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TL;DR
Apollo economist Torsten Slok says aggregate data show no clear financial payoff from AI outside the technology sector, while companies are committing heavily to data centers, chips and cloud capacity. The claim describes broad trends, not proof that AI has produced no gains: measured benefits appear in some specific workflows, and the overall economic effect remains uncertain.
Apollo chief economist Torsten Slok said October 24 that available aggregate data show no clear financial payoff from AI outside the technology sector, even as Meta and other companies commit hundreds of billions of dollars to computing infrastructure. His conclusion highlights a widening gap between the measurable cost of AI investment and evidence of broad economic returns, though it does not establish that AI has produced no gains at individual companies or in particular tasks.
Apollo’s analysis compares the seven largest technology companies—Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia and Tesla—with the other 493 members of the S&P 500. In charts cited by Slok, inflation-adjusted revenue per worker and profit margins rose for the seven, while the corresponding measures for the other companies remained broadly flat. The figures show trends, not a direct measurement of how much AI caused them.
The note also points to San Francisco Federal Reserve measures of productivity, which Apollo said show no visible boost to productivity growth from AI so far. Separately, data from Ramp, a corporate spending platform with more than 85,000 U.S. business customers, show AI-related spending concentrated among a small group of firms. Ramp’s figures indicate the top 10% of its customers account for 99.5% of spending on model serving and inference. That sample describes Ramp customers, not all U.S. businesses.
The investment bill is visible in company filings. Meta reported $34.91 billion in capital expenditures in the third quarter and said it expects capital spending of $135 billion to $145 billion in 2026. Its filing listed roughly $355.73 billion in leases not yet started and $454.52 billion in non-cancelable contractual commitments, mostly related to cloud capacity, servers and network equipment, plus up to $14.72 billion in contingent cloud purchases. The combined figure is about $825 billion in future commitments; it includes some items not exclusively tied to 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 Costs and Returns
The gap matters because large infrastructure commitments are being made before broad productivity gains are apparent in the data cited by Apollo. If AI tools do not raise revenue, reduce costs or improve output enough to cover their expense, companies could face pressure on profit margins and investment returns. Meta’s third-quarter figures illustrate the scale of spending: operating cash flow was $32.79 billion against $34.91 billion in capital expenditures, leaving free cash flow at negative $2.12 billion, compared with positive $10.6 billion a year earlier.
That result alone does not show that AI spending caused Meta’s cash-flow decline or will fail to pay off. Meta also reported third-quarter revenue of $64.60 billion, up 26%, and its investment supports a broad set of infrastructure needs. But the scale of planned spending makes the economic question relevant beyond technology companies: investors, workers and business customers will want to know whether AI translates into lasting productivity, better services or lower costs—and who captures those benefits.
There is evidence of gains in specific settings. Source material cited customer-support research reporting 14% more issues resolved per hour, with a 34% gain for novice workers, and retail experiments showing sales changes from zero to 16.3% depending on workflow. Those findings concern defined tasks and settings; they do not establish that the same results apply across the economy.
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What Apollo’s ‘Zero’ Measures
Slok’s phrase that AI has delivered “zero financial payoff” outside tech is his interpretation of aggregate indicators, not a controlled estimate of AI’s causal effect. Flat averages among 493 S&P 500 companies could conceal firms that gained and firms that did not. The measures also cannot isolate AI from other influences, including labor costs, interest rates and tariffs.
The source material also cites a survey of nearly 9,000 executives in which 83% reported no productivity impact from AI so far, with an estimated average effect of 0.2% a year. Those results are survey findings, not a universal measure of business performance. They sit alongside examples of task-level benefits and reinforce the distinction between returns in selected workflows and visible gains across entire companies or sectors.
Spending is also concentrated. Ramp’s data show that its largest customers account for nearly all spending in several AI categories, while 80.4% of the top 1% of AI spenders in its data are venture-backed, compared with 13.1% of the median spender. That pattern suggests much of the current outlay is associated with a relatively narrow group of firms. It does not establish how much of that spending is ultimately productive or how representative those customers are.
“No Signs of AI Payoff Outside the Tech Sector”
— Torsten Slok, Apollo chief economist, in an October 24 Daily Spark note
How Much AI Is Paying Back
The available figures do not show how much of the technology giants’ stronger revenue per worker or margins is attributable to AI. Nor do broad productivity measures establish that AI has had no effect: gains may be too small, too recent or limited to specific tasks to appear in economy-wide data. “Zero payoff” is therefore stronger than what the aggregate evidence alone can prove.
Meta’s approximately $825 billion in listed future commitments is not the same as cash already spent, and the total includes infrastructure and other items not all identified as AI-related. The source material also does not provide a complete breakdown of expected returns, financing terms across the companies involved, or a consistent measure of AI spending and revenue across industries. The long-term cost of operating the infrastructure and the eventual value to customers remain uncertain.
Evidence to Watch in Coming Results
The next test is whether companies report sustained improvements in productivity, revenue or costs as AI tools move from trials into everyday operations. Investors will also watch how large infrastructure plans affect capital spending, cash flow and borrowing costs, and whether spending remains concentrated among a small group of buyers and providers.
For now, Apollo’s analysis offers a snapshot of limited aggregate returns alongside rising commitments, not a final verdict on AI’s economic value. New company results, independent productivity data and clearer reporting on AI-related revenue and expenses will help show whether task-level gains spread across businesses—and whether they justify the infrastructure bill.
Key Questions
What did Apollo conclude about AI’s economic payoff?
Apollo economist Torsten Slok said aggregate indicators showed no clear financial payoff outside the technology sector. That is his interpretation of trends in productivity, revenue per worker and margins, not proof that AI has produced no gains in any company.
What is included in Meta’s roughly $825 billion figure?
Meta’s filing lists 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. Much of it relates to data centers, servers, cloud capacity and network equipment, but the total is not all exclusively AI-related and is not money already spent.
Does the evidence show AI has no productivity benefits?
No. The aggregate data cited by Apollo show no visible broad productivity boost so far, while specific studies and experiments cited in the source material report gains in some customer-support and retail workflows. Task-level results do not establish economy-wide gains, and aggregate averages can hide differences between firms.
Why is AI spending concentrated among a few companies?
Ramp’s data show that a small share of its business customers accounts for most spending in several AI categories. The data also show a high share of venture-backed firms among the largest spenders. These figures describe Ramp’s customer base, so they should not be treated as a complete census of all companies.
Source: ThorstenMeyerAI.com
