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TL;DR
Apollo economist Torsten Slok says revenue per worker and profit margins are rising for seven major technology companies but remain broadly flat for the other 493 S&P 500 companies. That is an aggregate reading, not proof that AI has produced no gains anywhere: studies cited in the source report improvements in some customer-service and retail workflows, while most executives surveyed report no productivity impact so far.
Apollo chief economist Torsten Slok says current corporate data show no visible aggregate financial payoff from artificial intelligence outside the largest technology companies, even as Meta’s disclosed future commitments approach $825 billion and SpaceX has borrowed $40 billion to buy AI chips. The contrast highlights a central uncertainty for businesses and investors: spending on AI infrastructure is easy to count, but broad productivity and profit gains remain difficult to identify.
Slok’s conclusion appeared in Apollo’s October 24 Daily Spark note, titled “No Signs of AI Payoff Outside the Tech Sector.” The note compared the seven companies commonly called the Magnificent 7 with the other 493 S&P 500 companies. Apollo’s charts show revenue per worker and profit margins rising for the seven, while the corresponding measures for the other companies have remained broadly flat. Slok also cited productivity measures that, in the note’s assessment, show no clear AI-driven boost.
The figures do not directly measure the effect of AI on every company. A flat average can conceal firms whose gains are offset by losses elsewhere, and the data do not isolate AI from other economic forces. The source report also says Ramp data on business spending show that a small share of firms account for most purchases of model services and neocloud capacity. Those figures describe Ramp’s customer base, not the S&P 500 as a whole.
Meanwhile, Meta’s third-quarter results showed $34.91 billion in capital expenditures and negative free cash flow of $2.12 billion, compared with positive free cash flow a year earlier. The company’s 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. These obligations are not all specifically for AI; the source report says some include Reality Labs hardware. Meta’s 2026 capital-spending forecast is $135 billion to $145 billion.
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 Gains
The gap between investment and measurable returns matters because companies are committing capital, signing long-term capacity agreements and, in some cases, borrowing to secure computing resources before broad benefits are visible in financial results. If returns remain concentrated in a small number of technology firms, other businesses may face pressure to justify AI costs to investors and to decide whether to expand, redesign or limit their deployments.
That does not mean AI produces no value. The source report cites studies finding 14% more issues resolved per hour in a customer-support setting, with a larger gain for novice workers, and retail experiments ranging from no sales lift to a rise of as much as 16.3%, depending on the workflow. These results suggest that gains can appear in specific tasks, but they do not establish economy-wide returns. The report also says 83% of nearly 9,000 executives surveyed saw no productivity impact so far, with the average reported effect at 0.2% a year. Those survey results are not a substitute for a controlled measure of AI’s overall economic effect.
For readers, the practical distinction is between investment, adoption and realized returns. Large infrastructure budgets show that companies expect demand; they do not, by themselves, show that customers or workers are generating enough additional value to cover the cost. The financial risk becomes more material if capacity spending and financing costs rise faster than revenue or productivity gains.
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What Apollo’s Comparison Measures
Apollo’s note is a comparison of company-level trends, not a controlled experiment on AI. It tracks revenue per worker and margins for the Magnificent 7—Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia and Tesla—against the rest of the S&P 500. The note also cites San Francisco Federal Reserve productivity measures, which it says show no sign yet of AI lifting productivity growth. Those broad indicators can lag changes within individual firms and do not establish what caused a change in performance.
The spending figures offer a separate view of the scale of investment. The source report says forecasts for capital spending by Amazon, Alphabet, Meta, Microsoft and Oracle approach $780 billion in 2026, with projected annual totals exceeding $1 trillion from 2027 through 2030. Those numbers are forecasts, not contractual obligations. Meta’s approximately $825 billion figure instead combines several categories of future commitments disclosed in its filing; it should not be read as a single-year AI budget or as spending already paid.
Outside the largest technology companies, the report describes AI purchasing as concentrated among a small group of high-spending firms, many of them venture-backed. Slok has characterized some of that spending as a cost center and raised concerns about whether the marginal benefit of computing exceeds its cost. Those are his interpretations of the data, rather than a settled measurement of the returns to every AI deployment.
“No Signs of AI Payoff Outside the Tech Sector”
— Torsten Slok, Apollo chief economist, in the October 24 Daily Spark note
What the Aggregate Data Cannot Show
The available comparisons do not establish that AI caused the revenue, margin or productivity patterns Apollo describes. They also cannot show whether gains at individual companies are being canceled out by costs or weaker results elsewhere. The source report does not provide a controlled economy-wide estimate separating AI’s effect from interest rates, tariffs, labor costs or other factors.
It is also unclear how much of Meta’s disclosed commitments will ultimately be used, when they will be paid, or what share is directly tied to AI rather than other operations. Some amounts are leases or contracts extending over multiple years, and the commitments include items beyond AI. SpaceX’s $40 billion borrowing is reported as being for AI chips, but the source material gives limited detail on the financing terms or the returns expected from that investment.
The workflow studies and executive survey point in different directions because they measure different things. Specific task-level gains do not automatically translate into company-wide productivity, while a report of no impact so far does not rule out later benefits. The timing and distribution of any broader returns remain uncertain.
The Next Test Is Measurable Returns
The next evidence will come from company results and productivity data showing whether AI use contributes to sustained revenue growth, lower costs or higher output per worker. Investors will also be watching whether the largest infrastructure spenders can fund planned capacity without putting pressure on cash flow, credit conditions or other business priorities.
Meta’s 2026 spending outlook and its subsequent filings will provide updates on capital expenditure and contractual commitments. More broadly, companies will need to show whether specific deployments produce repeatable gains after accounting for model, infrastructure and implementation costs. Until those results are clearer, Apollo’s conclusion is best read as a statement about current aggregate trends, not a final verdict on AI’s long-term economic value.
Key Questions
What did Apollo conclude about AI returns outside technology?
Apollo chief economist Torsten Slok said its comparison of company-level trends shows no visible aggregate financial payoff outside the seven largest technology companies. The comparison does not prove that no individual non-tech company has benefited.
Does Apollo’s analysis prove AI has no economic value?
No. The note reports broad trends in revenue per worker, margins and productivity; it does not isolate AI’s causal effect across every company or task. The source report cites gains in some customer-service and retail workflows.
What does Meta’s roughly $825 billion figure represent?
It combines disclosed future leases, contractual commitments and contingent cloud purchases. It is not a single-year AI budget, and the source report says not all of the commitments are for AI.
Why do some AI studies show gains while executives report little impact?
Task-level studies and executive surveys measure different outcomes. A workflow can become faster without producing a measurable change in a company’s total productivity or financial results.
Source: ThorstenMeyerAI.com
