly expanding costs.
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What Apollo’s Data Capture
Apollo published its “No Signs of AI Payoff Outside the Tech Sector” note on October 24. It examined public-company revenue per worker and margins alongside productivity indicators and spending data from Ramp, a corporate card and spending platform. Ramp’s figures cover its more than 85,000 U.S. business customers, not the S&P 500 as a whole.
Ramp data cited by Apollo show spending concentrated among a small number of companies: the top 10% accounted for 99.5% of spending on model serving and inference, 99% of neocloud spending and 95.6% of spending on OpenAI and Anthropic. Apollo also reported that 80.4% of the top 1% of AI spenders were venture-backed, compared with 13.1% of median spenders. These figures describe the platform’s customer base and should not be treated as a census of U.S. businesses.
Meta is one example of the infrastructure commitments involved. The roughly $825 billion figure combines leases and contractual obligations stretching through 2036, including data-center, energy, network and cloud capacity. It is not a single-year cash outlay. Separately, forecasts cited in the source put capital spending by Amazon, Alphabet, Meta, Microsoft and Oracle at nearly $780 billion in 2026 and above $1 trillion annually from 2027 through 2030; those are projections, not company commitments.
“Artificial intelligence “has delivered zero financial payoff to corporate America outside of tech.””
— Torsten Slok, Apollo chief economist, in an October 24 note
What the Aggregate Numbers Miss
The size and timing of economy-wide AI returns remain uncertain. Company averages cannot show which departments or firms are gaining, and the cited productivity measures do not identify AI as the cause of changes or a lack of change. Survey responses also depend on how executives define and recognize productivity impact.
Meta’s commitments do not equal its annual spending, and the source says some obligations are not AI-related. The reported decline in free cash flow is one quarter’s result, not a forecast of future cash generation. It is also unclear how much of the planned infrastructure will be used, what revenue it will support, and how quickly any gains will appear.
Financing is another unresolved issue. The source reports that SpaceX borrowed $40 billion to buy AI chips and that insurance costs for debt tied to Meta and CoreWeave rose. Such signals may reflect growing concern about risk, but they do not by themselves establish that borrowers will struggle to repay or that planned projects will fail.
Spending and Productivity to Watch
The next evidence will come from company results and filings showing whether infrastructure spending translates into higher revenue, improved margins or stronger cash generation. Meta’s guidance places its 2026 capital spending at $135 billion to $145 billion; future updates can show whether spending stays within that range and how management connects it to business results.
Investors and policymakers will also be watching productivity data and company-level disclosures for clearer evidence of gains beyond the technology sector. Specific trials may offer useful clues, but results will need to be tested across more tasks and over longer periods before they can establish broad effects.
For now, the confirmed picture is uneven: AI spending and infrastructure obligations are large and measurable, while economy-wide returns remain difficult to identify. Whether that gap narrows will depend on how quickly businesses turn AI use into lasting productivity or revenue gains—and whether those gains outweigh the costs.
Key Questions
What did Apollo mean by “zero financial payoff”?
Apollo economist Torsten Slok used the phrase to describe aggregate trends showing little visible improvement in revenue per worker and profit margins for the 493 S&P 500 companies outside the seven largest technology firms. It does not prove that no individual business or team has benefited from AI.
What does Meta’s roughly $825 billion figure represent?
It combines 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 cover multiple years and include some spending not specifically tied to AI.
Are companies seeing any measurable AI gains?
Some task-level studies cited in the source report gains, including more customer-support issues resolved per hour and sales increases in certain retail experiments. Results vary by workflow, and those trials do not establish economy-wide returns.
Does negative free cash flow mean Meta is losing money?
No. Meta reported negative free cash flow of $2.12 billion in the third quarter after $32.79 billion in operating cash flow and $34.91 billion in capital expenditures. Free cash flow subtracts capital spending from operating cash flow; it is not the same as net income.
Source: ThorstenMeyerAI.com
