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TL;DR
Apollo chief economist Torsten Slok says revenue per worker and profit margins are rising among seven major technology companies but remain broadly flat across the other 493 S&P 500 firms. The analysis points to no clear economy-wide productivity gain yet, even as AI infrastructure spending and financing demands grow; evidence from specific workplace uses is more mixed.
Apollo chief economist Torsten Slok said an analysis published October 24 found no visible financial payoff from AI outside the technology sector in broad corporate data, even as companies commit heavily to computing infrastructure. The finding describes aggregate trends, not a direct measurement proving that AI has produced no benefit at individual firms.
Apollo’s “Daily Spark” note compared revenue per worker and profit margins at the seven companies often called the Magnificent Seven with those at the remaining 493 S&P 500 companies. Its charts show the seven’s inflation-adjusted revenue per employee rising to about $780,000 in the third quarter of 2026, while the other companies remained around $525,000, within a range they had occupied since 2021. The seven’s margins rose to roughly 30%, compared with about 10% for the other 493.
The note also cited San Francisco Federal Reserve productivity measures, which Apollo said showed no sign of AI boosting productivity growth. Separately, data from Ramp, a corporate spending platform with more than 85,000 U.S. business customers, indicate AI-related spending is concentrated among a small share of firms. The top 10% of spenders account for 99.5% of spending on model serving and inference, according to figures cited in the note. Those results describe Ramp customers and should not be treated as a census of all U.S. companies.
Slok’s broad conclusion contrasts with evidence that certain AI deployments can improve specific tasks. The source material cites a customer-support study reporting 14% more issues resolved per hour, with a 34% gain for novice workers, and retail experiments showing sales changes ranging from no increase to 16.3%, depending on the workflow. It also cites a survey in which 83% of nearly 9,000 executives said AI had not yet affected productivity. These observations use different methods and populations; they do not establish a single economy-wide effect.
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 central issue for businesses is whether expensive AI infrastructure and software will produce gains that can be seen in revenue, margins or output. Apollo’s figures suggest that, so far, those gains have not lifted the average performance of non-tech S&P 500 companies in the measures it examined. That raises questions for executives deciding how quickly to expand AI use and for investors judging whether current spending can earn a return.
The figures do not show that all AI projects fail. Aggregate averages can conceal firms or departments that benefit, as well as losses that offset gains elsewhere. Results from customer support and retail also suggest that effects may depend on how a system is introduced and which task it supports. For workers and consumers, the distinction matters: measurable improvements in a limited workflow do not necessarily translate into broad productivity growth, lower prices or higher corporate profits.
Meanwhile, investment commitments create financial exposure before returns are clear. Large infrastructure plans can involve long-term leases, cloud agreements and equipment purchases. If usage or revenue grows more slowly than expected, companies may face pressure on cash flow and margins. Apollo’s analysis focuses on the weak visible payoff; the spending figures show why the timing and scale of returns are receiving greater scrutiny.
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What Apollo’s Charts Compare
The note, titled “No Signs of AI Payoff Outside the Tech Sector,” was published October 24 and drew coverage the following day. It uses company-level financial and productivity indicators to compare the seven large technology firms with the rest of the S&P 500. The comparison is a snapshot of broad trends, not a controlled test isolating AI’s effect from other changes in the economy.
The source report also points to the scale of planned infrastructure spending. Meta’s October 21 third-quarter release reported $34.91 billion in capital expenditures for the quarter and negative free cash flow of $2.12 billion, compared with positive free cash flow of $10.6 billion a year earlier. Meta gave a 2026 capital spending outlook of $135 billion to $145 billion. Its October 22 filing listed about $355.73 billion in leases not yet started and $454.52 billion in non-cancelable contractual commitments, plus as much as $14.72 billion in contingent cloud purchases. The report says these commitments are largely related to data centers, servers and cloud capacity, but not all are exclusively for AI.
The source material also reports that SpaceX borrowed $40 billion to buy AI chips and describes growing attention to the financing available for data-center and cloud companies. Such examples show that AI development involves substantial spending, but do not establish whether those investments will ultimately be profitable.
“has delivered zero financial payoff to corporate America outside of tech.”
— Torsten Slok, Apollo chief economist, in the October 24 Daily Spark note
How Much AI Is Driving the Data
Apollo’s comparison cannot establish that AI caused the gap between the seven technology companies and the other 493. Revenue per worker and margins reflect many factors, including business mix, labor costs and market conditions. Flat group averages may also hide companies or teams with gains that are offset by weaker results elsewhere.
The source material does not provide a common methodology for comparing the cited customer-support study, retail experiments, executive survey and S&P 500 measures. Their figures cover different outcomes and settings. It is also unclear how much of Meta’s listed future commitments is specifically attributable to AI, and whether planned spending will be matched by sufficient demand or revenue. Apollo’s “zero” is therefore a forceful summary of its aggregate reading, not proof that AI produces no financial benefit anywhere outside tech.
Evidence to Watch in Coming Results
The next test will be whether company results and productivity measures show sustained improvement as AI tools move from experimentation into routine work. Investors will also watch whether large infrastructure commitments translate into revenue and whether spending pressures cash flow and margins. Future filings, earnings reports and productivity data can clarify those questions, but the source material gives no specific date for when a broad payoff should appear.
For now, the confirmed picture is mixed: spending is measurable and substantial, Apollo’s chosen indicators show no broad non-tech payoff, and some task-level studies report gains. How widely those gains can be reproduced—and whether they outweigh the cost of the computing and systems involved—remains unsettled.
Key Questions
What did Apollo’s analysis conclude?
Apollo chief economist Torsten Slok said the indicators he reviewed showed no visible aggregate financial payoff from AI outside tech. The note compared revenue per worker and margins at seven large technology companies with those at the other 493 S&P 500 firms.
Does “zero payoff” mean no non-tech company has benefited?
No. The phrase summarizes Slok’s interpretation of aggregate trends. Group averages can hide individual winners and losses, and the analysis does not directly test AI’s effects at every company.
What evidence of workplace gains is cited?
The source material cites a customer-support study reporting 14% more issues resolved per hour, with a 34% increase for novice workers, and retail experiments with sales changes from zero to 16.3%, depending on the workflow. These results do not establish an economy-wide productivity gain.
Why are companies’ AI spending plans part of the story?
Major infrastructure commitments require money before their financial returns are known. Meta reported $34.91 billion in quarterly capital expenditures and listed hundreds of billions of dollars in future leases and contractual commitments, although not all of those commitments are exclusively for AI.
What remains uncertain?
It is not yet clear how much AI is driving broad productivity or financial results, whether task-level gains will spread across businesses, or whether companies’ infrastructure spending will generate returns that justify its cost.
Source: ThorstenMeyerAI.com
